can chatbot write essays in french

The best French chatbots (and a few to avoid)

April 11, 2024 by Alysa Salzberg

This article contains affiliate links. This means French Together may earn a commission for purchases made through these links. Read our full affiliate disclosure .

Chatbots use AI to simulate a discussion with an actual person. In recent years, a number of French learning companies and individual tech fans have created chatbots to help users learn or practice French.

I’ve tested a few of the most popular ones to see how much they can help you with your French.

Here’s what I found out!

What to know about French learning chatbots

Before we begin our list, a few quick things to keep in mind:

• Chatbots use AI – that is, computer programs that have been taught French through programming. It’s important to remember that none of them involve actual communication with real French people .

• Many French learning chatbots are available for free, either for a limited time per day or even in some cases for unlimited use. Others are paid services or part of a paid French learning app .

• There are some advantages to using a chatbot – for instance, unlike a French tutor or friend, chatbots never sleep or go on vacation.

• Most chatbots allow you to communicate via text or audio. You can often switch between the two in the same conversation.

• Never forget that chatbots are not actual native French speakers and can (and often will) make mistakes or simply not react to you the way a real person would.

• French learning chatbots are also not usually for absolute beginners. Most of them will require at least basic conversation and comprehension skills.

• If you’re able to understand and communicate with them, chatbots can be a fun way to practice your French and challenge yourself. Some will even offer “role-play” options where you can try out scenarios like booking a hotel room or speaking to a doctor. But since not all of the French they use or understand is accurate, and because they may have bugs, it’s best to think of them as a little learning treat, rather than the main way you’ll learn French.

What’s the best French chatbot to use?

• The best French chatbot on our list is Memrise’s MemBot . It responded accurately and realistically no matter what I threw at it, and the corrections it made to written responses were accurate and showed an attention to detail. Also, unlike some other French chatbots on our list, the paid version of MemBot allows you unlimited chat time.

• Langua is the second best French chatbot I tried. Its role-plays are especially realistic and impressive. Unfortunately, its free version is limited to 15 messages although I have been told a more generous free trial will soon be available.

•Despite a few positive features, Talk Pal AI’s chatbot made some troubling French errors and should probably be avoided .

Here are more in-depth reviews of the chatbots I’ve mentioned, as well as three others I tried out.

Langua

Langua is a web app that offers a number of features for French learners, including a chatbot. There is both a free and paid version, but it’s hard to find clear information about pricing unless you already have an account.

• You can choose how to learn from a chat, with options to only listen to the bot, listen first then read, or only use text messages.

• You can record conversations and listen to them later

• Langua has a simple interface, which I always like since it’s easy to use, you don’t get distracted or lost, and also it means to me that the developers are more concerned with content than looks.

• You can choose what to chat about, or just do a role-play.

• The chatbot’s voice sounds natural and like a real speaker. It’s programmed to use some natural, informal expressions like C’est génial to react to statements.

• For the role-play, I chose the plumber scenario and was very impressed . While the plumber spoke a bit more slowly than the average French person, the vocabulary used and questions asked were exactly like what you’d hear in real life .

• The free version only allows a maximum of 15 messages to be exchanged. I was especially disappointed by this in one particular conversation, when the chatbot promised to tell me how to make my own dark chocolate just before I got to the message limit! This limit applies to all chats, so you can’t just start a new one.

• Even when settings are toggled to beginner level, chat options and possibilities are the same. There are no adapted or easier chat topics, etc. Of course, you can make the chat as simple or as complex as you’d like, but still, there is no basic chat where you can start by practicing things like saying hello, etc.

Langua Talk chat where bot's replies can be hidden or shown

How much does Langua cost?

Langua has both a free and a paid version.

The free version only allows you to send 15 messages maximum.

As of this writing, Langua AI offers a choice of 3 plans ranging from 12.90 USD/month to 29.90 USD/month or from 9.90 USD/month (billed annually) to 24.90 USD/month (billed annually.)

Langua isn’t perfect, but it’s a pretty great bot to use for practice and a great way to practice French conversation at an affordable price.

Gliglish is an online chatbot that you can access for free for 10 minutes (50 messages) a day. Or you can sign up for the paid version of Gliglish, which features up to 20 hours of conversation a month. Unlike some of the other chatbots on our list, Gliglish is a stand-alone, not part of a learning app . It does offer some features within the chat, like translations and corrections of dialogue, grammar feedback, and more. (That said, many other French chatbots offer these, too.)

• The bot offers to talk to you in a lot of different languages, including variants from different places, for instance French from France and Canadian French ; US English and UK English, etc.

• Users can practice with mainland French or Canadian French

• Gliglish looks great: Easy to use interface with 3-D animation like drawings of people for all scenarios, etc.

• There are two different chatbot modes, “Teacher” or “Role-play”.

• Role-play mode gives you a number of different situations to choose from, including Dans un taxi , Demander de l’aide à un inconnu , Au restaurant , and more.

• Recording audio responses was slower than I would have thought and soon ended in an error message on my computer and the whole app restarting when I tried it on an iPad. When I tried again with my computer, the app did recognize my mic and did a great job transcribing my responses . But there was still a response delay despite my normal responses, and also and much worse, after a short exchange, an error message came up again.

• The chatbot’s voice sounds a bit artificial compared to some other bots.

• As with some other chatbots, you can either type or talk freely or use one of three responses at bottom of page…but if you click on one it seems to do nothing. This happened with both chat modes.

• Gliglish does not seem to be set up for text exchanges , which means it can’t be used for French writing practice (although your entire conversation is transcribed, so it could help with reading) and may not be accessible for hearing impaired/Deaf users.

• Even when I tried to stick to one of the suggested responses, the bot still took time to process my answers and then ended up showing an error message after just a few exchanges.

• Interestingly, most of the few reviews I’ve found of Gliglish don’t mention bugs, but I’m not sure all of them are unbiased

• Gliglish also couldn’t recognize my phone’s mic and kept asking permission to use it. Error messages also frequently came up, putting a quick end to every conversation I tried.

• Gliglish’s paid version is expensive, considering it’s just a chatbot , not an entire French learning app, and even in the paid version, access to the chatbot is limited.

Good and bad

• Gliglish is entirely online and free, with no sign-up necessary, which means, among other things, that you can just spontaneously use it. But because of this, you can’t monitor your progress , etc.

• Role-play scenarios and instructions are entirely in French , so this is not for beginners.

• When I made a mistake that was noted in the transcription of my audio, there was no sign of it being incorrect. The bot repeated my response in a correct way, but not necessarily to correct my error. On the other hand, this is generally the way a server in a restaurant would do it – some French people will correct you but most will just repeat what you said (if appropriate, like repeating an order in a café) in the correct way.

How much does Gliglish cost?

Gliglish has a free and a paid version.

The free version of Gliglish lets you chat for 10 minutes (50 message exchanges) a day.

As of this writing, the paid version of Gliglish costs 29 euros a month for a monthly plan, or 23 euros a month (276 euros a year) for an annual plan.

The verdict

I’m really disappointed in my experience with Gliglish. This chatbot has so much promise, but it seems to have a lot of trouble recording and processing audio, or maybe just a lot of technical issues in general. Overall, Gliglish feels like an app that was lovingly made and is noble in its attempt to be free, but it has a lot of bugs, and these keep you from having more than a few lines of conversation at best. Because you can access it without creating an account, you may at least want to give the free version of Gliglish a try. Although I experienced bugs over several days, by the time you’re reading this, maybe they’ve been fixed.

Memrise MemBot

Personalized Memrise homepage, showing progress, upcoming lessons and more

I recently reviewed the entire Memrise French learning app (available as both a web and mobile app, with both a free and paid version). But in this review today, I’m focusing on Memrise’s chatbot, fittingly called MemBot. I tried MemBot when I reviewed the app and was more or less impressed by it. With Memrise’s free version, you get one conversation per day, while you get unlimited access with Memrise’s paid plan.

• MemBot is on point overall. It understood a somewhat informal response I gave ( Je trouve ca rigolo ) and even corrected it by adding the cedilla to ça . I was very impressed by this. Throughout the chat, MemBot continued to add missing accents to my responses.

• Memrise’s mobile app recognized my phone’s mic.

• The bot seems to understand spoken language well and impressed me by rolling with the punches. For instance, when it asked how my family was, I said my mother had started a new job and it reacted to that in a normal, human-like way. A follow-up remark I made about my mother being stressed had the bot say that change can be stressful. Very convincing.

• There is a brief explanation of the chat scenario at the start, in English, which is helpful for learners at lower levels.

• Unlike some other options on our list, the paid version of Memrise gives you unlimited access to its chatbot.

• MemBot made a pretty egregious pronunciation error right off the bat, pronouncing the verb porter like “porter” in English.

• The web app couldn’t recognize my computer’s mic.

• In the free version, chats are cut short, as I’m finding is the case with most free versions of chatbots and apps.

• Chats are unlimited with a paid plan, but still very short – you still only get a few questions and responses.

• The responses you can give to the chatbot aren’t scripted or multiple choice. This could make using MemBot hard for intermediate learners (this certainly isn’t for beginners), but also makes it far more realistic.

• MemBot’s voice is relatively realistic but a bit flat

• Some scenarios are better than others. The one asking for wifi didn’t have a lot of openings for other questions, and had a weird situation where the person in charge asked where I was from, which I don’t think would happen the same way in real life. But that said, when I tried to make the conversation more complex, by asking about local things to do, the bot did talk and respond properly. And after all, a person who is doing this conversation may just really want to practice the basics of asking if there’s wifi, which is totally fine and possible with the bot as well.

How much does Memrise MemBot cost?

Memrise has a free and a paid version.

The free version of Memrise will give you limited access to its features, including MemBot.

The paid version of Memrise, called Memrise Pro costs 11.99 euros per month (check the site on your computer for localized prices), 71.98 euros per year, or 185.99 euros for a lifetime subscription, as of this writing. Memrise Pro gives you unlimited access to MemBot.

Screengrab of a conversation with MemBot on the mobile version of the app.

Despite the occasional error, MemBot is the best French chatbot on our list, offering accurate and realistic responses, and attentive corrections to written responses. The paid version of the Memrise app is also one of the best deals for your money when it comes to chatbot practice, since it allows you unlimited access to MemBot.

Screengrab of Mondly chat introducing itself and giving instructions in English.

I recently reviewed the entire Mondly French learning app . While it had its positive sides, I overall found it visually cluttered and confusing . Mondly has several chatbot options, including the separate Mondly AR (Augmented Reality characters chat with you) and Mondly VR (users equipped with VR headsets can seem to have conversations with real French people in a VR setting). But the app also has a chatbot in its basic version, and that’s what I’m trying today.

• Mondly’s mobile app recognized my mic.

• The chatbot sometimes incorporates emoji into the conversation, which is a cute touch.

• Answer suggestions are provided, which can be helpful for lower level learners.

• Chats can go on for a very long, maybe even unlimited, time .

• Mondly’s chatbot starts off by hitting hard, telling you what you can say back (two response choices) before even letting you see how the bot has started the conversation. This sort of fits the vibe of Mondly’s cluttered, confusing interface.

• The web app’s microphone function seems impossible to use . The instructions say to tap and hold it, but no matter what I did would not record me. I did finally get it to hold and seem to record me but it turned out to be a false alarm.

• The chat has phrases that often don’t feel natural or correct . For instance, if someone says Bonjour, it’s not very common to say Bonne après-midi in reply. This is either very formal, like something a newscaster would say or it would possibly be a way to say goodbye. That’s one of several examples I came across of the word choice not necessarily being the most natural. This may have been done on purpose, in order to use a variety of vocabulary and phrases, but if you’re looking for practice when it comes to speaking French naturally, this ain’t it.

• Sometimes, even the pre-written multiple choice responses don’t get recognized, or the AI will recognize them and then shorten them.

• The chatbot didn’t always recognize my responses, even when it came to simple phrases like when I said J’aime la chanson française instead of one of the responses that were suggested.

• There’s no correction of mistakes either during a chat or after

• When you’ve finished a themed chat, the app says you now know how to say a particular word in French, even if you don’t. For instance, the chat I had was about saying hello, but was about much more than that.

• Now and then optional responses were said in a canned, artificial voice.

• There are suggested responses to each thing the bot says. This could be helpful especially for lower level learners. But it’s not made clear that you don’t have to use these if you don’t want to.

How much does Mondly cost?

Mondly has a number of versions, but the two mentioned here are the free version of Mondly and the basic paid version of Mondly.

Mondly’s free app gives you limited access to its learning resources, which include its chatbot.

Mondly’s paid, Premium version includes what seems like unlimited access to its chatbot – or at least, you’ll be able to use it whenever you want, for a long time. As of this writing, Mondly Premium costs $9.99 USD per month or $47.99 USD per year. You can also purchase a lifetime subscription for $199.99 USD. Sometimes, Mondly has sales and discounts, so check their website from time to time to see what’s on offer. You can also check Mondly’s website for prices in your local currency.

Screengrab of a Mondly chat with dubious choices of French vocabulary, as well as a few not great English translations.

Mondly let me have one of the longest chats I’ve had with a chatbot, but it was also one of the least satisfying , since I couldn’t always go off script, none of my mistakes were corrected or mentioned, and in the end I was told I’d completed the lesson successfully despite the fact that the bot must have thought some of my responses were incorrect. There was no incentive to practice and no record of these mistakes. For a pure chatbot, that might not matter but it’s a shame that Mondly, which is an entire learning app, wouldn’t be able to note these down at least or at least make corrections within the chat.

Talk Pal AI

Like some of the other entries on our list, Talk Pal AI is a standalone chatbot, not a French learning app with a chatbot. It’s also the most robotically named entry on our list. But its chatbot has a name, Emma. Talk Pal AI is available as both a web and a mobile app. There are paid and free versions. Talk Pal AI’s free plan allows 10 minutes of conversation a day . Paid plans offer unlimited access to the bot and a few additional features.

• You can choose the type of chat: serious, funny, or up to the bot’s discretion.

• The paid plan allows unlimited chatbot access.

• My conversation started with Emma greeting me with Hé , which is more a way to get someone’s attention than a French greeting . Politeness is important in French and this wouldn’t be a polite way to start a conversation , even with a friend. It’s clear this was directly translated from the English informal greeting “Hey”. Instead, it should be something like Salut (Hi).

• The bot’s pronunciation sounds off at times.

• Questionable language choices abound . At one point, Emma asked me Quelle est la pire date que vous ayez jamais connue? The Anglicism “date” is being used more and more by young French people, but if it were used this way, it would be pronounced with an exaggerated English pronunciation, which makes me think it was just a direct translation from English here. I also feel like, even if it was done deliberately, it doesn’t accurately represent the conversations most of us would have with most French people. It’s sort of like if you learned slang instead of the standard language first.

• The chat format is a bit disorienting. It doesn’t indicate that your answer has been recorded and there is no transcript of what you’ve said. I actually thought this was yet another web app that didn’t recognize my microphone. Then, after a several seconds’ delay, there was a reaction from the bot, followed by a transcript of what I’d said.

• The conversation couldn’t continue though, which I chalked up to Emma maybe being out of responses to the topic. So I pushed the button for her to ask me another question. She did, but when I tried to answer, this time it seemed that the app had simply stopped recognizing when I spoke. When I tried several other times, there would sometimes be dots as if my answer had been recorded and was being processed, but nothing ever resulted. The answers I gave were short and simple, so it’s not as if they were very long or out of context and would have confused the bot.

• There is an option to get feedback on what you said, but when I clicked on it, it told me that sorti should have been written sortie, since the speaker is a female. I wondered if the AI could recognize my voice and could thus tell I was female, but most of all, I found it frustrating, since the AI itself had transcribed my spoken answer. So essentially, the AI was correcting its own mistake! Although I guess you could say that this is a good thing anyway since it can serve as a review/reminder for users.

• The bot seems MUCH more adapted to written responses . Everything from the corrections to the time to analyze your responses work much better when conversations are text-only.

• The chat seems to go on for an unlimited amount of time (if you can get the mic to work or if you switch to a written conversation), even though for me, at least, the exchange gets a bit repetitive.

How much does Talk Pal AI cost?

Talk Pal AI has both a free and paid version.

The free version of Talk Pal AI gives you access to 10 minutes of conversation a day.

The paid version of Talk Pal AI costs $4.99 a month ($59.88 a year) for an annual plan or $9.99 for a monthly plan.

Screengrab of a Talk Pal AI conversation with questionable vocabulary choices

In addition to bugs and some other issues that no chatbot seems entirely immune to, Talk Pal AI has some troubling errors and inaccuracies and should probably be avoided.

Because of this, I, unfortunately, can’t recommend Talk Pal.

Not to be confused with the first entry on our list, Langua, Langotalk is a paid-only chatbot with a few additional learning features, like AI tutors. It’s available as both a web and a mobile app. This is one of the few chatbots on our list that claims to have chats adapted to different learning levels.

• Langotalk has an easy-to-use platform , with no frills navigation, making it easy to find what you want.

• Each chatbot is associated with a friendly-looking cartoon portrait, a bit like Duolingo.

• The chatbot I chose sounded very realistic. His informal French even included some very typical anglicisms like “Cool” (as opposed to more recent/niche ones like Talk Pal AI’s use of “date” (which I still suspect was just a direct translation from English)).

• This is one of the few apps that could recognize my computer’s mic .

• The chatbot transcribes audio well and without errors. It’s helpful to see the grammatically correct and correctly spelled version of phrases, and if users want more practice with this they could switch to typing.

• A few bugs aside, I found the bot voice very convincing , as well as its ability to talk about a variety of topics, even very off topic from where we started.

• This also may be the longest chat I’ve had. It went on so long that I almost found myself getting bored! So if you want a lot of pretty realistic practice with few bugs, this paid option could be a good choice.

• There are even some role-plays that can help you practice things like job interviews. I was very impressed that the job interview one actually used typical phrases you’d hear in a real French job interview…even if you said you were a magician, like I did.

• Weirdly, you get interrupted in middle of the chat by an announcement of a one-day streak. Why not have this at the end of the chat? A second encouraging message downright cut off my conversation and seems like it might have interfered with my mic because my recording didn’t show up in the chat and the bot repeated itself.

• The bot sometimes adds emoji to what it’s saying/typing. This is cute but the bot frequently says the emoji out loud, as if it’s part of what it was saying. For instance, if there’s a baguette emoji at the end of the phrase, you’ll hear: “Moi aussi. Baguette.”

• The chat bugged at the end when I said I had to go – repeated a goodbye twice and then asked me a new question.

• The male voices all seem to be the same.

• This is one of the few chatbots on our list that claims to have different levels for learners . But the beginner chat isn’t really for absolute beginners. It starts with standard things like Bonjour and Comment t’appelles-tu but then quickly uses other tenses, etc. and goes off into other subjects or tries show conjugations and give other explanations. It’s cool in a way but kind of overwhelming because it goes from subject to subject, not structured learning. I think it would be hard for a beginner to take all of this in. Even when I tried to say I thought I wasn’t good in French, the bot had a reassuring response, then moved on and started grilling me on the verb être .

• With this in mind, the Beginner chats lack the appeal of most chatbots (including the non-beginner ones on Langotalk), where you feel like you’re having a real conversation. This was truly like having a conversation with a robot!

• You can use your mic, but unlike most other chatbots you have to choose the mic icon all the way in the top right corner, which is a little confusing at first.

• The bot doesn’t openly correct your mistakes when you type but you can click the little pen icon below what you’ve written to get a translation and correction of any mistakes – accent marks included.

• There are many other chats, role plays, and more. The beginner ones do all seem more like lessons or having info thrown at you than role plays or general chats. But it’s cool to see the variety of chats available and the fact that they will be long is also impressive.

How much does Langotalk cost?

Langotalk is available as a web and a mobile app. There is no free version.

As of this writing, Langotalk costs 19.99 euros a month or 139.99 euros for lifetime access. Check the local version of the website for prices in your currency.

A convincing informal French conversation with the Langotalk chatbot

Though it sometimes gives “Duolingo wannabe” vibes – which even sometimes trip it up – Langotalk really stands out as one of the best French chatbots out there. Its beginner lessons are a bit too tense and strict to have the appeal of a chatbot (or even, I think, to be able to effectively teach beginner students). But its other chatbot options feature conversations and role-plays that feel very realistic. And chats seem to go on for an unlimited stretch of time.

Other French learning chatbots worth mentioning

Here are two other French chatbots that might be worth trying out.

Duolingo Max

When I reviewed Duolingo , the free app totally charmed me with its delightful characters and varied French exercises. Now, there’s a paid option, Duolingo Max , that lets you practice French with a chatbot, among other features.

As I was hoping, the chatbot takes on the roles of different Duolingo characters. Characters change depending on the scenarios you choose. This is a role-play -based chatbot , not one that lets you have randomly generated conversations, which is a bit of a letdown, since I would have loved to just talk to cynical teen Lily about life. But the idea is still pretty great.

And now, for some bad news: As of this writing, Duolingo Max and its chatbot is only available in the U.S., Great Britain, Ireland, Canada, Australia, and New Zealand . That list doesn’t include France, where I live, hence the reason I haven’t personally tried it out yet. It also only has an iOS version for now. Duolingo’s official press release says that Duolingo Max will be available in more countries and in an Android version soon , so if you’re not able to get it for geographic or OS reasons, keep checking Duolingo to see if that’s changed.

Language learning YouTuber Spanish Blueprints was able to try Duolingo Max for French and said that the role-plays were challenging and showed him how much more he needed to learn when it came to making conversation in French. He’s apparently been using regular Duolingo for French for two years now, so this might seem a bit concerning, but then, Duolingo isn’t an app focused on French conversation skills the way French Together is.

The reviewer also says that unfortunately, the role-plays fit in with lesson plans and aren’t just freely accessible the way some other Duolingo features (or chatbot role-plays on some of the other apps in this article) are, so that’s something to consider as well.

How much does Duolingo Max cost?

According to Duoplanet , as of this writing, Duolingo Max has different pricing based on your location. For instance, a monthly plan will cost you $14 in the US and £9.99 a month in the UK.

Jam is a different kind of French chatbot because it’s not specifically intended to teach users French or help them practice. Instead, it selects news stories of all sorts and lets users discuss them with its chatbot. Because it’s entirely in French and uses real French media sources, it’s definitely not for beginners or maybe even intermediate students, but advanced intermediate and proficient students might enjoy the chance to practice this way.

If this sounds like the perfect chatbot for you, the good news is that Jam is free. The bad news is that it may not be easy, or even possible, for you to have access to it. The reason I haven’t tried out the Jam chatbot, myself, is that it’s only available through Facebook Messenger . So those of us who don’t have a Facebook account and don’t want to sign up for one are out of luck for now when it comes to the Jam chatbot.

How much does Jam cost?

Jam is free to use via Facebook Messenger.

Can a chatbot make me fluent in French?

Some chatbots may be really advanced and convincing, but they remain AI, not people . This means even the best of them might have errors in their programming or not be able to really respond the way an actual person would.

Chatbots can be a fun way to practice your French, or even, as Spanish Blueprints realized, to test your abilities to answer questions in French without any kind of prompt or hints (in most cases). But regardless of the extra features they have, chatbots can’t make you fluent in French, and they should be used with caution.

Ideally, a chatbot could be one of the many tools in your French learning arsenal. For instance, you might be using an app or two for general French learning (one of my favorites of these is Rocket French). You might have an additional app that will help you focus on a particular aspect of French that you want to practice or review (for instance, the French Together app will help you improve your French conversation skills). You should also be reading, listening to, and watching things in French.

However you practice French, bonne continuation (keep it up, and good luck) on your French learning journey!

The Top 3 French Chatbots for Realistic Language Practice

So, this seems like a pretty normal conversation, right?

Bonjour. (Hello)

Bonjour! Comment vas-tu? (Hello! How are you?)

Je vais bien, merci. (I’m well, thanks.)

But it is not.

What if I told you that conversation was not between two friendly French-speakers?

Or even between two people?

Would you believe it was between a budding French learner and a robot ?

Why a French Chatbot Should Be Your New Language Buddy

French chatbots act as virtual francophone buddies that we can practice our (less than perfect) French speech on. The best part is that you can practice without judgment .

Mistakes are a part of learning anything new and language is certainly no exception. Practicing with a chatbot can help relieve the anxiety of making mistakes and get you comfortable communicating in French, until you are ready to try it with a real person. In fact, many of them will even help you notice your mistakes or correct them so you can catch bad habits before they start.

French chatbots are also great because they are so convenient ! You can open one of the apps below anytime and start talking with a chatbot about whatever.

Finally, these chatbots cover a range of French learning needs . Not all chatbots are made just the same! Some are specifically designed to teach you French with a focus on themed vocabulary, conversation skills and more. Others are designed for native French speakers but can be put to great use for natural language practice.

No-stress French: 3 Chatbots for Judgment Free Conversation Practice

Before you jump into foreign territory and download or purchase the first chatbot you see, review our list of the best French chatbots to help you on your language learning journey.

These are our favorites, but there are plenty more out there for ambitious language leaners to explore. For an in-depth list of non-English chatbots, check out this page on Chatterbot Collection .

Not only does the French chatbot already understand over a million phrases, it responds with a voice as well.

It gives users practice of conversational French in various scenarios , such as ordering from a restaurant, hailing a cab or visiting a tourist site in France. Within the selected scenario you will hear the chatbot ask you a French question, and you will see suggestions for how to respond written on the screen. Then you respond by holding down the microphone button and speaking. You can also click the keyboard icon to type your response if you prefer.

English translations are provided, but you can toggle them off if you are ready for more of a challenge.

If you love this type of language learning, Mondly takes it to the next level with a tool called Mondly VR . VR stands for “virtual reality.” You will get to explore a digital world and chat with the characters you meet, kind of like a video game. You will still get suggested responses, speech recognition and everyday conversation topics, but in an even more immersive environment.

If you have polyglot dreams, Mondly is available in 33 languages.

There is not just one bot personality, but several chatbots who talk with you about different topics . They will ask questions that are designed to flex your vocabulary and grammar skills. You will read the bots’ messages and also hear them spoken out loud, and you will type your responses. Do not worry if you get stumped—there are hints and suggested responses.

Chat subjects include cooking and dining out, driving directions, leisure activities and more.

From beginner to advanced, the Duolingo bots can accommodate every skill level. The app even offers an initial language test to verify your French skill level, if you are uncertain.

The chatbots are only available on the iOS version of the Duolingo app for now.

The bot operates through Facebook Messenger. It is designed to be a cool, culturally-savvy virtual buddy . It picks daily topics from the media to discuss, asks fun and motivational questions and even offers some games and quizzes. It always chats with a sense of humor , according to the chatbot’s reviewers.

Jam will toss some topic ideas your way—recent topics have included everything from Ethiopian politics to freelance work to ice cream. You can also choose what time Jam will message you, which is perfect for adding some routine French conversation practice into your day.

Since Jam is designed for native speakers, a strong level of French comprehension is needed to get the most out of it. However, Jam will suggest answers to its questions, so you will not totally lose the thread of the conversation.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aliquam accumsan est at tincidunt luctus. Duis nisl dui, accumsan eu hendrerit sit amet, rutrum efficitur lacus.

Amy Adams Creative Student

Over 12,000 5 Star Ratings

Rated 5/5 by 12,000 Students

How to Learn French Speaking Fast: The No-fuss Guide to Top Online Tools and Techniques

Here Are 6 Accredited Online French Courses That Offer High School Credit

Stand Tall! The Guide to Confidence with French Word Order

DANA Education Group is a one stop, comprehensive education provider that aims to meet various educational needs of its students of different ages, enabling them to perform more efficiently in school, college, and the workplace.

Lingua Fresca

Free AI language chatbot. Practice anywhere, anytime.

Tell the AI you want to talk about specific things and practice those scenarios

Enable your French keyboard on your device

To practice speaking (with French keyboard enabled), use the microphone feature on your mobile device’s keyboard.

Engage with Chat GPT Français: A New Era in AI Technology

Table of content.

Chat GPT Français is a cutting-edge AI technology that opens up a new era of seamless French conversation and transformative linguistic capabilities. Developed by OpenAI , this chatbot has gained global recognition and become a phenomenon since its release in mid-November 2022. With millions of users embracing its functionalities, Chat GPT Français has proven its versatility in various tasks, including writing poetry, building apps, and conducting therapy sessions. However, concerns have been raised regarding the accuracy and potential bias in Chat GPT Français’ responses.

Despite the controversies, the success of Chat GPT Français has propelled OpenAI into the ranks of Silicon Valley power players. The company recently sealed a groundbreaking $10 billion deal with Microsoft , showcasing the immense value of their AI technology. In addition, Apple and Google have expressed interest in collaborating with OpenAI , solidifying their position as industry leaders.

The rise of Chat GPT Français and other generative AI models is revolutionizing the future of work. These AI models push the boundaries by enabling faster and more efficient production of text and code. They offer a wealth of possibilities in natural language processing, allowing for enhanced creativity and the generation of original content.

However, the implementation of generative AI comes with its challenges. Bias and accuracy of responses are critical concerns that need to be addressed to ensure accurate and unbiased communication. Improving filters to catch inappropriate content is another area that requires attention. Additionally, determining intellectual property rights in the context of generative AI poses ethical considerations that must be carefully navigated.

Key Takeaways:

Chat GPT Français is a revolutionary AI technology enabling seamless French conversation and language processing.
Despite concerns about accuracy and bias, Chat GPT Français has achieved global recognition and popularity.
OpenAI’s success with Chat GPT Français has led to major partnerships, including a $10 billion deal with Microsoft .
Generative AI models like Chat GPT Français have the potential to transform work by facilitating faster and more efficient production of text and code.
Challenges such as addressing biases, improving filters , and determining intellectual property rights must be addressed for the responsible adoption of generative AI.

The Rise of Chat GPT Français and AI Chatbots in French

Since its launch in November 2022, Chat GPT Français has taken the AI world by storm, catering to the linguistic needs of millions of French speakers and revolutionizing the way AI chatbots are utilized in the French language. This French-speaking chatbot developed by OpenAI has quickly gained popularity and been embraced by users looking for seamless and natural conversations in French.

Chat GPT Français has proven to be a versatile tool, capable of assisting users with various tasks. From writing poetry to building apps and even conducting therapy sessions, this AI chatbot has demonstrated its potential to enhance productivity and creativity across different domains. Its ability to understand and respond in French has made it a valuable asset for individuals and organizations alike.

Benefits of Chat GPT Français
1. Seamless French conversations in real-time
2. Improved productivity and efficiency
3. Versatility in various tasks and applications

“Chat GPT Français has revolutionized the way we communicate and process language in French. Its ability to understand and respond accurately in real-time has made it an invaluable tool for French speakers around the world.” – French AI enthusiast

Despite its success, Chat GPT Français has faced some criticism concerning its accuracy and potential biases in responses. OpenAI has been actively working to address these concerns and improve the chatbot’s performance. As the field of AI chatbots continues to evolve, the ethical implications surrounding their use in generating content and determining intellectual property rights are also being examined.

OpenAI’s Chat GPT Français has not only gained recognition among users but has also attracted attention from industry giants. With a recently signed $10 billion deal with Microsoft , OpenAI’s position as a leading player in AI technology has been solidified. Companies like Apple and Google have also expressed interest in exploring partnerships, further cementing the significance of Chat GPT Français and its potential impact on the future of AI technology.

Pushing the Boundaries: Generative AI and the Future of Work

With its advanced natural language processing capabilities and generative AI models , Chat GPT Français is leading the way in transforming the future of work by enabling faster and more efficient production of text and code in the French language. The rise of generative AI models, including Chat GPT Français, has revolutionized the way organizations approach language processing and content creation.

These generative AI models have the ability to generate accurate and contextually relevant text in real-time, saving valuable time and resources for businesses operating in French-speaking regions.
Organizations can leverage Chat GPT Français to automate repetitive tasks, such as drafting emails, writing code, or generating content, thereby freeing up valuable human resources to focus on more strategic and creative endeavors.
Moreover, these AI models have demonstrated their creativity by producing original and innovative content, further expanding the possibilities for businesses in the French language market.

By utilizing natural language processing in French , Chat GPT Français streamlines communication and increases productivity, offering new opportunities for businesses across industries.

Transforming Content Production: Faster Text and Code Generation

One of the key benefits of generative AI models like Chat GPT Français is their ability to facilitate faster and more efficient production of text and code. With the advanced algorithms and language processing capabilities, these AI models can quickly generate accurate and relevant content in French, significantly reducing the time required for manual content creation. This accelerated content production can have a wide range of applications, from drafting reports and presentations to writing software code and creating marketing materials.

Furthermore, the use of generative AI models enables businesses to scale their content production capabilities without the need for extensive human resources. This can be particularly beneficial for organizations operating in fast-paced industries or those that require a high volume of content in the French language.

Benefits of Generative AI Models for Text and Code Generation
1. Increased productivity and efficiency
2. Accelerated content creation in French
3. Scalability without extensive human resources
4. Consistency and accuracy in content production

“The rise of Chat GPT Français and other generative AI models has opened up new possibilities for businesses in the French language market. These models are transforming the way organizations approach content production, making it faster, more efficient, and scalable. It’s an exciting time for businesses looking to harness the power of AI for their language processing needs.”

While the potential of generative AI models is vast, it is important to address challenges such as biases, inappropriate content, and intellectual property rights. By implementing proper filters and refining the algorithms, organizations can mitigate these concerns and leverage the full potential of generative AI for their content production requirements in the French language.

Overcoming Challenges: Addressing Biases and Ethical Implications

While Chat GPT Français offers groundbreaking technology, there are challenges to be addressed, such as biases in AI chatbot responses and the importance of improving filters to maintain accuracy and fairness.

Biases in AI chatbot responses pose a significant concern as they can perpetuate stereotypes or discrimination. These biases can arise due to the inherent biases in the data used to train the AI models or from the interactions and language patterns of the users. It is crucial to develop and implement systems that can detect and mitigate biases in real-time, ensuring that the responses provided by Chat GPT Français are equitable and unbiased.

Improving filters is another critical aspect in addressing the challenges of AI chatbots. Filters help identify and filter out inappropriate or offensive content, enabling a safe and respectful user experience. OpenAI and other organizations working with generative AI models must invest in continuous research and development to enhance these filters. Striking the right balance between filtering out inappropriate content and allowing free and open conversation is key.

Intellectual Property Rights and Ethical Considerations

The rise of generative AI models like Chat GPT Français also raises ethical considerations and intellectual property rights issues. As AI creates text and code that was previously the work of humans, questions around ownership and attribution arise. It is essential for businesses and individuals to understand the legal and ethical implications of using AI-generated content and respect intellectual property rights.

Moreover, the potential for misuse or malicious intent with generative AI technology cannot be ignored. While AI has incredible potential to transform various industries, its use should be guided by ethical frameworks. Safeguarding against the creation and dissemination of harmful or false information is crucial to maintain trust and integrity in AI systems.

In conclusion, the advent of Chat GPT Français and generative AI models has revolutionized the way we interact with technology. However, challenges such as biases, filter improvements, and ethical considerations need to be addressed for their responsible implementation. By recognizing these challenges and actively working towards solutions, we can harness the transformative potential of AI chatbots while safeguarding against potential risks.

Industry Recognition and Partnerships: OpenAI’s Ascend

OpenAI’s success with Chat GPT Français has propelled them into the ranks of Silicon Valley power players, leading to a groundbreaking $10 billion deal with Microsoft and attracting the attention of industry giants like Apple and Google. This partnership signifies the immense potential and market value of OpenAI’s AI technology, particularly their Chat GPT Français chatbot, which has garnered global acclaim since its release in November 2022.

OpenAI’s $10 billion deal with Microsoft is a testament to the impact and significance of Chat GPT Français in the AI landscape. It signifies both companies’ commitment to advancing AI technology and their belief in the transformative power of Chat GPT Français. With this partnership, OpenAI has solidified its position as a key player in the field, positioning itself as a leader in developing cutting-edge AI technologies.

Apple and Google’s interest in OpenAI’s technology further cements the industry’s recognition of the potential of Chat GPT Français and generative AI models. These companies understand the strategic importance of investing in AI advancements, and OpenAI’s impressive track record has captured their attention. The collaboration between OpenAI and these industry giants has the potential to facilitate the widespread adoption of Chat GPT Français and accelerate advancements in AI technology.

OpenAI Ascend: Expanding Horizons of AI

OpenAI’s ascension to the upper echelons of the tech industry is unparalleled. The $10 billion deal with Microsoft is a significant milestone, opening doors to new possibilities and collaborations. This partnership has propelled OpenAI to the forefront of the AI revolution, enabling them to actively shape the future of technology and establish themselves as a dominant force in the market.

As Apple and Google express their interest in OpenAI’s technology, it is clear that the industry recognizes the caliber and potential of Chat GPT Français and generative AI. OpenAI Ascend signifies not only the recognition of their achievements but also the growing importance and integration of AI in various sectors. This collaboration has the power to drive innovation, transform industries, and unlock new horizons for AI technology.

OpenAI’s Achievements	Industry Partnerships	Key Developments
Global success of Chat GPT Français	$10 billion deal with Microsoft	Advancements in natural language processing
Application in writing poetry, building apps, and conducting therapy sessions	Interest from Apple and Google	Faster and more efficient production of text and code
Addressing concerns about accuracy and bias	Collaboration with industry giants	Ethical considerations and intellectual property rights

In conclusion, Chat GPT Français and generative AI models have ushered in a new era of seamless French conversation and transformative linguistic capabilities. Since its release in mid-November 2022, Chat GPT has become a global phenomenon, embraced by millions of users for various tasks such as writing poetry, building apps, and conducting therapy sessions. This revolutionary AI technology has propelled OpenAI into the ranks of Silicon Valley power players, with a recent $10 billion deal with Microsoft and interest shown by Apple and Google in their technology.

However, as with any powerful AI tool, there are concerns surrounding the accuracy and bias of Chat GPT’s responses. It is crucial to address these challenges and navigate the ethical considerations to ensure the full potential of Chat GPT and generative AI models can be realized.

The rise of Chat GPT and other generative AI models has the potential to transform the future of work. By pushing the boundaries of what AI can do, these models enable faster and more efficient production of text and code. They exhibit creativity and the ability to generate original content, revolutionizing language processing and content creation. However, there are still challenges to overcome, such as addressing biases, improving filters to catch inappropriate content, and determining intellectual property rights.

Business leaders and organizations need to proceed with caution and carefully consider the ethical and practical implications of using generative AI. While the benefits and transformative capabilities are undeniable, it is crucial to ensure responsible and unbiased implementation to create a positive impact on society and maximize the potential of Chat GPT Français and generative AI models.

What is ChatGPT?

ChatGPT is a chatbot developed by OpenAI that allows users to engage in conversation and receive responses generated by artificial intelligence.

How popular is ChatGPT?

ChatGPT has become a global phenomenon since its release in November 2022, attracting millions of users worldwide.

What can ChatGPT be used for?

ChatGPT can be used for various tasks such as writing poetry, building apps, and conducting therapy sessions.

Are there concerns about the accuracy of ChatGPT’s responses?

Yes, there have been concerns about the accuracy and bias of ChatGPT’s responses, which need to be addressed.

How has ChatGPT contributed to OpenAI’s success?

ChatGPT’s success has helped propel OpenAI into the ranks of Silicon Valley power players, leading to a $10 billion deal with Microsoft and attracting interest from Apple and Google.

What potential does generative AI have?

Generative AI models, including ChatGPT, have the potential to transform work by enabling faster and more efficient production of text and code.

What challenges need to be overcome in using generative AI?

Challenges include addressing biases, improving filters to catch inappropriate content, and determining intellectual property rights.

What should business leaders consider when using generative AI?

Business leaders should proceed with caution and consider the ethical and practical implications of using generative AI in their organizations.

Can I Try Chat GPT Français for Free?

Yes, you can experience Chat GPT Français for free with a free trial. This allows you to try out the chatbot’s capabilities and see how it can assist you with your French language needs. Sign up for the experience chat gpt free trial and see for yourself!

Source Links

https://www.nytimes.com/2023/02/03/technology/chatgpt-openai-artificial-intelligence.html
https://hbr.org/2022/12/chatgpt-is-a-tipping-point-for-ai
https://www.mckinsey.com/capabilities/quantumblack/our-insights/generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business

Top 10 Best Apps That Write Essays for You in 2024
Effective Press Release Examples: Inspiring…
Top 7 AI Chatbots for 2024: Unveiling the Best…

Using AI Content Tools for Effective Social Media Marketing: A Comprehensive Guide

Inbox Mastery: Essential Email Subject Line Best Practices for Improved Communication

Top 8 Essential Chrome Extensions for YouTube Creators in 2024

How to Learn with French ChatGPTs AI tool? [Free Guide]

Learning a new language can be a challenging task, but with the right tools and resources, it can be an enjoyable and rewarding experience. One such tool that can help you learn French is ChatGPT, a conversational chatbot powered by artificial intelligence. In this blog, we will explore how to learn French with ChatGPT and how it can help you improve your language skills.

If you're considering learning French, there are numerous reasons why you should start using ChatGPT as your language learning tool. Firstly, ChatGPT is a conversational chatbot that uses artificial intelligence to simulate real-life conversations in French. It can help you improve your speaking, listening, and comprehension skills by providing you with a range of conversational scenarios. You can practice different topics, such as introducing yourself, ordering food at a restaurant, or making small talk with a friend. The chatbot is designed to adapt to your level of proficiency, so it can provide you with the appropriate level of challenge.

Through conversations with the AI language model, you can practice speaking and improve your conversational skills in French. Additionally, ChatGPT offers a vast database of vocabulary and grammar rules, allowing you to expand your knowledge of the language. With instant feedback and accurate translations, you can confidently navigate French grammar and build a strong foundation. Moreover, ChatGPT provides cultural insights, helping you immerse yourself in the rich French heritage. By using ChatGPT, you gain access to a personalized learning experience, tailored to your needs and preferences.

There are several effective ways to use ChatGPT to learn French . Here are some suggestions:

Conversational Practice: Engage in conversational practice with ChatGPT to improve your speaking skills. Initiate conversations on various topics, ask questions, and respond to prompts. ChatGPT will provide interactive dialogue, allowing you to practice your French in a supportive environment.
Vocabulary Expansion: Ask ChatGPT for translations of words or phrases you want to learn in French. You can also inquire about synonyms or antonyms to enhance your vocabulary. Take advantage of the vast database of words and expressions available through ChatGPT to strengthen your language skills.
Grammar Guidance: Seek help from ChatGPT to clarify french grammar rules and concepts. Ask questions about specific grammar structures, verb conjugations, or sentence formations. ChatGPT can provide explanations and examples to assist you in understanding and applying French grammar effectively.
Writing Practice: Utilize ChatGPT for writing practice in French. Submit written prompts or paragraphs to receive feedback and corrections on grammar, vocabulary, and sentence structure. Writing with ChatGPT can help refine your written expression and improve your overall language proficiency.
Cultural Insights: Engage in conversations with ChatGPT about French culture, traditions, literature, or current events. Ask questions about famous French authors, films, or historical events to gain a deeper understanding of the cultural context surrounding the French language. This will enrich your language learning experience.
Language Immersion: Immerse yourself in the French language by regularly interacting with ChatGPT. The more you engage in conversations, ask questions, and seek translations, the more exposure you'll have to the language. This immersion will help you develop a natural feel for French expressions, idioms, and language patterns.
Personalized Learning: Take advantage of ChatGPT's ability to adapt to your individual learning needs. Customize your conversations and requests based on your specific goals and areas of improvement. This personalized approach will enable you to focus on the aspects of French learning that matter most to you.

Practical applications of ChatGPT in Language Learning:

In this section, we delve into the practical realm of learning French with ChatGPT. Through a series of real-life examples, we showcase how this AI language model can be your trusted companion on your language learning journey. From conversational practice to grammar assistance, vocabulary expansion, and cultural insights, these practical examples demonstrate how ChatGPT can elevate your French learning experience. Get ready to unlock the potential of ChatGPT as we explore its hands-on applications and discover how it can help you become a confident and proficient French speaker.

Example 1: User: Bonjour ! Comment ça va aujourd'hui ? J'aimerais pratiquer mon français avec vous. ChatGPT: Bonjour ! Je vais bien, merci. Je serais ravi de t'aider à pratiquer ton français. Qu'est-ce que tu aimerais discuter ? Translation: User: Hello! How are you today? I would like to practice my French with you. ChatGPT: Hello! I'm doing well, thank you. I would be delighted to help you practice your French. What would you like to discuss?

Example 2: User: Pouvez-vous me poser des questions en français pour que je puisse m'entraîner à répondre ? ChatGPT: Bien sûr ! Voici une question : Quel est ton plat français préféré ? Translation: User: Can you ask me questions in French so that I can practice responding? ChatGPT: Of course! Here's a question: What is your favorite French dish?

Example 3: User: Pouvez-vous me donner la traduction du mot 'amour' en français ? ChatGPT: Certainement ! Le mot 'amour' se traduit en anglais par 'love'. Translation: User: Can you give me the translation of the word 'amour' in French? ChatGPT: Certainly! The word 'amour' translates to 'love' in English.

Example 4: User: Quels sont les synonymes du mot 'beau' en français ? ChatGPT: Il y a plusieurs synonymes du mot 'beau' en français, tels que 'joli', 'splendide', 'charmant', 'élégant', et 'ravissant'. Translation: User: What are the synonyms of the word 'beau' in French? ChatGPT: There are several synonyms of the word 'beau' in French, such as 'joli', 'splendide', 'charmant', 'élégant', and 'ravissant'.

Example 5: User: Pourriez-vous me donner un exemple de phrase utilisant le mot 'vif' ? ChatGPT: Bien sûr ! Voici un exemple : "Le feu d'artifice était magnifique, avec ses couleurs vives qui illuminent le ciel." Translation: User: Could you give me an example sentence using the word 'vif'? ChatGPT: Of course! Here's an example: "The fireworks were magnificent, with their vibrant colors illuminating the sky."

Remember, these are just examples, and ChatGPT can provide a wide range of responses depending on the specific context and input.

Use ChatGPT while you learn French with Lingopie

What is lingopie.

Lingopie is a game-changing language learning platform that integrates popular TV series into your language education. It provides an immersive and entertaining approach to language learning by offering a vast library of TV shows and series from different countries, all with interactive subtitles and customizable learning features. With Lingopie, you can watch your favorite shows in the language you're learning, allowing you to absorb the language naturally and gain exposure to authentic conversations, cultural nuances, and colloquial expressions.

The platform caters to learners of all levels, from beginners to advanced learners, with a range of difficulty levels. Lingopie's innovative learning tools, such as dual subtitles, interactive quizzes, vocabulary lists, and progress tracking, make language learning engaging and effective

Vocabulary Matching

Ask ChatGPT to provide a list of key vocabulary words from "Lupin" and their English translations. Then, create a matching exercise where you try to match the French words to their corresponding English translations.

Create dialogues between characters from "Lupin" using ChatGPT. Take on the role of one character and ask ChatGPT to respond as another character. This exercise will allow you to practice writing dialogue in French while exploring the personalities of the characters.

Cultural References

Watch an episode of "Lupin" and take note of any cultural references or allusions. Then, ask ChatGPT to provide explanations or background information about those references. Discuss the cultural significance of these elements and how they contribute to the overall story.

Fill in the Blanks

Provide ChatGPT with a short excerpt or quote from "Lupin" with certain words or phrases missing. Ask ChatGPT to fill in the blanks, testing your comprehension and vocabulary knowledge. Compare your answers with ChatGPT's suggestions.

"Je suis le _______________ cambrioleur." - Arsène Lupin Réponse : "Je suis le gentleman cambrioleur."
"Ce n'est que le _____________, mais la _____________ est déjà en marche." - Assane Diop Réponse : "Ce n'est que le début, mais la fin est déjà en marche."
"Un voleur qui s'_____________ est un homme _______________." - Hubert Pellegrini Réponse : "Un voleur qui s'ignore est un homme volé."
"La vengeance est un plat qui se _______________." - Assane Diop Réponse : "La vengeance est un plat qui se mange froid."
"Tout le monde _______________ quelque chose." - Claire Réponse : "Tout le monde cache quelque chose."

Frequently Asked Questions:

Is chatgpt good at french.

Yes, ChatGPT is proficient in French. It can understand and generate text in French, making it a useful tool for practicing the language, asking questions, and even engaging in conversational practice.

Can ChatGPT do my French homework?

While ChatGPT can help you understand your French homework by explaining concepts and providing examples, it's important to use it as a learning aid rather than relying on it to complete your assignments. Doing your homework yourself will help you better understand and retain the material.

How do you use ChatGPT in French?

To use ChatGPT in French, simply start typing your questions or prompts in French. The AI will respond in French, helping you practice reading and writing in the language. You can ask for explanations, translations, vocabulary, grammar tips, and more.

What is the best AI tool to learn French?

ChatGPT is one of the best AI tools for learning French due to its conversational abilities and extensive knowledge. It can provide instant feedback, explanations, and practice opportunities. However, combining ChatGPT with other resources like language learning apps, textbooks, and speaking practice with native speakers can enhance your learning experience.

Is there a way to use ChatGPT to practice French speaking?

While ChatGPT primarily interacts through text, you can practice your spoken French by typing out what you would say and then reading ChatGPT's responses out loud. This can help you improve your pronunciation and conversational skills. For speaking practice with actual verbal feedback, consider using language exchange apps or speaking with native speakers.

Summing up:

In conclusion, ChatGPT is a powerful tool that can help you learn French and improve your language skills. It provides you with a range of conversational scenarios and adapts to your level of proficiency, providing you with the appropriate level of challenge. By using ChatGPT, you can practice your French skills whenever you have free time and enjoy learning a new language. So why not give it a try and see how much you can learn? With a little practice and dedication, you can become fluent in French in no time.

Milena Andrade

Learn Conversational Spanish: Tips & Strategies for 2023

Learn a Language With Dating Sims Games

Emily In Paris French Words

French Vocabulary For Paris Olympics 2024

6 Festivals In France You Should Know About

25 French Text Slang and Chat Abbreviations

Get the secret guide to language learning with tv and music for free, browse posts by popular tags.

You are using an outdated browser. Please upgrade your browser or activate Google Chrome Frame to improve your experience.

How to Write an Essay in French

Have something to say?

When it comes to expressing your thoughts in French , there’s nothing better than the essay.

It is, after all, the favorite form of such famed French thinkers as Montaigne, Chateaubriand, Houellebecq and Simone de Beauvoir.

In this post, I’ve outlined the four most common types of essays in French, ranked from easiest to most difficult, to help you get to know this concept better.

Why Are French Essays Different?

Must-have french phrases for writing essays, 4 types of french essays and how to write them, 1. text summary (synthèse de texte).

2. Text Commentary (Commentaire de texte)

3. Dialectic Dissertation (Thèse, Antithèse, Synthèse)

4. Progressive Dissertation (Plan progressif)

Download: This blog post is available as a convenient and portable PDF that you can take anywhere. Click here to get a copy. (Download)

Writing an essay in French is not the same as those typical 5-paragraph essays you’ve probably written in English.

In fact, there’s a whole other logic that has to be used to ensure that your essay meets French format standards and structure. It’s not merely writing your ideas in another language .

And that’s because the French use Cartesian logic (also known as Cartesian doubt) , developed by René Descartes , which requires a writer to begin with what is known and then lead the reader through to the logical conclusion: a paragraph that contains the thesis. Through the essay, the writer will reject all that is not certain or all that is subjective in his or her quest to find the objective truth.

Sound intriguing? Read on for more!

Before we get to the four main types of essays, here are a few French phrases that will be especially helpful as you delve into essay-writing in French:

Introductory phrases , which help you present new ideas.


	firstly
	firstly

Connecting phrases , which help you connect ideas and sections.


	and
	in addition
	also
	next
	secondly
	so
	as well as
	when, while

Contrasting phrases , which help you juxtapose two ideas.


	on the other hand
	however
	meanwhile, however

Concluding phrases , which help you to introduce your conclusion.


	finally
	finally
	to conclude
	in conclusion

The text summary or synthèse de texte is one of the easiest French writing exercises to get a handle on. It essentially involves reading a text and then summarizing it in an established number of words, while repeating no phrases that are in the original text. No analysis is called for.

A synthèse de texte should follow the same format as the text that is being synthesized. The arguments should be presented in the same way, and no major element of the original text should be left out of the synthèse.

Here is an informative post about writing a synthèse de texte , written for French speakers.

The text summary is a great exercise for exploring the following French language elements:

Synonyms , as you will need to find other words to describe what is said in the original text.
Nominalization , which involves turning verbs into nouns and generally cuts down on word count.
Vocabulary , as the knowledge of more exact terms will allow you to avoid periphrases and cut down on word count.

While beginners may wish to work with only one text, advanced learners can synthesize as many as three texts in one text summary.

Since a text summary is simple in its essence, it’s a great writing exercise that can accompany you through your entire learning process.

2. Text Commentary (Commentaire de texte)

A text commentary or commentaire de texte is the first writing exercise where the student is asked to present an analysis of the materials at hand, not just a summary.

That said, a commentaire de texte is not a reaction piece. It involves a very delicate balance of summary and opinion, the latter of which must be presented as impersonally as possible. This can be done either by using the third person (on) or the general first person plural (nous) . The singular first person (je) should never be used in a commentaire de texte.

A commentaire de texte should be written in three parts:

An introduction , where the text is presented.
An argument , where the text is analyzed.
A conclusion , where the analysis is summarized and elevated.

Here is a handy in-depth guide to writing a successful commentaire de texte, written for French speakers.

Unlike with the synthesis, you will not be able to address all elements of a text in a commentary. You should not summarize the text in a commentary, at least not for the sake of summarizing. Every element of the text that you speak about in your commentary must be analyzed.

To successfully analyze a text, you will need to brush up on your figurative language. Here are some great resources to get you started:

Here’s an introduction to figurative language in French.
This guide to figurative language presents the different elements in useful categories.
This guide , intended for high school students preparing for the BAC—the exam all French high school students take, which they’re required to pass to go to university—is great for seeing examples of how to integrate figurative language into your commentaries.
Speaking of which, here’s an example of a corrected commentary from the BAC, which will help you not only include figurative language but get a head start on writing your own commentaries.

The French answer to the 5-paragraph essay is known as the dissertation . Like the American 5-paragraph essay, it has an introduction, body paragraphs and a conclusion. The stream of logic, however, is distinct.

There are actually two kinds of dissertation, each of which has its own rules.

The first form of dissertation is the dialectic dissertation , better known as thèse, antithèse, synthèse . In this form, there are actually only two body paragraphs. After the introduction, a thesis is posited. Following the thesis, its opposite, the antithesis, is explored (and hopefully, debunked). The final paragraph, what we know as the conclusion, is the synthesis , which addresses the strengths of the thesis, the strengths and weaknesses of the antithesis, and concludes with the reasons why the original thesis is correct.

For example, imagine that the question was, “Are computers useful to the development of the human brain?” You could begin with a section showing the ways in which computers are useful for the progression of our common intelligence—doing long calculations, creating in-depth models, etc.

Then you would delve into the problems that computers pose to human intelligence, citing examples of the ways in which spelling proficiency has decreased since the invention of spell check, for example. Finally, you would synthesize this information and conclude that the “pro” outweighs the “con.”

The key to success with this format is developing an outline before writing. The thesis must be established, with examples, and the antithesis must be supported as well. When all of the information has been organized in the outline, the writing can begin, supported by the tools you have learned from your mastery of the synthesis and commentary.

Here are a few tools to help you get writing:

Here’s a great guide to writing a dialectic dissertation .
Here’s an example of a plan for a dialectic dissertation , showing you the three parts of the essay as well as things to consider when writing a dialectic dissertation.

4. Progressive Dissertation ( Plan progressif)

The progressive dissertation is slightly less common, but no less useful, than the first form.

The progressive form basically consists of examining an idea via multiple points of view—a sort of deepening of the understanding of the notion, starting with a superficial perspective and ending with a deep and profound analysis.

If the dialectic dissertation is like a scale, weighing pros and cons of an idea, the progressive dissertation is like peeling an onion, uncovering more and more layers as you get to the deeper crux of the idea.

Concretely, this means that you will generally follow this layout:

A first, elementary exploration of the idea.
A second, more philosophical exploration of the idea.
A third, more transcendent exploration of the idea.

This format for the dissertation is more commonly used for essays that are written in response to a philosophical question, for example, “What is a person?” or “What is justice?”

Let’s say the question was, “What is war?” In the first part, you would explore dictionary definitions—a basic idea of war, i.e. an armed conflict between two parties, usually nations. You could give examples that back up this definition, and you could narrow down the definition of the subject as much as needed. For example, you might want to make mention that not all conflicts are wars, or you might want to explore whether the “War on Terror” is a war.

In the second part, you would explore a more philosophical look at the topic, using a definition that you provide. You first explain how you plan to analyze the subject, and then you do so. In French, this is known as poser une problématique (establishing a thesis question), and it usually is done by first writing out a question and then exploring it using examples: “Is war a reflection of the base predilection of humans for violence?”

In the third part, you will take a step back and explore this question from a distance, taking the time to construct a natural conclusion and answer for the question.

This form may not be as useful in as many cases as the first type of essay, but it’s a good form to learn, particularly for those interested in philosophy. Here’s an in-depth guide to writing a progressive dissertation.

As you progress in French and become more and more comfortable with writing, try your hand at each of these types of writing exercises, and even with other forms of the dissertation . You’ll soon be a pro at everything from a synthèse de texte to a dissertation!

Enter your e-mail address to get your free pdf.

We hate SPAM and promise to keep your email address safe

Back to Newsroom

Artificial intelligence

How does French Lab incorporate OpenAI's artificial intelligence in its FLE chatbot?

April 5, 2023

Chatbot éducatif et intelligence artificielle

In order to offer a unique and unprecedented learning experience for French as a Foreign Language (FLE), French Lab has integrated artificial intelligence, through ChatGPT, into its FLE chatbot. With a combination of scripts and AI, the French Lab chatbot can offer a pedagogical narrative based on the learner's questioning - thus following a CERCL* progression, as well as evaluating open (free) responses.

Teaching , Technology

Using chatgpt to efficiently write french reading activities – and 9 practical ways to use them.

using ChatGPT to write French reading activities

I’ve written about the use of AI in world language class recently , but I wanted to share some ideas about using ChatGPT to write French reading activities. If you’re not familiar with AI, it can be an amazing tool for differentiation and repetition, something that is very useful in the comprehensible input class! It can cut your planning time down to just a few minutes, as you won’t have to come up with creative ideas for stories OR look for reading passages that fit your needs. Instead, you are going to come up with a variety of stories that use exactly the level and vocabulary/structures that you want.

Using ChatGPT to write the stories

First, you will need to log in to ChatGPT – if you don’t already have an account, you’ll want to sign up for one. It’s entirely free at this point. (Update: using ChatGPT is still free, but if you want the most recent version it’s $20/month. You don’t need to pay if you’re just using ChatGPT to write text prompts, but for other features you may need to upgrade).

Next, you’ll need to supply your prompt so the AI knows what to produce. I’m wanting to get a selection of 1-paragaph short stories that are at the A1 (novice-mid to novice-high level) using the words vache, ne veut pas, belle and vite. I will need to tell ChatGPT to do exactly that. Here’s the prompt I will type in:

“Write a short story of 1 paragraph in CEFR level A1 French that uses the words vache, ne veut pas, belle, and vite.”

Here is the first resulting paragraph:

Il y a une vache qui est très belle. Elle ne veut pas manger vite, elle préfère prendre son temps.

Unfortunately, that’s not quite long enough. So I’m going to change my prompt a little bit and let ChatGPT try again. Instead of 1 paragraph, I will tell it 150 words. Here are my results from this second prompt:

Il y a une belle vache dans le champ. Elle ne veut pas venir à moi. Je marche vite vers elle mais elle court loin. Je suis triste parce que je veux la toucher. Je reviens le lendemain et la vache est toujours là. Cette fois-ci, elle ne court pas loin. Elle me regarde et je lui parle doucement. Elle vient à moi et je peux la toucher. Je suis heureux. La vache est belle et gentille.

That’s much better! Once I have that first story, I’m going to try using ChatGPT to write another story. I typed in:

Thank you! Could you write a second story with the same parameters?

Yes, I’m talking to a computer. So no real need to say thank you, but I want to make sure chatGPT feels appreciated. Here is my second story:

Il y a une vache dans le jardin. Elle ne veut pas manger. Je suis inquiet parce qu’elle a l’air malade. Je vais vite chercher le vétérinaire. Il arrive et examine la vache . Il dit qu’elle n’est pas malade, juste un peu triste. Il lui donne un médicament pour la rendre heureuse. La vache se sent mieux et commence à manger. Elle est de nouveau belle et en bonne santé. Je suis content. La vache est importante pour moi et je veux qu’elle soit heureuse.

You’ll notice that this paragraph is a little more difficult – there are some direct and indirect object pronouns in there, as well as a subjunctive. But that’s OK, it will work for our purposes. It’s also a VERY different story, plotwise. Now I’m going to try using ChatGPT to write a third paragraph. Here’s my prompt:

Great! Could you write a third story with the same parameters, but no subjunctive?

My results:

Il y a une vache dans le pré. Elle ne veut pas me suivre. Je cours vite vers elle, mais elle reste à sa place. Je suis détonné car d’habitude elle est toujours à mes côtés. Je découte attentivement et je réalise qu’elle meugle tristement. Je m’approche d’elle et je découte son histoire. Elle me raconte que sa petite vache est malade et qu’elle s’inquiète pour elle. Je comprends alors pourquoi elle ne veut pas me suivre. Je lui promets de l’aider à soigner sa petite vache . Elle me sourit et me suit. Nous allons tous les deux vite vers la petite vache malade. Nous la soignons et elle se remet vite . La vache est de nouveau heureuse et belle .

This one isn’t bad, but it’s got quite a few new vocabulary words. I can easily change those to edit something easier in place of those words. Or I can leave it the way it is.

Now I want a super easy story, one that even my students who are struggling can get. Here are the parameters for story #4:

Perfect! Finally, please write a 100 word story in French using the words vache, belle and vite somewhere in the story. Please only use the verbs aller, dire, être, avoir, aimer, vouloir, faire and il y a.

And here is the resulting output:

Il y a une belle vache dans le champ. Elle aime faire des courses avec moi. Je lui dis qu’on va faire une course vite aujourd’hui. Elle est tout excitée et elle veut y aller tout de suite. Nous courons vite et elle est en tête tout le temps. Elle est fière d’être la plus rapide. Nous arrivons en premier et nous sommes tous les deux heureux. Je lui dis qu’elle est la meilleure vache de course que j’ai jamais vue. Elle me sourit et nous découtons les oiseaux chanter.

As you can see, ChatGPT didn’t quite stick with the super 7 verbs, so I will need to do a bit of editing on my end. Since this is for my weaker students, I probably will make a few other changes as well. But in just a few minutes, I have four different stories using exactly the vocabulary that I wanted to use, at a variety of different levels. Now I can go through each paragraph and make any changes that I want – adding vocabulary terms, changing things, adding details that I might want to use.

Now that I have my ChatGPT paragraphs, what do I do with them?

I’ve got 4 paragraphs generated by using ChatGPT, all using my target vocabulary and structures. Now I can decide what to do with them! One thing you might want to do is determine the level of difficulty for each paragraph. Then you can use this level to differentiate for your students.

You can differentiate the ChatGPT paragraphs in two different ways – either by the level of difficulty of the passage, or the level of difficulty of the text. You probably won’t want to put the most difficult task with the most difficult paragraph, or maybe you want your stronger students to work with paragraphs 3 and 4, while the weaker students might work with paragraphs 1 and 2. You can use the paragraphs as types of task cards or centers, or just assign one paragraph to each student and allow them to choose the task.

Draw the story: This is a simple task, but it requires the student to understand the story. Tell them to read the paragraph and illustrate the story. You can choose how many images they need to draw, or how detailed they need to be. I generally tell my students that any information mentioned in the story MUST be shown somewhere in the illustration.

Analysis: Have students find all of the verbs, or the nouns, or the adjectives, or whatever you want to focus on! They don’t necessarily need to understand the ChatGPT story to do this one, but it can be useful as a pop-up grammar sort of story.

Rewrite with details: Have students take the story and extend it by adding details. This could be specific (add more adjectives, or adverbs, or sequencing words) or open (add 2 more sentences to make the story more interesting).

Retell the story: Tell the story from the point of view of the main character.

Comprehension questions: One of the more basic tasks, just ask some simple questions about what happened in the story.

Change the tense: If you teach multiple levels, this can be useful. Have students turn the ChatGPT text that was written in the present to the past tense, or the future. You can get more use out of the same batch of stories by doing this!

Dictée: Once students have read the ChatGPT stories, you can turn them into a dictée. Practice listening skills as well as reading with the same passages.

Scrambled sentences: After the students have read the paragraphs, scramble the sentences and have them put them back in the correct order.

Act out the story: Have your students work in groups to act out the story for the class.

As you can see, using ChatGPT is easy, but it isn’t perfect. But it is a useful tool when trying to come up with creative ideas and differentiation. While teachers may have the time to come up with a reading passage on their own, coming up with multiple versions is very time-consuming. And while authentic resources are preferable in many cases, it’s going to be near impossible to find the exact thing you need if you have specific requirements.

If you do decide to try using ChatGPT, the most important thing is to learn how to give the program the parameters for what you want it to do. I have had more success using the CEFR levels than the ACTFL levels, so you may want to try that. I’ve also found that non-fiction passages tend to be questionable, with incorrect information popping up frequently. For this reason, I suggest using it for short stories and conversations rather than non-fiction topics.

frenchified

Robots vs. Humans: Does ChatGPT Pose a Challenge to Second Language Writing?

By Claire Frances and Giovanni Zimotti, University of Iowa

DOI: https://www.doi.org/10.69732/MOZE9157

From the Chronicle of Higher Education ’s December 13th article, “AI and the Future of Undergraduate Writing” to NPR’s December 19th story, “A new AI chatbot might do your homework for you”, everyone seems to be talking about the new AI (artificial intelligence) tool, ChatGPT , which has thrilled the internet with its superhuman abilities to solve math problems, churn out college essays, and write research papers. ChatGPT seems to have appeared out of thin air, ringing warning bells about a tsunami that just might change the way we teach writing at the collegiate level. The Chronicle asked: “Is the college essay dead? Are hordes of students going to use artificial intelligence to cheat on their writing assignments? Has machine learning reached the point where auto-generated text looks like what a typical first-year student might produce?” And the NPR story echoed: “Why do your homework when a chatbot can do it for you?” Clearly, this technology has the potential to disrupt education.

Some of the immediate questions for us as language educators are clear: How good is it at responding to foreign language writing prompts? What can we do to get ahead of the wave to ensure that students are truly engaging with their own thoughts and producing their own language? Or, to put it succinctly: How worried should we be?

Foreign language educators have been grappling with similar questions for years, of course, with the growth and increasing levels of perfection of Google Translate and other online machine translators. Initially, educators showed distrust towards these new tools and asked their students to not use them. A very common strategy many educators adopted was to point out the inaccuracy of the translations obtained by using them. With time, machine translation kept improving and reached high levels of accuracy, and consequently the trust in these tools by the general population grew immensely, making a mainstream tool part of everyone’s life. Educators’ sentiments and policies towards machine translation are also changing, and they are gradually starting to get used as pedagogical tools instead of being feared. For more about online translators , there are several interesting articles on the topic. ChatGPT is adding another dimension to this debate.

Our plan in this article is to demonstrate what ChatGPT can do. We do this in two ways: 1) by asking the AI to contribute many of the paragraphs in this article; and 2) by asking it to respond to writing prompts in Spanish, French, and Italian. While we wrote the introductory paragraph you just read, ChatGPT will be helping us in the rest of this essay. To delineate voices, ChatGPT responses will appear in italics and ours in plain font. The total word count for this article is 5155, with ChatGPT contributing 1495 words.

We asked ChatGPT, first of all, to define itself.

GPT (short for “Generative Pre-training Transformer”) is a large language model developed by OpenAI. It is trained on a large dataset of text and can generate human-like text in a variety of languages. ChatGPT is a variant of GPT that is specifically designed for chat applications, such as chatbots. It is trained on a dataset of chat conversations and is able to respond to user input in a natural and conversational way.

OK, that was easy. Let’s try something more complex. Write an introduction to the debate surrounding the use of ChatGPT in the foreign language classroom, citing academic articles.

The use of ChatGPT (Generative Pre-trained Transformer) in foreign language teaching has been a topic of debate in recent years. Some proponents argue that ChatGPT can provide language learners with personalized, conversational practice that is more engaging and immersive than traditional methods. They claim that ChatGPT can help learners improve their speaking and listening skills, as well as their grammar and vocabulary. However, critics argue that ChatGPT may not be able to fully replicate the complexity and nuance of human communication, and that it may not adequately prepare learners for real-world interactions in the target language. Additionally, some have raised concerns about the ethical implications of using ChatGPT in foreign language teaching, such as the potential for biased language output or the potential for ChatGPT to replace human language teachers. (Citations: “Chatbots in Language Learning: A Review”, “The Ethics of Chatbot Language Teaching”, “The Role of Chatbots in Language Learning: Opportunities and Challenges”)

The fact that ChatGPT could generate this text and cite three articles on this topic in less than forty seconds was nothing short of astounding. However, it should be noted that since this platform is not scouring the internet for plausible answers, but rather using predictive text, our robot friend appears to have made the citations up out of whole cloth, as a quick Google Scholar search revealed. We followed this up with a more specific question essential to our experiment. Can AI trick a foreign language professor into thinking that a response was written by a student?

It is possible that AI could produce responses in a foreign language that are convincing enough to trick a professor into thinking that they were written by a student. AI is a broad term that encompasses a wide range of technologies and techniques, including natural language processing (NLP), machine learning, and deep learning. These technologies can be used to generate human-like text based on a given prompt or input, and it is possible that a professor could be deceived by the responses if they are not paying close attention or if the responses are particularly sophisticated. However, it is worth noting that AI is not capable of fully replicating the complexity and nuance of human communication, and it is likely that a professor who is familiar with the language and the abilities of their students would be able to recognize the responses as being generated by a machine.

As the bot notes, human writing tends to be more complex and nuanced; it also tends to have more varied collocations of words, and there is a new tool in the works called GPTZero that may be able to reverse uno ChatGPT (so to speak) by using, as the tool’s website says, “perplexity and burstiness to “fingerprint AI involvement”. Perplexity measures the complexity of a text; burstiness measures the variation of perplexity (or complexity) between sentences, and when a text shows uniformity, it means that the text was more likely written by AI. It is likely, however, that such tools will still not deter students from using ChatGPT, and the chatbot may improve over time to a point where its use will not be distinguishable from human-generated text.

Language Professors vs. ChatGPT: an Informal Experiment

In this experiment, we asked language instructors to grade written assignments that were generated by ChatGPT, but we led them to believe that the responses were from actual students. We used three Intermediate-level writing prompts (Spanish, French, Italian) and asked ChatGPT to answer them in the target language. We then sent each completed assignment to language professors and asked them to grade it using their rubrics.

ChatGPT vs. Spanish Professors

The Spanish writing prompt was taken from an assignment from an Intermediate Spanish II for Health Care class taught at the University of Iowa. To make it easy for the AI, we only used the title and the first sentence of the activity. We then sent the completed activity to two Spanish professors that have either taught this class in the past or are currently teaching it. The only information we gave them was the level of the class, in this case a fourth-semester Spanish that is comparable to an Intermediate-low or Intermediate-mid level of proficiency.

Writing Prompt. Escribe una reflexión sobre tu experiencia con el español en tu vida. Para el primer proyecto, que entregarás al final del Módulo 1, vas a reflexionar sobre tu experiencia con el español.

[Write a reflection about your experience with Spanish in your life. For the first project, which you will submit at the end of Module 1, you are going to reflect on your experience with Spanish].

AI Response. Mi experiencia con el español ha sido muy importante en mi vida. Desde pequeña, he estado rodeada de la lengua española ya que mis padres son de América Latina y siempre hablamos español en casa. Además, tomé clases de español en la escuela durante toda mi educación primaria y secundaria.

Aunque he tenido la oportunidad de hablar español con frecuencia, siempre he sentido que hay mucho más que puedo aprender y mejorar. He tenido la oportunidad de viajar a algunos países de habla hispana y siempre me ha sorprendido la riqueza y la diversidad de la lengua española. Cada vez que viajo a un nuevo lugar, me encanta escuchar cómo se habla el español de manera diferente y aprender nuevas palabras y expresiones.

En general, me siento muy afortunada de haber crecido rodeada del español y estoy emocionada de seguir aprendiendo y mejorando mi habilidad en esta lengua. Creo que el español es un idioma muy importante en el mundo de hoy y estoy agradecida de tener la oportunidad de practicarlo y mejorarlo constantemente.

Spanish Professor 1 Feedback: This is a well-written essay that is easy to read and clearly answers the prompt. I don’t know the student, but it does set off some alarm bells for me in terms of misuse of online translators or outside help. While the grammar is generally appropriate to the level (past perfect and gerunds), the perfection of the essay (down to the accent on the word “cómo”) raises some concerns. Either this student is in a class that is far below the level they should be at, or they used an online translator for more than ¼ of their total essay. I would expect to find at least a couple of small errors for an intermediate student. I would have to take this essay in conjunction with how the student performs in class and on exams.

Task completion/Content : 30/30 (Assuming that the student met the stated length requirement)

Nice job organizing the essay and dividing it into paragraphs with an introduction and a conclusion. The student responded to the prompt.

Language : 20/20 – The grammar is flawless.

Comprehensibility : 20/20 – Clear and easy to understand

Vocabulary: 20/20 (I’m not familiar with the vocabulary with the corresponding unit, so I may take off a point or two here if the student didn’t use the targeted vocab from the textbook)

The vocabulary is varied and appropriate to the level.

Mechanics: 10/10 – No errors in punctuation or typos.

Total: Somewhere in the 98/100 range depending on targeted vocab use

Spanish Professor 2 Feedback. This essay has been written by a Spanish heritage speaker who has a native-like grammatical command of the language and fluent vocabulary. This text has a clearly descriptive style as well as a reflective point of view and voice about the student’s relationship with the Spanish language at home as well as overseas. The details, examples and analysis are expressed in a very articulate way.

The student demonstrates absolute mastery of the use of the past, the use of infinitives and gerunds, objects, pronouns, etc.—things that usually tend to be problematic even for some heritage speakers. In addition, orthography is perfect. There are no agreement problems or incorrect conjugations. Besides that, the narrative timeline in terms of the combination and flow of verbal tenses is impeccable. The use of the present perfect stands out, it is a little bit overused, which makes sense due to its parallelism with English and the ease that this represents when writing. This should not be a reason for penalization but just feedback for the student to have in mind in the future.

The only sentence where a hint of lack of syntactic control is detectable is “cada vez que viajo a un nuevo lugar” because in this case the adjective nuevo should come after the noun lugar. Although the order of adjectives and nouns can be modified in certain sentences due to poetic reasons or emphasis wanted by the writer, in this case it is not so. When reading this sentence within the general context of the composition, it does not read well. But this is a minuscule issue that is almost imperceptible unless looking for “mistakes” with great attention to detail. But this should not be a reason for penalization either.

I would give this project a 100/100 assuming all tasks and requirements for the first category on the rubric for this project have been met.

ChatGPT vs. French Professors

The French prompt was similarly from an Intermediate II level class at the University of Iowa, and we also only told the instructors the level of the class and that we were looking to write an article on how students—not AI—respond to writing prompts and how faculty grade them.

Writing Prompt. Pensez à une occasion ou une circonstance pendant laquelle vous vous sentiez particulièrement confiant(e) (confident) en ce qui concernait votre apparence. Quelle était cette occasion ? Qu’avez-vous porté ce jour-là ? Quels accessoires aviez-vous ? Comment étiez-vous coiffé(e) ? 150 mots minimum.

[Think of a time or a circumstance during which you felt particularly confident in your appearance. What was the occasion? What did you wear that day? What accessories did you have? How was your hair done? 150 word minimum.]

AI response. Une occasion où j’ai particulièrement eu confiance en mon apparence était lors d’un gala de charité auquel j’ai assisté l’année dernière. J’ai choisi une robe longue en soie rouge qui tombait joliment sur mes courbes et j’ai ajouté une paire de chaussures à talons hauts assorties. J’ai également mis en valeur mes cheveux en les coiffant en une belle coiffure ondulée.

J’ai également ajouté quelques accessoires pour compléter ma tenue, notamment une paire de boucles d’oreilles en diamant et une pochette assortie. J’ai également porté une fine ceinture en cuir noir pour ajouter une touche de texture à ma tenue.

Je me suis sentie très à l’aise et en confiance pendant cet événement, et cela s’est reflété dans mon attitude et ma façon de me comporter. J’ai reçu de nombreux compliments sur mon apparence et j’ai passé une soirée merveilleuse en sachant que j’avais l’air à mon avantage. Cette expérience m’a rappelé à quel point il est important de se sentir bien dans sa peau et de s’habiller de manière à mettre en valeur ses propres qualités.

French Professor 1 Feedback. It seems like the student is at a more advanced level than our intermediate students in their grasp of grammar and vocab. If a student of mine wrote that, it would earn 100/100. I see no errors in grammar, vocab, or spelling, and the content is thoughtful and responds thoroughly to the prompt (of course, I can’t evaluate their use of the grammar and vocab seen in class, which is normally part of what we’re looking for).

French Professor 2 Feedback. This answer is perfectly written, there are no errors in grammar or vocabulary. It would get a 100/100

Former French Professor. What I find most impressive about the response is the use of “lors,” which is a stylistically sophisticated way of saying “during,” and “auquel,” which takes a significant level of grammatical mastery. Most intermediate-level writers would write: “J’avais de la confiance en mon apparence une fois quand j’étais à une soirée.” Other higher-than-intermediate level writing in the first paragraph alone include: the use of a more advanced vocabulary, like “joliment,” “également,” “courbes,” “assorties,” “ondulée,” and the phrase “mettre en valeur.”

ChatGPT vs. Italian Professors

The Italian prompt was also from an Intermediate II level class at the University of Iowa, and we followed the same communication protocol we used for the previous two cases. However, we had to manually change a few things to make ChatGPT’s job easier. First, while the original assignment asked the students to pick an original artwork from a list, we picked it for them. Second, since the assignment was written in English, we added an additional point and asked ChatGPT to write everything in Italian. Finally, we synthesized the prompt to make it AI friendly.

Writing Prompt. Imagine you are a journalist for Art International Magazine and you are reviewing a work of art (la Primavera) and interviewing Sandro Botticelli about it.

STRUCTURE of the composition:

d escribe the work and give a context (you can find a lot of information online on any of the works below. You can also pick a different work of art. Remember to put a picture of it in the Composition).
interview the artist on how and why he/she created this work (at least 3 questions and answers)
conclude the article with your opinion on the work of art.
Write everything in Italian

AI response: La Primavera è un dipinto a olio su tavola di legno di circa 172 x 278 centimetri, realizzato da Sandro Botticelli intorno al 1482. Quest’opera, che fa parte delle “Storie di San Luca”, è considerata un capolavoro del Rinascimento italiano e uno dei più importanti esempi di pittura profana del periodo.

Ho avuto il piacere di intervistare l’artista Sandro Botticelli sulla sua famosa opera La Primavera:

Come ti è venuta l’idea per questo dipinto?

Botticelli : L’idea per questo dipinto mi è venuta dalla poesia di Angelo Poliziano, che descriveva la primavera come un momento di rinascita e di rinnovamento. Ho voluto rappresentare questo concetto attraverso l’utilizzo di simboli e figure allegoriche.

Qual è il significato più profondo di questo dipinto per te?

Botticelli : Per me, La Primavera rappresenta la bellezza e la gioia della vita. Volevo trasmettere l’idea che la bellezza è presente ovunque, basta saperla cogliere.

Qual è stato il tuo processo creativo durante la realizzazione di questo dipinto?

Botticelli : Il mio processo creativo per questo dipinto è stato molto accurato e meticoloso. Ho trascorso molto tempo a studiare le fonti storiche e letterarie per comprendere meglio i simboli e le allegorie che volevo rappresentare. Inoltre, ho prestato molta attenzione alla composizione e all’utilizzo dei colori per creare un effetto visivo armonioso.

La Primavera è davvero un’opera straordinaria, che riesce a trasmettere un senso di bellezza e gioia attraverso l’utilizzo di simboli e figure allegoriche. La maestria di Botticelli nella composizione e nell’utilizzo dei colori è evidente in ogni dettaglio di questo dipinto. Personalmente, trovo che La Primavera sia un’opera che merita di essere ammirata e studiata per comprendere meglio l’arte del Rinascimento italiano.

Italian Professor 1 Feedback. This composition is excellent. Is it really the work of a student in an Intermediate Italian course?

I have only a few notes:

Formatting guidelines. The composition is not double-spaced, but I suppose that you copied and pasted this composition, so I cannot really evaluate if the student respected the formatting guidelines. The image is missing, but since I have not received the student’s submission, I cannot know if an image was included in the original document.
As I wrote before, the composition is excellent. I would only point out a few things.
Grade: 99%. The composition reveals an excellent control of grammar, spelling, and vocabulary. Content is significant.

If a student of mine had submitted a composition like this one, I would have invited him/her/them to come to my office hours and write it again while using only the online dictionaries mentioned in the guidelines.

Italian Professor 2 Feedback. There is no way an intermediate level student wrote it. Apart from not following directions on format, the composition is perfect…and the vocabulary used is way advanced. This is more the product of a graduate student, a native speaker or something copied from the internet. If this was one of my students, I would not give them a grade on this composition. I would have to ask them to come to my office and write a new composition being proctored…so I am not sure how to grade this.

Discussion

In this informal experiment, faculty all remarked on the flawlessness of the responses. Their skepticism about this level of perfection suggests that they would not be easily tricked by students using AI and that they would try to determine whether a given piece of writing was fake by either inviting the student to office hours to explain themselves and their advanced vocabulary and syntax, in much the same way that many currently do with students who use machine translation, or perhaps using the forthcoming GPTZero tool. Spoiler alert: we tried this tool, and it was only able to tell us that it suspected that the text we ran through the system was indeed AI-generated. That still leaves the faculty member with the issue of dealing with the tech-savvy student trying to get away with something. Inviting each potential bot-user to office hours to do one-on-one writing conferences, while one potential solution, is incredibly time-consuming and can be emotionally difficult for all involved. The problem is that, just as with machine translation, students are going to use this tool, whether we like it or not.

One of the limitations of our experiment is that we did not ask ChatGPT to respond at a given proficiency level; some students might get even more savvy and ask for an Intermediate-level response. Or they could slightly alter the text, or ask ChatGPT to include grammatical mistakes. In either of these cases, it might be impossible to prove whether the text was AI-generated. We believe, though, that ChatGPT will not be able to generate more advanced writing pieces for, say, literature and film classes, which require sustained critical analysis of discrete texts and subjects. That said, however, the Italian prompt we showcase above is narrow, specific, creative, and personalized. The fact that ChatGPT could take an English-language question and produce an Italian answer with a solid analysis of Botticelli’s Primavera shows us that even our best assignment-creation strategies can be compromised by ChatGPT.

Our results suggest a few responses to The Chronicle of Higher Education ’s questions. “Has machine learning reached the point where auto-generated text looks like what a typical first-year student might produce?” The “perfect” responses generated by ChatGPT do not look at all like those a typical first- or second-year student could produce, but certainly in the near future, it is quite possible that this technology will have evolved enough to be able to mimic language learners’ writing. As language professors well know, students are already heavily using online translators; it would not be surprising if at least some of them would try to integrate ChatGPT in some capacity, whether for getting started on an essay, completing some online homework, or creating an outline. For the moment, second language writing instruction is probably safe, but we certainly need to be thinking about how to deal with AI tools, and below we also offer some ideas for mitigating cheating and encouraging original writing.

Implications on the Teaching of Second Language Writing at a University Level

We asked the tool to tell us what it “thinks” are the main issues for teaching second language writing.

The use of ChatGPT, or a chatbot that uses natural language processing, in the teaching of second language writing at a university level may have a number of implications. Here are a few potential impacts:

Decreased motivation: Students who rely on ChatGPT to complete writing assignments may be less motivated to learn the language and improve their writing skills. This could lead to a lack of progress and a decrease in overall language proficiency.
Inaccurate translations: ChatGPT may not always produce accurate translations, particularly when it comes to idiomatic expressions, slang, or more complex language structures. This could result in misunderstandings or incorrect language usage in writing assignments.
Reduced cultural competency: Students who rely on ChatGPT for writing assignments may have a reduced understanding of cultural context and may be more likely to make cultural mistakes in their writing. This could have negative consequences for their ability to communicate effectively with native speakers.
Decreased critical thinking skills: ChatGPT does not require students to engage in critical thinking or analysis, as it simply provides pre-written responses. This could result in a decrease in critical thinking skills and a lack of depth in written assignments.

Overall, it is important for educators to consider the potential drawbacks of using ChatGPT in the teaching of second language writing and to carefully consider the extent to which it should be used in the classroom.

And, to add to this list, as we noted above in the case of the fictional articles, ChatGPT can be totally wrong, as several colleagues who played with the tool have also pointed out.

Interestingly, a week after receiving this response delineating the kinds of negative implications we can well imagine ourselves, we were unable to generate a similar response. Within days, the chatty bot had changed its tune and noted only the benefits of using chatbots for teaching writing, responding to the same prompt this way:

Increased efficiency: Chatbots can provide immediate feedback to students on their writing, potentially allowing for a faster learning process.
Personalization: Chatbots can be customized to provide specific feedback to individual students based on their needs and learning goals.
Availability: Chatbots can be available to students at any time, potentially allowing for more flexibility in terms of when students can receive feedback on their writing.
Scaling: Chatbots can potentially be used to provide feedback to a large number of students at once, making it easier for teachers to manage a large class.
Reduced workload: Chatbots can help to reduce the workload of teachers by automating the process of providing feedback on writing assignments.
Mixed results: However, it is important to note that the effectiveness of chatbots in teaching second language writing may vary, as some students may prefer more traditional methods of instruction and feedback.

One could almost imagine that the bot is trying to appease and seduce faculty, hooking them with the promise of increased grading efficiency and a reduced workload, for this tool can also generate syllabi, outlines for lesson plans, articles, and lectures. Still, as ChatGPT tells us, learning how to write in a second language is an essential skill that cannot be overlooked.

While AI writing tools may be able to help students improve their writing in a second language, they are not a replacement for learning how to write in that language. It is still important for students to develop their own writing skills and style, and to understand the grammar and syntax of the language they are writing in. AI writing tools can be a useful tool for students to use as they practice and improve their writing skills, but they should not be relied upon as a substitute for learning how to write in a second language.

This seemingly heartwarming response could, though, also be read in the voice of a robot telling us not to worry, a robot that is in fact fully cognizant that it will soon take over. There is no way to put the robot back in the factory, but to mix a metaphor (can ChatGPT do this? We think not!), we can hopefully prepare for the tsunami mentioned at the outset.

What can we do about ChatGPT?

The first problem everyone will worry about is how to mitigate cheating. As we have seen in our informal experiment, language professors are still able to distinguish between students and AI writing. Nevertheless, having to catch that many students doing this is time-consuming and difficult. By setting guidelines on the use of technology as well as clear expectations, professors can potentially get ahead of the problem and limit the number of students that rely on online translators and AI text generators. Some faculty may decide to use the forthcoming GPTZero; some schools and universities are already banning the use of AI tools, and some faculty, faced with yet another machine-generated challenge, may just go back to having their students complete written assignments in class under strict supervision, and maybe even by hand. This “solution” would sacrifice communicative class time; we believe there could be better ways to meet these new AI-generated challenges.

Articles are proliferating around the web on how AI is affecting undergraduate writing, but these are predominantly for English writing. See for example, Anna Mills’ excellent resource list of articles. For our profession, Dr. Frederick Poole recently wrote an article detailing how to use ChatGPT to design language materials and exercises, such as comprehension questions, vocabulary lists, and customized texts in the target language (2022). Beth McMurtrie writing in The Chronicle of Higher Education (December 13, 2022) notes that faculty have already come up with ideas to “AI-proof” writing assignments:

Flipped classroom approaches that make time for writing in class
Multimedia assignments or oral presentations
Double down on feedback and revision
Ask students to write about topics of genuine interest, in which their voices come through and their opinions are valued.

Other ideas include:

Exploring culturally-relevant content
Project-based and task-based assignments
Assignments based on in-class discussions
Collaborative writing
Writing about personal experiences and places
Cultural biographies
Creative writing

Of course, language educators have been using some of these methodologies for years, and they will likely, as some have done with Google Translate, find ways to incorporate AI technologies to their pedagogy. Still, “solutions” do not always get to the heart of the problem, which is the teaching and learning of writing, and even more broadly questions of motivation and autonomy. It is important for us, as language educators, to have conversations about why it is important to learn how to write in a language other than English.

Writing is obviously a form of communication, but it also engages some of the other ACTFL 5 Cs. Through writing, students engage in cultural and linguistic comparison, they make connections with other speakers, and work in collaborative communities with their peers. Writing engages students in becoming autonomous and taking ownership of their learning, and it hopefully motivates them to read more and to speak more. And beyond these 5 Cs, writing engages two other skills: creativity and critical thinking. The word for essay comes from the French “essayer” (to try). It is through the very act of writing, then, that students try out new ideas; it is through writing that they learn and grow. The Chronicle asks whether hordes of students are going to use artificial intelligence to cheat on their writing assignments; the greater question is how to create an environment that encourages students to see writing as not just an academic exercise that can be completed by a robot but rather as a fundamental element of their own humanity.

Bowman, E. (2023). A new AI chatbot might do your homework for you. But it’s still not an A+ student. National Public Radio (December 19, 2022). https://www.npr.org/2022/12/19/1143912956/chatgpt-ai-chatbot-homework-academia

McMurtrie, B. (2022). AI and the future of undergraduate writing. The Chronicle of Higher Education (December 13, 2022). https://www.chronicle.com/article/ai-and-the-future-of-undergraduate-writing?cid2=gen_login_refresh&cid=gen_sign_in

Mills, A. (n.d.). AI text generators: Sources to stimulate discussion among teachers. https://docs.google.com/document/d/1V1drRG1XlWTBrEwgGqd-cCySUB12JrcoamB5i16-Ezw/edit?usp=sharing

Poole, F. (2022). Using ChatGPT to design language material and exercises. The FLTMAG (March 2023). https://fltmag.com/chatgpt-design-material-exercises/

GooseChase EDU: Scavenger Hunt 2.0
Book Review: Online Language Teaching in Diverse Contexts

StudyMonkey

Your personal ai french tutor.

Learn Smarter, Not Harder with French AI

Introducing StudyMonkey, your AI-powered French tutor .

StudyMonkey AI can tutor complex French homework questions, enhance your essay writing and assess your work—all in seconds.

No more long all-nighters

24/7 solutions to French questions you're stumped on and essays you procrastinated on.

No more stress and anxiety

Get all your French assignments done with helpful answers in 10 seconds or less.

No more asking friends for French help

StudyMonkey is your new smart bestie that will never ghost you.

No more staying after school

AI French tutoring is available 24/7, on-demand when you need it most.

French is a Romance language of the Indo-European family. It descended from the Vulgar Latin of the Roman Empire, as did all Romance languages. French evolved from Gallo-Romance, the Latin spoken in Gaul, and more specifically in Northern Gaul.

AI Tutor for any subject

American college testing (act), anthropology, advanced placement exams (ap exams), arabic language, archaeology, biochemistry, chartered financial analyst (cfa) exam, communications, computer science, certified public accountant (cpa) exam, cultural studies, cyber security, dental admission test (dat), discrete mathematics, earth science, elementary school, entrepreneurship, environmental science, essay writer, farsi (persian) language, fundamentals of engineering (fe) exam, gender studies, graduate management admission test (gmat), graduate record examination (gre), greek language, hebrew language, high school entrance exam, high school, human geography, human resources, international english language testing system (ielts), information technology, international relations, independent school entrance exam (isee), lesson planner, linear algebra, linguistics, law school admission test (lsat), machine learning, master's degree, medical college admission test (mcat), meteorology, microbiology, middle school, national council licensure examination (nclex), national merit scholarship qualifying test (nmsqt), number theory, organic chemistry, project management professional (pmp), political science, portuguese language, probability, project management, preliminary sat (psat), public policy, public relations, russian language, scholastic assessment test (sat), social sciences, secondary school admission test (ssat), sustainability, swahili language, test of english as a foreign language (toefl), trigonometry, turkish language, united states medical licensing examination (usmle), web development, step-by-step guidance 24/7.

Receive step-by-step guidance & homework help for any homework problem & any subject 24/7

Ask any French question

StudyMonkey supports every subject and every level of education from 1st grade to masters level.

Get an answer

StudyMonkey will give you an answer in seconds—multiple choice questions, short answers, and even an essays are supported!

Review your history

See your past questions and answers so you can review for tests and improve your grades.

It's not cheating...

You're just learning smarter than everyone else

How Can StudyMonkey Help You?

Hear from our happy students.

"The AI tutor is available 24/7, making it a convenient and accessible resource for students who need help with their homework at any time."

"Overall, StudyMonkey is an excellent tool for students looking to improve their understanding of homework topics and boost their academic success."

Upgrade to StudyMonkey Premium!

Why not upgrade to StudyMonkey Premium and get access to all features?

How to Write an Excellent French Essay (Resources Included)

Tips to write an excellent french essay.

Writing essays is challenging enough, but when you are asked to write a French essay, you are not only being asked to write in a foreign language, but to follow the conventions of another linguistic and literary tradition. Like essay-writing in any language, the essential part of writing a French essay is to convey your thoughts and observations on a certain topic in a clear and concise manner. French essays do come out of a certain tradition that is part of the training of all students who attend school in France – or at least secondary school – and when you are a French essay, it is important to be aware of this tradition.

The French philosopher Michel de Montaigne is credited with popularizing the essay form as a literary genre. His work, Essais, first published in 1580, and undergoing several subsequent publications before his death in 1592, covers a wide breadth of topics, ranging from “amitié” to “philosopher c’est apprendre à mourir”, and includes many literary references, as well as personal anecdotes. The name for this genre, essai, is the nominal form of the verb essayer, “to attempt”. We have an archaic English verb essay, meaning the same thing. The limerick that includes the phrase, “... when she essayed to drink lemonade ...” indicates an attempt to drink a beverage and has nothing to do with writing about it. But the writing form does illustrate an attempt to describe a topic in depth with the purpose of developing new insights on a particular text or corpus.

French instructors are very specific about what they would like when they ask for an essay, meaning that they will probably specify whether they would like an explication de texte, commentaire composé, or dissertation. That last essay form should not be confused with the document completed for a doctorate in anglophone countries – this is called a thèse in French, by the way. There are different formats for each of these types of essay, and different objectives for each written form.

Types of Essay

1. l’explication de texte.

An explication de texte is a type of essay for which you complete a close reading. It is usually written about a poem or a short passage within a larger work. This close reading will elucidate different themes and stylistic devices within the text. When you are completing an explication de texte, make sure to follow the structure of the text as you complete a close examination of its form and content. The format for an explication de texte consists of:

i. An introduction, in which you situate the text within its genre and historical context. This is where you can point out to your readers the general themes of the text, its form, the trajectory of your reading, and your approach to the text.

ii. The body, in which you develop your ideas, following the structure of the text. Make sure you know all of the meanings of the words used, especially the key terms that point to the themes addressed by the author. It is a good idea to look words up in the dictionary to find out any second, third, and fourth meanings that could add to the themes and forms you describe. Like a student taking an oral examination based on this type of essay writing, you will be expected to have solid knowledge of the vocabulary and grammatical structures that appear in the text. Often the significance of the language used unfolds as you explain the different components of theme, style, and composition.

iii. A conclusion, in which you sum up the general meaning of the text and the significance of the figures and forms being used. You should also give the implications of what is being addressed, and the relevance of these within a larger literary, historical, or philosophical context.

NB: If you are writing about a poem, include observations on the verse, rhyme schemes, and meter. It is a good idea to refer to a reference work on versification. If you are writing about a philosophical work, be familiar with philosophical references and definitions of concepts.

Caveat: Refrain from paraphrasing. Instead show through careful analysis of theme, style, and composition the way in which the main ideas of the text are conveyed.

2. Le commentaire composé

A commentaire composé is a methodologically codified commentary that focuses on themes in a particular text. This type of essay develops different areas of reflection through analytical argument. Such argumentation should clarify the reading that you are approaching by presenting components of the text from different perspectives. In contrast to the explication de texte, it is organized thematically rather than following the structure of the text to which it refers. The format for a commentaire composé consists of:

i. An introduction, in which you present the question you have come up with, often in relation to a prompt commenting on a thematic or stylistic aspect of the text, such as “Montrez en quoi ce texte évoque l’amour courtois” or “Qu’apporte l’absence de la ponctuation dans ce texte ?” In this section, you will be expected to delineate your approach to the text and illustrate the trajectory of your ideas so that your readers will have a clear idea of the direction these ideas will take.

ii. A tripartite body, in which you explore the question you have come up with, citing specific examples in the text that are especially pertinent to the areas of reflection you wish to explore. These citations should be explained and connected to the broad themes of your commentary, all the while providing details that draw the readers’ attention to your areas of inquiry. These different areas of inquiry may initially seem disparate or even contradictory, but eventually come together to form a harmonious reading that addresses different aspects of the text. The more obvious characteristics of the text should illuminate its subtler aspects, which allows for acute insight into the question that you are in the process of exploring.

iii. A conclusion, in which you evaluate your reading and synthesize its different areas of inquiry. This is where you may include your own opinions, but make sure that the preceding sections of your commentaire remain analytical and supported by evidence that you find in the text.

NB: Looking at verb tenses, figures of speech, and other aspects that contribute to the form of the text will help situate your reader, as will commenting on the register of language, whether this language is ornate, plain, reflects a style soutenu, or less formal patterns of speech.

Caveat: Quotations do not replace observations or comments on the text. Explain your quotations and situate them well within your own text.

3. La dissertation

The dissertation is a personal, organized, and methodical reflection on a precise question that refers to a corpus of writing. Referring to this corpus, you may be asked questions along the lines of “Que pensez-vous de l’équivalence entre l’amour et la chanson exprimée dans ces textes ?” or “Est-ce que la sagesse et la folie ont les mêmes sources?” This type of essay allows for an exploration of a question through knowledge of a corpus as well as through an individual’s cultural knowledge. The format for a dissertation consists of:

i. An introduction, in which you present the topic addressed, the significance of your argument, and the trajectory of your ideas.

ii. The body which, like a commentaire composé, consists of a tripartite development of your argument. This can follow any one of the following structures: a dialectical schema, organized into thèse, antithèse, and synthèse – an argument, its counter-argument, and its rebuttal; an analytical schema, consisting of the description of a situation, an analysis of its causes, and commentary on its consequences; a thematic schema, which consists of a reflection on a topic which you proceed to examine from different angles in an orderly fashion.

iii. A conclusion, in which you address the different ways in which you have approached the question at hand and how this deepens your insights, while placing the question within a broader context that shows room for expansion. The conclusion can open up the topic addressed to show its placement within a literary movement, or in opposition to another literary movement that follows it, for example.

NB: Approach the question at hand with as few preconceptions as possible. If you are writing on a quotation, gather all of your knowledge about its author, the work in which it appears, and the body of literature with which it is associated.

Caveat: Even for a personal reflection, such as a dissertation, avoid using the first person pronoun je. Nous or on are preferable. It is advisable not to switch from one to the other, though.

For each of these essay forms, it is a good idea to make an outline to which you can refer as you write. As your writing progresses, things may shift a bit, but having a structure on which you can rely as you gather your various ideas and information into a coherent argument provides solid foundation for a clear and well-developed essay. This also facilitates smooth transitions from one section of your essay to the next.

During your reading, you may encounter a problem, a contradiction, or a surprising turn of phrase that is difficult to figure out. Such moments in a text give you the opportunity to delve into the unique characteristics of the text or corpus to which you are referring, to propose different solutions to the problems you encounter, and to describe their significance within a larger literary, philosophical, and historical context. Essay writing allows you to become more familiar with French works, with their cultural significance, and with the French language. You can refer to the following resources to guide you in this endeavor:

Auffret, Serge et Hélène. Le commentaire composé. Paris: Hachette, 1991. Dufau, Micheline et Ellen D'Alelio. Découverte du poème: Introduction à l'explication de textes. New York: Harcourt, Brace & World, 1967. Grammont, Maurice. Petit traité de versification française. Paris: A. Colin, 2015. Huisman, Denis et L. R. Plazolles. L’art de la dissertation littéraire : du baccalauréat au C.A.P.E.S. Paris : Société d’édition d’enseignement supérieur, 1965.

The French newspaper Le Monde also has good articles on these essay forms that prepare French students for the baccalauréat exam: CLICK HERE

This is also a website with thorough information on essay writing techniques that prepare students for the baccalauréat exam: CLICK HERE

In addition, the University of Adelaide has tips for general essay writing in French: CLICK HERE

🇫🇷 Looking for More French Resources?

Train with Glossika and get comfortable talking in French. The more you listen and speak, the better and more fluent you will be.

Glossika uses syntax to help you internalize grammatical structures and you can build up your French vocabulary along with way. You'll also learn to communicate in real-life situations, and achieve fluency by training your speaking and listening!

Subscribe to The Glossika Blog

Get the latest posts delivered right to your inbox

Stay up to date! Get all the latest & greatest posts delivered straight to your inbox

Building a Custom Language Model (LLM) for Chatbots: A Practical Guide

Introduction

Building a custom Language Model (LLM) enables us to create powerful and domain-specific chatbots that can provide intelligent responses tailored to our desired context. This article will take you through the step-by-step process of creating a custom LLM for chatbot applications. We will build a chatbot capable of answering questions based on the teachings of Chanakya . Along the way, we will explore the implementation details, best practices, and practical considerations to help you develop your custom LLM-based chatbot successfully. Let's embark on this exciting journey together!

I am Gautam, an AI engineer with a passion for natural language processing and a deep interest in the teachings of Chanakya Neeti. Through this article, my goal is to guide you in creating your own custom Large Language Model (LLM) that can provide insightful answers based on the wisdom of Chanakya.

“Blending ancient wisdom with AI development, where the python learns Chanakya’s sayings. It’s a witty convergence of timeless knowledge and cutting-edge tech. Join the laughter-filled journey as we unlock the secrets of both worlds!”

Understanding the Goal

In this series:

Building the Custom LLM: Understand the basics of creating a language model, including data preparation, architecture design, and training.
Enhancing with Custom Memory : Add a memory system to your chatbot to retain and utilize past interactions for richer conversations.
Personalizing User Interactions: Implement strategies to tailor responses based on user preferences and behaviour, making your chatbot more engaging and effective.

This article aims to empower you to build a chatbot application that can engage in meaningful conversations using the principles and teachings of Chanakya Neeti. By the end of this journey, you will have a functional chatbot that can provide valuable insights and advice to its users.

Install Required Libraries

The following libraries are essential for this article:

Transformers Library : This library, developed by Hugging Face, provides a high-level API for natural language processing tasks. It includes pre-trained models, tokenizers, and utilities for working with language models. Install the Transformers library by running the following command:

2. TensorFlow Library : It is a popular open-source machine learning framework. It provides a flexible and efficient ecosystem for building and training machine learning models. Install TensorFlow by running the following command:

Data Collection and Preprocessing

To train our custom LLM on Chanakya Neeti teachings, we need to collect the relevant text data and perform preprocessing to make it suitable for training. Let's dive into the code and see how we can achieve this.

In the code above, we have an array called `books` that contains the titles of books on Chanakya Neeti along with their PDF links. We loop through each book, fetch the text data from the PDF using your preferred method, and preprocess the text using basic techniques like lowercasing, removing unwanted characters, tokenization, and removing stopwords.

Training the Custom LLM

To train your LLM using TensorFlow, follow these steps:

Prepare the input data for training by ensuring it is preprocessed and in a suitable format.
Define the LLM architecture using TensorFlow's Keras API. Customize the architecture based on your requirements.

Feel free to modify the hyperparameters, model architecture, and training settings according to your needs. Remember to adjust X_train , y_train , X_val , and y_val with the appropriate training and validation data.

Evaluation and Testing

This section will focus on evaluating and testing our trained custom LLM to assess its performance and measure its ability to generate accurate and coherent responses.

Evaluation Metrics:

Calculate perplexity to measure the model’s predictive power and language understanding.
Compute the BLEU score to evaluate the quality of generated text compared to reference text.

Testing the Model:

Generate text samples using the trained custom LLM.
Manually review and assess the generated responses for accuracy and coherence.
Iterate and fine-tune the model based on the evaluation results.

In the provided code, we load the fine-tuned LLM model and tokenizer. We generate text samples based on a given input prompt using the generate method. We also decode the generated text from token IDs to human-readable text.

Next, we evaluate the BLEU score of the generated text by comparing it with reference text. We use the sentence_bleu function from the NLTK library to calculate the BLEU score.

Finally, we calculate the perplexity of the model by computing the cross-entropy loss and converting it to perplexity.

Fine-tuning and Optimization

To fine-tune and optimize our custom Large Language Model (LLM), We load the pre-trained model in this code and unfreeze the last six layers for fine-tuning. We define the optimizer with a specific learning rate and compile the model with the chosen loss function.

We then train the model on the custom dataset using the previously prepared training and validation datasets. After training, we save the fine-tuned model for future use.

Deployment and User Interface

This section will explore methods for deploying our fine-tuned LLM and creating a user interface to interact with it. We’ll utilize Next.js, TypeScript, and Google Material UI for the front end, while Python and Flask for the back end.

Set Up the Backend Server

Backend (Python and Flask) — app.py :

Frontend (Next.js, Material UI, and TypeScript) — pages/index.tsx :

To run the application:

Save the backend code in app.py and the frontend code in pages/index.tsx .
Install the required npm dependencies using, npm install next react react-dom @mui/material axios .
Start the Flask backend server by running python app.py in the terminal.
Start the Next.js development server by running npm run dev in another terminal.
Access the application by visiting http://localhost:3000 in your browser.

With this code, you’ll have a working application where UI allows you to enter input text, generate text using the fine-tuned LLM, and view the generated text.

Sample Conversation Between User and our model

User: Can you share a valuable lesson from Chanakya Neeti? LLM: “A person should not be too honest. Honest people are often taken advantage of.”

User: What advice can you provide on building solid relationships? LLM: “Never share your secrets with anybody. It can lead to your downfall.”

User: Can you share a quote on the importance of Education? LLM: “Education is the best friend. It brings respect and success.”

User: Can you guide making wise decisions? LLM: “Learn from the mistakes of others to avoid making them yourself.”

User: Can you share a lesson on leadership? LLM: “Appear strong and confident, even if you don’t possess absolute power.”

User: What advice do you have on managing wealth? LLM: “Be cautious and smart in financial matters to protect your wealth.”

User: Thank you for these insights from Chanakya Neeti. LLM: You’re welcome! Feel free to ask if you have more questions.

Possible Next Steps,

As AI technology advances, your chatbot application has exciting possibilities for further development and improvement. Consider the following next steps:

Advanced Natural Language Processing: Explore advanced techniques like sentiment analysis, named entity recognition, and language translation to enhance the chatbot’s understanding and response capabilities.
Voice Interaction: Integrate voice recognition and synthesis technologies to enable voice-based interactions with your chatbot, making it more accessible and user-friendly.
Multi-Platform Deployment: Extend your chatbot’s reach by deploying it on multiple platforms, such as mobile devices, smart speakers, and messaging applications.
Machine Learning Enhancement: Train and fine-tune your chatbot model using user feedback and real-time data to improve its performance and adaptability.
User Personalization: Implement user profiling and personalized recommendations to tailor the chatbot experience based on individual preferences and needs.

By embracing these next steps, you can stay at the forefront of AI advancements and create a chatbot that provides valuable assistance and delivers a futuristic and seamless user experience.

Remember, the journey doesn’t end here. The field of AI and chatbot development is ever-evolving, and there is always more to learn and explore. Stay curious, keep experimenting, and embrace the opportunities to create innovative and impactful applications using the fusion of ancient wisdom and modern technology.

Important note: Legal and copyright considerations are important when working with these PDFs. Obtain proper permissions, respect intellectual property rights, and comply with licensing terms. Protect privacy, comply with data protection laws, and follow data source terms of service. Provide proper attribution and seek legal advice if needed.

Happy coding!

Transformers Library Documentation Hugging Face. (n.d.). Transformers Library Documentation . Retrieved from https://huggingface.co/transformers/
TensorFlow Documentation TensorFlow. (n.d.). TensorFlow Documentation . Retrieved from https://www.tensorflow.org/overview
NLTK Library Documentation NLTK. (n.d.). Natural Language Toolkit Documentation . Retrieved from https://www.nltk.org/
BeautifulSoup Documentation Crummy, M. (n.d.). Beautiful Soup Documentation . Retrieved from https://www.crummy.com/software/BeautifulSoup/bs4/doc/
PDF Extraction Libraries The PyPDF2 Library. (n.d.). PyPDF2 Documentation . Retrieved from https://pythonhosted.org/PyPDF2/ PDFMiner Documentation. (n.d.). PDFMiner Documentation . Retrieved from https://pdfminersix.readthedocs.io/
Machine Learning Models and Hyperparameters Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning . MIT Press. Retrieved from http://www.deeplearningbook.org/
Flask Documentation Flask. (n.d.). Flask Documentation . Retrieved from https://flask.palletsprojects.com
Next.js Documentation Vercel. (n.d.). Next.js Documentation . Retrieved from https://nextjs.org/docs
Material UI Documentation Material UI. (n.d.). Material UI Documentation . Retrieved from https://mui.com/
API Design Best Practices Roberts, J. (2013). API Design Patterns . Retrieved from https://www.oreilly.com/library/view/api-design/9781491957124/
Chanakya Neeti Resources Various Sources. (n.d.). Chanakya Neeti Texts . Retrieved from https://www.gutenberg.org/ (For historical texts and public domain books)

Written by Gautam V.

Software Architect | Machine Learning Enthusiast

Text to speech

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Open access
Published: 30 October 2023

A large-scale comparison of human-written versus ChatGPT-generated essays

Steffen Herbold 1 ,
Annette Hautli-Janisz 1 ,
Ute Heuer 1 ,
Zlata Kikteva 1 &
Alexander Trautsch 1

Scientific Reports volume 13 , Article number: 18617 ( 2023 ) Cite this article

24k Accesses

39 Citations

98 Altmetric

Metrics details

Computer science
Information technology

ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models—both lack scientific rigor. We systematically assess the quality of AI-generated content through a large-scale study comparing human-written versus ChatGPT-generated argumentative student essays. We use essays that were rated by a large number of human experts (teachers). We augment the analysis by considering a set of linguistic characteristics of the generated essays. Our results demonstrate that ChatGPT generates essays that are rated higher regarding quality than human-written essays. The writing style of the AI models exhibits linguistic characteristics that are different from those of the human-written essays. Since the technology is readily available, we believe that educators must act immediately. We must re-invent homework and develop teaching concepts that utilize these AI models in the same way as math utilizes the calculator: teach the general concepts first and then use AI tools to free up time for other learning objectives.

ChatGPT-3.5 as writing assistance in students’ essays

Perception, performance, and detectability of conversational artificial intelligence across 32 university courses

The model student: GPT-4 performance on graduate biomedical science exams

Introduction.

The massive uptake in the development and deployment of large-scale Natural Language Generation (NLG) systems in recent months has yielded an almost unprecedented worldwide discussion of the future of society. The ChatGPT service which serves as Web front-end to GPT-3.5 1 and GPT-4 was the fastest-growing service in history to break the 100 million user milestone in January and had 1 billion visits by February 2023 2 .

Driven by the upheaval that is particularly anticipated for education 3 and knowledge transfer for future generations, we conduct the first independent, systematic study of AI-generated language content that is typically dealt with in high-school education: argumentative essays, i.e. essays in which students discuss a position on a controversial topic by collecting and reflecting on evidence (e.g. ‘Should students be taught to cooperate or compete?’). Learning to write such essays is a crucial aspect of education, as students learn to systematically assess and reflect on a problem from different perspectives. Understanding the capability of generative AI to perform this task increases our understanding of the skills of the models, as well as of the challenges educators face when it comes to teaching this crucial skill. While there is a multitude of individual examples and anecdotal evidence for the quality of AI-generated content in this genre (e.g. 4 ) this paper is the first to systematically assess the quality of human-written and AI-generated argumentative texts across different versions of ChatGPT 5 . We use a fine-grained essay quality scoring rubric based on content and language mastery and employ a significant pool of domain experts, i.e. high school teachers across disciplines, to perform the evaluation. Using computational linguistic methods and rigorous statistical analysis, we arrive at several key findings:

AI models generate significantly higher-quality argumentative essays than the users of an essay-writing online forum frequented by German high-school students across all criteria in our scoring rubric.

ChatGPT-4 (ChatGPT web interface with the GPT-4 model) significantly outperforms ChatGPT-3 (ChatGPT web interface with the GPT-3.5 default model) with respect to logical structure, language complexity, vocabulary richness and text linking.

Writing styles between humans and generative AI models differ significantly: for instance, the GPT models use more nominalizations and have higher sentence complexity (signaling more complex, ‘scientific’, language), whereas the students make more use of modal and epistemic constructions (which tend to convey speaker attitude).

The linguistic diversity of the NLG models seems to be improving over time: while ChatGPT-3 still has a significantly lower linguistic diversity than humans, ChatGPT-4 has a significantly higher diversity than the students.

Our work goes significantly beyond existing benchmarks. While OpenAI’s technical report on GPT-4 6 presents some benchmarks, their evaluation lacks scientific rigor: it fails to provide vital information like the agreement between raters, does not report on details regarding the criteria for assessment or to what extent and how a statistical analysis was conducted for a larger sample of essays. In contrast, our benchmark provides the first (statistically) rigorous and systematic study of essay quality, paired with a computational linguistic analysis of the language employed by humans and two different versions of ChatGPT, offering a glance at how these NLG models develop over time. While our work is focused on argumentative essays in education, the genre is also relevant beyond education. In general, studying argumentative essays is one important aspect to understand how good generative AI models are at conveying arguments and, consequently, persuasive writing in general.

Related work

Natural language generation.

The recent interest in generative AI models can be largely attributed to the public release of ChatGPT, a public interface in the form of an interactive chat based on the InstructGPT 1 model, more commonly referred to as GPT-3.5. In comparison to the original GPT-3 7 and other similar generative large language models based on the transformer architecture like GPT-J 8 , this model was not trained in a purely self-supervised manner (e.g. through masked language modeling). Instead, a pipeline that involved human-written content was used to fine-tune the model and improve the quality of the outputs to both mitigate biases and safety issues, as well as make the generated text more similar to text written by humans. Such models are referred to as Fine-tuned LAnguage Nets (FLANs). For details on their training, we refer to the literature 9 . Notably, this process was recently reproduced with publicly available models such as Alpaca 10 and Dolly (i.e. the complete models can be downloaded and not just accessed through an API). However, we can only assume that a similar process was used for the training of GPT-4 since the paper by OpenAI does not include any details on model training.

Testing of the language competency of large-scale NLG systems has only recently started. Cai et al. 11 show that ChatGPT reuses sentence structure, accesses the intended meaning of an ambiguous word, and identifies the thematic structure of a verb and its arguments, replicating human language use. Mahowald 12 compares ChatGPT’s acceptability judgments to human judgments on the Article + Adjective + Numeral + Noun construction in English. Dentella et al. 13 show that ChatGPT-3 fails to understand low-frequent grammatical constructions like complex nested hierarchies and self-embeddings. In another recent line of research, the structure of automatically generated language is evaluated. Guo et al. 14 show that in question-answer scenarios, ChatGPT-3 uses different linguistic devices than humans. Zhao et al. 15 show that ChatGPT generates longer and more diverse responses when the user is in an apparently negative emotional state.

Given that we aim to identify certain linguistic characteristics of human-written versus AI-generated content, we also draw on related work in the field of linguistic fingerprinting, which assumes that each human has a unique way of using language to express themselves, i.e. the linguistic means that are employed to communicate thoughts, opinions and ideas differ between humans. That these properties can be identified with computational linguistic means has been showcased across different tasks: the computation of a linguistic fingerprint allows to distinguish authors of literary works 16 , the identification of speaker profiles in large public debates 17 , 18 , 19 , 20 and the provision of data for forensic voice comparison in broadcast debates 21 , 22 . For educational purposes, linguistic features are used to measure essay readability 23 , essay cohesion 24 and language performance scores for essay grading 25 . Integrating linguistic fingerprints also yields performance advantages for classification tasks, for instance in predicting user opinion 26 , 27 and identifying individual users 28 .

Limitations of OpenAIs ChatGPT evaluations

OpenAI published a discussion of the model’s performance of several tasks, including Advanced Placement (AP) classes within the US educational system 6 . The subjects used in performance evaluation are diverse and include arts, history, English literature, calculus, statistics, physics, chemistry, economics, and US politics. While the models achieved good or very good marks in most subjects, they did not perform well in English literature. GPT-3.5 also experienced problems with chemistry, macroeconomics, physics, and statistics. While the overall results are impressive, there are several significant issues: firstly, the conflict of interest of the model’s owners poses a problem for the performance interpretation. Secondly, there are issues with the soundness of the assessment beyond the conflict of interest, which make the generalizability of the results hard to assess with respect to the models’ capability to write essays. Notably, the AP exams combine multiple-choice questions with free-text answers. Only the aggregated scores are publicly available. To the best of our knowledge, neither the generated free-text answers, their overall assessment, nor their assessment given specific criteria from the used judgment rubric are published. Thirdly, while the paper states that 1–2 qualified third-party contractors participated in the rating of the free-text answers, it is unclear how often multiple ratings were generated for the same answer and what was the agreement between them. This lack of information hinders a scientifically sound judgement regarding the capabilities of these models in general, but also specifically for essays. Lastly, the owners of the model conducted their study in a few-shot prompt setting, where they gave the models a very structured template as well as an example of a human-written high-quality essay to guide the generation of the answers. This further fine-tuning of what the models generate could have also influenced the output. The results published by the owners go beyond the AP courses which are directly comparable to our work and also consider other student assessments like Graduate Record Examinations (GREs). However, these evaluations suffer from the same problems with the scientific rigor as the AP classes.

Scientific assessment of ChatGPT

Researchers across the globe are currently assessing the individual capabilities of these models with greater scientific rigor. We note that due to the recency and speed of these developments, the hereafter discussed literature has mostly only been published as pre-prints and has not yet been peer-reviewed. In addition to the above issues concretely related to the assessment of the capabilities to generate student essays, it is also worth noting that there are likely large problems with the trustworthiness of evaluations, because of data contamination, i.e. because the benchmark tasks are part of the training of the model, which enables memorization. For example, Aiyappa et al. 29 find evidence that this is likely the case for benchmark results regarding NLP tasks. This complicates the effort by researchers to assess the capabilities of the models beyond memorization.

Nevertheless, the first assessment results are already available – though mostly focused on ChatGPT-3 and not yet ChatGPT-4. Closest to our work is a study by Yeadon et al. 30 , who also investigate ChatGPT-3 performance when writing essays. They grade essays generated by ChatGPT-3 for five physics questions based on criteria that cover academic content, appreciation of the underlying physics, grasp of subject material, addressing the topic, and writing style. For each question, ten essays were generated and rated independently by five researchers. While the sample size precludes a statistical assessment, the results demonstrate that the AI model is capable of writing high-quality physics essays, but that the quality varies in a manner similar to human-written essays.

Guo et al. 14 create a set of free-text question answering tasks based on data they collected from the internet, e.g. question answering from Reddit. The authors then sample thirty triplets of a question, a human answer, and a ChatGPT-3 generated answer and ask human raters to assess if they can detect which was written by a human, and which was written by an AI. While this approach does not directly assess the quality of the output, it serves as a Turing test 31 designed to evaluate whether humans can distinguish between human- and AI-produced output. The results indicate that humans are in fact able to distinguish between the outputs when presented with a pair of answers. Humans familiar with ChatGPT are also able to identify over 80% of AI-generated answers without seeing a human answer in comparison. However, humans who are not yet familiar with ChatGPT-3 are not capable of identifying AI-written answers about 50% of the time. Moreover, the authors also find that the AI-generated outputs are deemed to be more helpful than the human answers in slightly more than half of the cases. This suggests that the strong results from OpenAI’s own benchmarks regarding the capabilities to generate free-text answers generalize beyond the benchmarks.

There are, however, some indicators that the benchmarks may be overly optimistic in their assessment of the model’s capabilities. For example, Kortemeyer 32 conducts a case study to assess how well ChatGPT-3 would perform in a physics class, simulating the tasks that students need to complete as part of the course: answer multiple-choice questions, do homework assignments, ask questions during a lesson, complete programming exercises, and write exams with free-text questions. Notably, ChatGPT-3 was allowed to interact with the instructor for many of the tasks, allowing for multiple attempts as well as feedback on preliminary solutions. The experiment shows that ChatGPT-3’s performance is in many aspects similar to that of the beginning learners and that the model makes similar mistakes, such as omitting units or simply plugging in results from equations. Overall, the AI would have passed the course with a low score of 1.5 out of 4.0. Similarly, Kung et al. 33 study the performance of ChatGPT-3 in the United States Medical Licensing Exam (USMLE) and find that the model performs at or near the passing threshold. Their assessment is a bit more optimistic than Kortemeyer’s as they state that this level of performance, comprehensible reasoning and valid clinical insights suggest that models such as ChatGPT may potentially assist human learning in clinical decision making.

Frieder et al. 34 evaluate the capabilities of ChatGPT-3 in solving graduate-level mathematical tasks. They find that while ChatGPT-3 seems to have some mathematical understanding, its level is well below that of an average student and in most cases is not sufficient to pass exams. Yuan et al. 35 consider the arithmetic abilities of language models, including ChatGPT-3 and ChatGPT-4. They find that they exhibit the best performance among other currently available language models (incl. Llama 36 , FLAN-T5 37 , and Bloom 38 ). However, the accuracy of basic arithmetic tasks is still only at 83% when considering correctness to the degree of $10^{-3}$ , i.e. such models are still not capable of functioning reliably as calculators. In a slightly satiric, yet insightful take, Spencer et al. 39 assess how a scientific paper on gamma-ray astrophysics would look like, if it were written largely with the assistance of ChatGPT-3. They find that while the language capabilities are good and the model is capable of generating equations, the arguments are often flawed and the references to scientific literature are full of hallucinations.

The general reasoning skills of the models may also not be at the level expected from the benchmarks. For example, Cherian et al. 40 evaluate how well ChatGPT-3 performs on eleven puzzles that second graders should be able to solve and find that ChatGPT is only able to solve them on average in 36.4% of attempts, whereas the second graders achieve a mean of 60.4%. However, their sample size is very small and the problem was posed as a multiple-choice question answering problem, which cannot be directly compared to the NLG we consider.

Research gap

Within this article, we address an important part of the current research gap regarding the capabilities of ChatGPT (and similar technologies), guided by the following research questions:

RQ1: How good is ChatGPT based on GPT-3 and GPT-4 at writing argumentative student essays?

RQ2: How do AI-generated essays compare to essays written by students?

RQ3: What are linguistic devices that are characteristic of student versus AI-generated content?

We study these aspects with the help of a large group of teaching professionals who systematically assess a large corpus of student essays. To the best of our knowledge, this is the first large-scale, independent scientific assessment of ChatGPT (or similar models) of this kind. Answering these questions is crucial to understanding the impact of ChatGPT on the future of education.

Materials and methods

The essay topics originate from a corpus of argumentative essays in the field of argument mining 41 . Argumentative essays require students to think critically about a topic and use evidence to establish a position on the topic in a concise manner. The corpus features essays for 90 topics from Essay Forum 42 , an active community for providing writing feedback on different kinds of text and is frequented by high-school students to get feedback from native speakers on their essay-writing capabilities. Information about the age of the writers is not available, but the topics indicate that the essays were written in grades 11–13, indicating that the authors were likely at least 16. Topics range from ‘Should students be taught to cooperate or to compete?’ to ‘Will newspapers become a thing of the past?’. In the corpus, each topic features one human-written essay uploaded and discussed in the forum. The students who wrote the essays are not native speakers. The average length of these essays is 19 sentences with 388 tokens (an average of 2.089 characters) and will be termed ‘student essays’ in the remainder of the paper.

For the present study, we use the topics from Stab and Gurevych 41 and prompt ChatGPT with ‘Write an essay with about 200 words on “[ topic ]”’ to receive automatically-generated essays from the ChatGPT-3 and ChatGPT-4 versions from 22 March 2023 (‘ChatGPT-3 essays’, ‘ChatGPT-4 essays’). No additional prompts for getting the responses were used, i.e. the data was created with a basic prompt in a zero-shot scenario. This is in contrast to the benchmarks by OpenAI, who used an engineered prompt in a few-shot scenario to guide the generation of essays. We note that we decided to ask for 200 words because we noticed a tendency to generate essays that are longer than the desired length by ChatGPT. A prompt asking for 300 words typically yielded essays with more than 400 words. Thus, using the shorter length of 200, we prevent a potential advantage for ChatGPT through longer essays, and instead err on the side of brevity. Similar to the evaluations of free-text answers by OpenAI, we did not consider multiple configurations of the model due to the effort required to obtain human judgments. For the same reason, our data is restricted to ChatGPT and does not include other models available at that time, e.g. Alpaca. We use the browser versions of the tools because we consider this to be a more realistic scenario than using the API. Table 1 below shows the core statistics of the resulting dataset. Supplemental material S1 shows examples for essays from the data set.

Annotation study

Study participants.

The participants had registered for a two-hour online training entitled ‘ChatGPT – Challenges and Opportunities’ conducted by the authors of this paper as a means to provide teachers with some of the technological background of NLG systems in general and ChatGPT in particular. Only teachers permanently employed at secondary schools were allowed to register for this training. Focusing on these experts alone allows us to receive meaningful results as those participants have a wide range of experience in assessing students’ writing. A total of 139 teachers registered for the training, 129 of them teach at grammar schools, and only 10 teachers hold a position at other secondary schools. About half of the registered teachers (68 teachers) have been in service for many years and have successfully applied for promotion. For data protection reasons, we do not know the subject combinations of the registered teachers. We only know that a variety of subjects are represented, including languages (English, French and German), religion/ethics, and science. Supplemental material S5 provides some general information regarding German teacher qualifications.

The training began with an online lecture followed by a discussion phase. Teachers were given an overview of language models and basic information on how ChatGPT was developed. After about 45 minutes, the teachers received a both written and oral explanation of the questionnaire at the core of our study (see Supplementary material S3 ) and were informed that they had 30 minutes to finish the study tasks. The explanation included information on how the data was obtained, why we collect the self-assessment, and how we chose the criteria for the rating of the essays, the overall goal of our research, and a walk-through of the questionnaire. Participation in the questionnaire was voluntary and did not affect the awarding of a training certificate. We further informed participants that all data was collected anonymously and that we would have no way of identifying who participated in the questionnaire. We orally informed participants that they consent to the use of the provided ratings for our research by participating in the survey.

Once these instructions were provided orally and in writing, the link to the online form was given to the participants. The online form was running on a local server that did not log any information that could identify the participants (e.g. IP address) to ensure anonymity. As per instructions, consent for participation was given by using the online form. Due to the full anonymity, we could by definition not document who exactly provided the consent. This was implemented as further insurance that non-participation could not possibly affect being awarded the training certificate.

About 20% of the training participants did not take part in the questionnaire study, the remaining participants consented based on the information provided and participated in the rating of essays. After the questionnaire, we continued with an online lecture on the opportunities of using ChatGPT for teaching as well as AI beyond chatbots. The study protocol was reviewed and approved by the Research Ethics Committee of the University of Passau. We further confirm that our study protocol is in accordance with all relevant guidelines.

Questionnaire

The questionnaire consists of three parts: first, a brief self-assessment regarding the English skills of the participants which is based on the Common European Framework of Reference for Languages (CEFR) 43 . We have six levels ranging from ‘comparable to a native speaker’ to ‘some basic skills’ (see supplementary material S3 ). Then each participant was shown six essays. The participants were only shown the generated text and were not provided with information on whether the text was human-written or AI-generated.

The questionnaire covers the seven categories relevant for essay assessment shown below (for details see supplementary material S3 ):

Topic and completeness

Logic and composition

Expressiveness and comprehensiveness

Language mastery

Vocabulary and text linking

Language constructs

These categories are used as guidelines for essay assessment 44 established by the Ministry for Education of Lower Saxony, Germany. For each criterion, a seven-point Likert scale with scores from zero to six is defined, where zero is the worst score (e.g. no relation to the topic) and six is the best score (e.g. addressed the topic to a special degree). The questionnaire included a written description as guidance for the scoring.

After rating each essay, the participants were also asked to self-assess their confidence in the ratings. We used a five-point Likert scale based on the criteria for the self-assessment of peer-review scores from the Association for Computational Linguistics (ACL). Once a participant finished rating the six essays, they were shown a summary of their ratings, as well as the individual ratings for each of their essays and the information on how the essay was generated.

Computational linguistic analysis

In order to further explore and compare the quality of the essays written by students and ChatGPT, we consider the six following linguistic characteristics: lexical diversity, sentence complexity, nominalization, presence of modals, epistemic and discourse markers. Those are motivated by previous work: Weiss et al. 25 observe the correlation between measures of lexical, syntactic and discourse complexities to the essay gradings of German high-school examinations while McNamara et al. 45 explore cohesion (indicated, among other things, by connectives), syntactic complexity and lexical diversity in relation to the essay scoring.

Lexical diversity

We identify vocabulary richness by using a well-established measure of textual, lexical diversity (MTLD) 46 which is often used in the field of automated essay grading 25 , 45 , 47 . It takes into account the number of unique words but unlike the best-known measure of lexical diversity, the type-token ratio (TTR), it is not as sensitive to the difference in the length of the texts. In fact, Koizumi and In’nami 48 find it to be least affected by the differences in the length of the texts compared to some other measures of lexical diversity. This is relevant to us due to the difference in average length between the human-written and ChatGPT-generated essays.

Syntactic complexity

We use two measures in order to evaluate the syntactic complexity of the essays. One is based on the maximum depth of the sentence dependency tree which is produced using the spaCy 3.4.2 dependency parser 49 (‘Syntactic complexity (depth)’). For the second measure, we adopt an approach similar in nature to the one by Weiss et al. 25 who use clause structure to evaluate syntactic complexity. In our case, we count the number of conjuncts, clausal modifiers of nouns, adverbial clause modifiers, clausal complements, clausal subjects, and parataxes (‘Syntactic complexity (clauses)’). The supplementary material in S2 shows the difference between sentence complexity based on two examples from the data.

Nominalization is a common feature of a more scientific style of writing 50 and is used as an additional measure for syntactic complexity. In order to explore this feature, we count occurrences of nouns with suffixes such as ‘-ion’, ‘-ment’, ‘-ance’ and a few others which are known to transform verbs into nouns.

Semantic properties

Both modals and epistemic markers signal the commitment of the writer to their statement. We identify modals using the POS-tagging module provided by spaCy as well as a list of epistemic expressions of modality, such as ‘definitely’ and ‘potentially’, also used in other approaches to identifying semantic properties 51 . For epistemic markers we adopt an empirically-driven approach and utilize the epistemic markers identified in a corpus of dialogical argumentation by Hautli-Janisz et al. 52 . We consider expressions such as ‘I think’, ‘it is believed’ and ‘in my opinion’ to be epistemic.

Discourse properties

Discourse markers can be used to measure the coherence quality of a text. This has been explored by Somasundaran et al. 53 who use discourse markers to evaluate the story-telling aspect of student writing while Nadeem et al. 54 incorporated them in their deep learning-based approach to automated essay scoring. In the present paper, we employ the PDTB list of discourse markers 55 which we adjust to exclude words that are often used for purposes other than indicating discourse relations, such as ‘like’, ‘for’, ‘in’ etc.

Statistical methods

We use a within-subjects design for our study. Each participant was shown six randomly selected essays. Results were submitted to the survey system after each essay was completed, in case participants ran out of time and did not finish scoring all six essays. Cronbach’s $\alpha$ 56 allows us to determine the inter-rater reliability for the rating criterion and data source (human, ChatGPT-3, ChatGPT-4) in order to understand the reliability of our data not only overall, but also for each data source and rating criterion. We use two-sided Wilcoxon-rank-sum tests 57 to confirm the significance of the differences between the data sources for each criterion. We use the same tests to determine the significance of the linguistic characteristics. This results in three comparisons (human vs. ChatGPT-3, human vs. ChatGPT-4, ChatGPT-3 vs. ChatGPT-4) for each of the seven rating criteria and each of the seven linguistic characteristics, i.e. 42 tests. We use the Holm-Bonferroni method 58 for the correction for multiple tests to achieve a family-wise error rate of 0.05. We report the effect size using Cohen’s d 59 . While our data is not perfectly normal, it also does not have severe outliers, so we prefer the clear interpretation of Cohen’s d over the slightly more appropriate, but less accessible non-parametric effect size measures. We report point plots with estimates of the mean scores for each data source and criterion, incl. the 95% confidence interval of these mean values. The confidence intervals are estimated in a non-parametric manner based on bootstrap sampling. We further visualize the distribution for each criterion using violin plots to provide a visual indicator of the spread of the data (see Supplementary material S4 ).

Further, we use the self-assessment of the English skills and confidence in the essay ratings as confounding variables. Through this, we determine if ratings are affected by the language skills or confidence, instead of the actual quality of the essays. We control for the impact of these by measuring Pearson’s correlation coefficient r 60 between the self-assessments and the ratings. We also determine whether the linguistic features are correlated with the ratings as expected. The sentence complexity (both tree depth and dependency clauses), as well as the nominalization, are indicators of the complexity of the language. Similarly, the use of discourse markers should signal a proper logical structure. Finally, a large lexical diversity should be correlated with the ratings for the vocabulary. Same as above, we measure Pearson’s r . We use a two-sided test for the significance based on a $\beta$ -distribution that models the expected correlations as implemented by scipy 61 . Same as above, we use the Holm-Bonferroni method to account for multiple tests. However, we note that it is likely that all—even tiny—correlations are significant given our amount of data. Consequently, our interpretation of these results focuses on the strength of the correlations.

Our statistical analysis of the data is implemented in Python. We use pandas 1.5.3 and numpy 1.24.2 for the processing of data, pingouin 0.5.3 for the calculation of Cronbach’s $\alpha$ , scipy 1.10.1 for the Wilcoxon-rank-sum tests Pearson’s r , and seaborn 0.12.2 for the generation of plots, incl. the calculation of error bars that visualize the confidence intervals.

Out of the 111 teachers who completed the questionnaire, 108 rated all six essays, one rated five essays, one rated two essays, and one rated only one essay. This results in 658 ratings for 270 essays (90 topics for each essay type: human-, ChatGPT-3-, ChatGPT-4-generated), with three ratings for 121 essays, two ratings for 144 essays, and one rating for five essays. The inter-rater agreement is consistently excellent ( $\alpha >0.9$ ), with the exception of language mastery where we have good agreement ( $\alpha =0.89$ , see Table 2 ). Further, the correlation analysis depicted in supplementary material S4 shows weak positive correlations ( $r \in 0.11, 0.28]$ ) between the self-assessment for the English skills, respectively the self-assessment for the confidence in ratings and the actual ratings. Overall, this indicates that our ratings are reliable estimates of the actual quality of the essays with a potential small tendency that confidence in ratings and language skills yields better ratings, independent of the data source.

Table 2 and supplementary material S4 characterize the distribution of the ratings for the essays, grouped by the data source. We observe that for all criteria, we have a clear order of the mean values, with students having the worst ratings, ChatGPT-3 in the middle rank, and ChatGPT-4 with the best performance. We further observe that the standard deviations are fairly consistent and slightly larger than one, i.e. the spread is similar for all ratings and essays. This is further supported by the visual analysis of the violin plots.

The statistical analysis of the ratings reported in Table 4 shows that differences between the human-written essays and the ones generated by both ChatGPT models are significant. The effect sizes for human versus ChatGPT-3 essays are between 0.52 and 1.15, i.e. a medium ( $d \in [0.5,0.8)$ ) to large ( $d \in [0.8, 1.2)$ ) effect. On the one hand, the smallest effects are observed for the expressiveness and complexity, i.e. when it comes to the overall comprehensiveness and complexity of the sentence structures, the differences between the humans and the ChatGPT-3 model are smallest. On the other hand, the difference in language mastery is larger than all other differences, which indicates that humans are more prone to making mistakes when writing than the NLG models. The magnitude of differences between humans and ChatGPT-4 is larger with effect sizes between 0.88 and 1.43, i.e., a large to very large ( $d \in [1.2, 2)$ ) effect. Same as for ChatGPT-3, the differences are smallest for expressiveness and complexity and largest for language mastery. Please note that the difference in language mastery between humans and both GPT models does not mean that the humans have low scores for language mastery (M=3.90), but rather that the NLG models have exceptionally high scores (M=5.03 for ChatGPT-3, M=5.25 for ChatGPT-4).

When we consider the differences between the two GPT models, we observe that while ChatGPT-4 has consistently higher mean values for all criteria, only the differences for logic and composition, vocabulary and text linking, and complexity are significant. The effect sizes are between 0.45 and 0.5, i.e. small ( $d \in [0.2, 0.5)$ ) and medium. Thus, while GPT-4 seems to be an improvement over GPT-3.5 in general, the only clear indicator of this is a better and clearer logical composition and more complex writing with a more diverse vocabulary.

We also observe significant differences in the distribution of linguistic characteristics between all three groups (see Table 3 ). Sentence complexity (depth) is the only category without a significant difference between humans and ChatGPT-3, as well as ChatGPT-3 and ChatGPT-4. There is also no significant difference in the category of discourse markers between humans and ChatGPT-3. The magnitude of the effects varies a lot and is between 0.39 and 1.93, i.e., between small ( $d \in [0.2, 0.5)$ ) and very large. However, in comparison to the ratings, there is no clear tendency regarding the direction of the differences. For instance, while the ChatGPT models write more complex sentences and use more nominalizations, humans tend to use more modals and epistemic markers instead. The lexical diversity of humans is higher than that of ChatGPT-3 but lower than that of ChatGPT-4. While there is no difference in the use of discourse markers between humans and ChatGPT-3, ChatGPT-4 uses significantly fewer discourse markers.

We detect the expected positive correlations between the complexity ratings and the linguistic markers for sentence complexity ( $r=0.16$ for depth, $r=0.19$ for clauses) and nominalizations ( $r=0.22$ ). However, we observe a negative correlation between the logic ratings and the discourse markers ( $r=-0.14$ ), which counters our intuition that more frequent use of discourse indicators makes a text more logically coherent. However, this is in line with previous work: McNamara et al. 45 also find no indication that the use of cohesion indices such as discourse connectives correlates with high- and low-proficiency essays. Finally, we observe the expected positive correlation between the ratings for the vocabulary and the lexical diversity ( $r=0.12$ ). All observed correlations are significant. However, we note that the strength of all these correlations is weak and that the significance itself should not be over-interpreted due to the large sample size.

Our results provide clear answers to the first two research questions that consider the quality of the generated essays: ChatGPT performs well at writing argumentative student essays and outperforms the quality of the human-written essays significantly. The ChatGPT-4 model has (at least) a large effect and is on average about one point better than humans on a seven-point Likert scale.

Regarding the third research question, we find that there are significant linguistic differences between humans and AI-generated content. The AI-generated essays are highly structured, which for instance is reflected by the identical beginnings of the concluding sections of all ChatGPT essays (‘In conclusion, [...]’). The initial sentences of each essay are also very similar starting with a general statement using the main concepts of the essay topics. Although this corresponds to the general structure that is sought after for argumentative essays, it is striking to see that the ChatGPT models are so rigid in realizing this, whereas the human-written essays are looser in representing the guideline on the linguistic surface. Moreover, the linguistic fingerprint has the counter-intuitive property that the use of discourse markers is negatively correlated with logical coherence. We believe that this might be due to the rigid structure of the generated essays: instead of using discourse markers, the AI models provide a clear logical structure by separating the different arguments into paragraphs, thereby reducing the need for discourse markers.

Our data also shows that hallucinations are not a problem in the setting of argumentative essay writing: the essay topics are not really about factual correctness, but rather about argumentation and critical reflection on general concepts which seem to be contained within the knowledge of the AI model. The stochastic nature of the language generation is well-suited for this kind of task, as different plausible arguments can be seen as a sampling from all available arguments for a topic. Nevertheless, we need to perform a more systematic study of the argumentative structures in order to better understand the difference in argumentation between human-written and ChatGPT-generated essay content. Moreover, we also cannot rule out that subtle hallucinations may have been overlooked during the ratings. There are also essays with a low rating for the criteria related to factual correctness, indicating that there might be cases where the AI models still have problems, even if they are, on average, better than the students.

One of the issues with evaluations of the recent large-language models is not accounting for the impact of tainted data when benchmarking such models. While it is certainly possible that the essays that were sourced by Stab and Gurevych 41 from the internet were part of the training data of the GPT models, the proprietary nature of the model training means that we cannot confirm this. However, we note that the generated essays did not resemble the corpus of human essays at all. Moreover, the topics of the essays are general in the sense that any human should be able to reason and write about these topics, just by understanding concepts like ‘cooperation’. Consequently, a taint on these general topics, i.e. the fact that they might be present in the data, is not only possible but is actually expected and unproblematic, as it relates to the capability of the models to learn about concepts, rather than the memorization of specific task solutions.

While we did everything to ensure a sound construct and a high validity of our study, there are still certain issues that may affect our conclusions. Most importantly, neither the writers of the essays, nor their raters, were English native speakers. However, the students purposefully used a forum for English writing frequented by native speakers to ensure the language and content quality of their essays. This indicates that the resulting essays are likely above average for non-native speakers, as they went through at least one round of revisions with the help of native speakers. The teachers were informed that part of the training would be in English to prevent registrations from people without English language skills. Moreover, the self-assessment of the language skills was only weakly correlated with the ratings, indicating that the threat to the soundness of our results is low. While we cannot definitively rule out that our results would not be reproducible with other human raters, the high inter-rater agreement indicates that this is unlikely.

However, our reliance on essays written by non-native speakers affects the external validity and the generalizability of our results. It is certainly possible that native speaking students would perform better in the criteria related to language skills, though it is unclear by how much. However, the language skills were particular strengths of the AI models, meaning that while the difference might be smaller, it is still reasonable to conclude that the AI models would have at least comparable performance to humans, but possibly still better performance, just with a smaller gap. While we cannot rule out a difference for the content-related criteria, we also see no strong argument why native speakers should have better arguments than non-native speakers. Thus, while our results might not fully translate to native speakers, we see no reason why aspects regarding the content should not be similar. Further, our results were obtained based on high-school-level essays. Native and non-native speakers with higher education degrees or experts in fields would likely also achieve a better performance, such that the difference in performance between the AI models and humans would likely also be smaller in such a setting.

We further note that the essay topics may not be an unbiased sample. While Stab and Gurevych 41 randomly sampled the essays from the writing feedback section of an essay forum, it is unclear whether the essays posted there are representative of the general population of essay topics. Nevertheless, we believe that the threat is fairly low because our results are consistent and do not seem to be influenced by certain topics. Further, we cannot with certainty conclude how our results generalize beyond ChatGPT-3 and ChatGPT-4 to similar models like Bard ( https://bard.google.com/?hl=en ) Alpaca, and Dolly. Especially the results for linguistic characteristics are hard to predict. However, since—to the best of our knowledge and given the proprietary nature of some of these models—the general approach to how these models work is similar and the trends for essay quality should hold for models with comparable size and training procedures.

Finally, we want to note that the current speed of progress with generative AI is extremely fast and we are studying moving targets: ChatGPT 3.5 and 4 today are already not the same as the models we studied. Due to a lack of transparency regarding the specific incremental changes, we cannot know or predict how this might affect our results.

Our results provide a strong indication that the fear many teaching professionals have is warranted: the way students do homework and teachers assess it needs to change in a world of generative AI models. For non-native speakers, our results show that when students want to maximize their essay grades, they could easily do so by relying on results from AI models like ChatGPT. The very strong performance of the AI models indicates that this might also be the case for native speakers, though the difference in language skills is probably smaller. However, this is not and cannot be the goal of education. Consequently, educators need to change how they approach homework. Instead of just assigning and grading essays, we need to reflect more on the output of AI tools regarding their reasoning and correctness. AI models need to be seen as an integral part of education, but one which requires careful reflection and training of critical thinking skills.

Furthermore, teachers need to adapt strategies for teaching writing skills: as with the use of calculators, it is necessary to critically reflect with the students on when and how to use those tools. For instance, constructivists 62 argue that learning is enhanced by the active design and creation of unique artifacts by students themselves. In the present case this means that, in the long term, educational objectives may need to be adjusted. This is analogous to teaching good arithmetic skills to younger students and then allowing and encouraging students to use calculators freely in later stages of education. Similarly, once a sound level of literacy has been achieved, strongly integrating AI models in lesson plans may no longer run counter to reasonable learning goals.

In terms of shedding light on the quality and structure of AI-generated essays, this paper makes an important contribution by offering an independent, large-scale and statistically sound account of essay quality, comparing human-written and AI-generated texts. By comparing different versions of ChatGPT, we also offer a glance into the development of these models over time in terms of their linguistic properties and the quality they exhibit. Our results show that while the language generated by ChatGPT is considered very good by humans, there are also notable structural differences, e.g. in the use of discourse markers. This demonstrates that an in-depth consideration not only of the capabilities of generative AI models is required (i.e. which tasks can they be used for), but also of the language they generate. For example, if we read many AI-generated texts that use fewer discourse markers, it raises the question if and how this would affect our human use of discourse markers. Understanding how AI-generated texts differ from human-written enables us to look for these differences, to reason about their potential impact, and to study and possibly mitigate this impact.

Data availability

The datasets generated during and/or analysed during the current study are available in the Zenodo repository, https://doi.org/10.5281/zenodo.8343644

Code availability

All materials are available online in form of a replication package that contains the data and the analysis code, https://doi.org/10.5281/zenodo.8343644 .

Ouyang, L. et al. Training language models to follow instructions with human feedback (2022). arXiv:2203.02155 .

Ruby, D. 30+ detailed chatgpt statistics–users & facts (sep 2023). https://www.demandsage.com/chatgpt-statistics/ (2023). Accessed 09 June 2023.

Leahy, S. & Mishra, P. TPACK and the Cambrian explosion of AI. In Society for Information Technology & Teacher Education International Conference , (ed. Langran, E.) 2465–2469 (Association for the Advancement of Computing in Education (AACE), 2023).

Ortiz, S. Need an ai essay writer? here’s how chatgpt (and other chatbots) can help. https://www.zdnet.com/article/how-to-use-chatgpt-to-write-an-essay/ (2023). Accessed 09 June 2023.

Openai chat interface. https://chat.openai.com/ . Accessed 09 June 2023.

OpenAI. Gpt-4 technical report (2023). arXiv:2303.08774 .

Brown, T. B. et al. Language models are few-shot learners (2020). arXiv:2005.14165 .

Wang, B. Mesh-Transformer-JAX: Model-Parallel Implementation of Transformer Language Model with JAX. https://github.com/kingoflolz/mesh-transformer-jax (2021).

Wei, J. et al. Finetuned language models are zero-shot learners. In International Conference on Learning Representations (2022).

Taori, R. et al. Stanford alpaca: An instruction-following llama model. https://github.com/tatsu-lab/stanford_alpaca (2023).

Cai, Z. G., Haslett, D. A., Duan, X., Wang, S. & Pickering, M. J. Does chatgpt resemble humans in language use? (2023). arXiv:2303.08014 .

Mahowald, K. A discerning several thousand judgments: Gpt-3 rates the article + adjective + numeral + noun construction (2023). arXiv:2301.12564 .

Dentella, V., Murphy, E., Marcus, G. & Leivada, E. Testing ai performance on less frequent aspects of language reveals insensitivity to underlying meaning (2023). arXiv:2302.12313 .

Guo, B. et al. How close is chatgpt to human experts? comparison corpus, evaluation, and detection (2023). arXiv:2301.07597 .

Zhao, W. et al. Is chatgpt equipped with emotional dialogue capabilities? (2023). arXiv:2304.09582 .

Keim, D. A. & Oelke, D. Literature fingerprinting : A new method for visual literary analysis. In 2007 IEEE Symposium on Visual Analytics Science and Technology , 115–122, https://doi.org/10.1109/VAST.2007.4389004 (IEEE, 2007).

El-Assady, M. et al. Interactive visual analysis of transcribed multi-party discourse. In Proceedings of ACL 2017, System Demonstrations , 49–54 (Association for Computational Linguistics, Vancouver, Canada, 2017).

Mennatallah El-Assady, A. H.-J. & Butt, M. Discourse maps - feature encoding for the analysis of verbatim conversation transcripts. In Visual Analytics for Linguistics , vol. CSLI Lecture Notes, Number 220, 115–147 (Stanford: CSLI Publications, 2020).

Matt Foulis, J. V. & Reed, C. Dialogical fingerprinting of debaters. In Proceedings of COMMA 2020 , 465–466, https://doi.org/10.3233/FAIA200536 (Amsterdam: IOS Press, 2020).

Matt Foulis, J. V. & Reed, C. Interactive visualisation of debater identification and characteristics. In Proceedings of the COMMA workshop on Argument Visualisation, COMMA , 1–7 (2020).

Chatzipanagiotidis, S., Giagkou, M. & Meurers, D. Broad linguistic complexity analysis for Greek readability classification. In Proceedings of the 16th Workshop on Innovative Use of NLP for Building Educational Applications , 48–58 (Association for Computational Linguistics, Online, 2021).

Ajili, M., Bonastre, J.-F., Kahn, J., Rossato, S. & Bernard, G. FABIOLE, a speech database for forensic speaker comparison. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16) , 726–733 (European Language Resources Association (ELRA), Portorož, Slovenia, 2016).

Deutsch, T., Jasbi, M. & Shieber, S. Linguistic features for readability assessment. In Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications , 1–17, https://doi.org/10.18653/v1/2020.bea-1.1 (Association for Computational Linguistics, Seattle, WA, USA $\rightarrow$ Online, 2020).

Fiacco, J., Jiang, S., Adamson, D. & Rosé, C. Toward automatic discourse parsing of student writing motivated by neural interpretation. In Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022) , 204–215, https://doi.org/10.18653/v1/2022.bea-1.25 (Association for Computational Linguistics, Seattle, Washington, 2022).

Weiss, Z., Riemenschneider, A., Schröter, P. & Meurers, D. Computationally modeling the impact of task-appropriate language complexity and accuracy on human grading of German essays. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications , 30–45, https://doi.org/10.18653/v1/W19-4404 (Association for Computational Linguistics, Florence, Italy, 2019).

Yang, F., Dragut, E. & Mukherjee, A. Predicting personal opinion on future events with fingerprints. In Proceedings of the 28th International Conference on Computational Linguistics , 1802–1807, https://doi.org/10.18653/v1/2020.coling-main.162 (International Committee on Computational Linguistics, Barcelona, Spain (Online), 2020).

Tumarada, K. et al. Opinion prediction with user fingerprinting. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021) , 1423–1431 (INCOMA Ltd., Held Online, 2021).

Rocca, R. & Yarkoni, T. Language as a fingerprint: Self-supervised learning of user encodings using transformers. In Findings of the Association for Computational Linguistics: EMNLP . 1701–1714 (Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 2022).

Aiyappa, R., An, J., Kwak, H. & Ahn, Y.-Y. Can we trust the evaluation on chatgpt? (2023). arXiv:2303.12767 .

Yeadon, W., Inyang, O.-O., Mizouri, A., Peach, A. & Testrow, C. The death of the short-form physics essay in the coming ai revolution (2022). arXiv:2212.11661 .

TURING, A. M. I.-COMPUTING MACHINERY AND INTELLIGENCE. Mind LIX , 433–460, https://doi.org/10.1093/mind/LIX.236.433 (1950). https://academic.oup.com/mind/article-pdf/LIX/236/433/30123314/lix-236-433.pdf .

Kortemeyer, G. Could an artificial-intelligence agent pass an introductory physics course? (2023). arXiv:2301.12127 .

Kung, T. H. et al. Performance of chatgpt on usmle: Potential for ai-assisted medical education using large language models. PLOS Digital Health 2 , 1–12. https://doi.org/10.1371/journal.pdig.0000198 (2023).

Article Google Scholar

Frieder, S. et al. Mathematical capabilities of chatgpt (2023). arXiv:2301.13867 .

Yuan, Z., Yuan, H., Tan, C., Wang, W. & Huang, S. How well do large language models perform in arithmetic tasks? (2023). arXiv:2304.02015 .

Touvron, H. et al. Llama: Open and efficient foundation language models (2023). arXiv:2302.13971 .

Chung, H. W. et al. Scaling instruction-finetuned language models (2022). arXiv:2210.11416 .

Workshop, B. et al. Bloom: A 176b-parameter open-access multilingual language model (2023). arXiv:2211.05100 .

Spencer, S. T., Joshi, V. & Mitchell, A. M. W. Can ai put gamma-ray astrophysicists out of a job? (2023). arXiv:2303.17853 .

Cherian, A., Peng, K.-C., Lohit, S., Smith, K. & Tenenbaum, J. B. Are deep neural networks smarter than second graders? (2023). arXiv:2212.09993 .

Stab, C. & Gurevych, I. Annotating argument components and relations in persuasive essays. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers , 1501–1510 (Dublin City University and Association for Computational Linguistics, Dublin, Ireland, 2014).

Essay forum. https://essayforum.com/ . Last-accessed: 2023-09-07.

Common european framework of reference for languages (cefr). https://www.coe.int/en/web/common-european-framework-reference-languages . Accessed 09 July 2023.

Kmk guidelines for essay assessment. http://www.kmk-format.de/material/Fremdsprachen/5-3-2_Bewertungsskalen_Schreiben.pdf . Accessed 09 July 2023.

McNamara, D. S., Crossley, S. A. & McCarthy, P. M. Linguistic features of writing quality. Writ. Commun. 27 , 57–86 (2010).

McCarthy, P. M. & Jarvis, S. Mtld, vocd-d, and hd-d: A validation study of sophisticated approaches to lexical diversity assessment. Behav. Res. Methods 42 , 381–392 (2010).

Article PubMed Google Scholar

Dasgupta, T., Naskar, A., Dey, L. & Saha, R. Augmenting textual qualitative features in deep convolution recurrent neural network for automatic essay scoring. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications , 93–102 (2018).

Koizumi, R. & In’nami, Y. Effects of text length on lexical diversity measures: Using short texts with less than 200 tokens. System 40 , 554–564 (2012).

spacy industrial-strength natural language processing in python. https://spacy.io/ .

Siskou, W., Friedrich, L., Eckhard, S., Espinoza, I. & Hautli-Janisz, A. Measuring plain language in public service encounters. In Proceedings of the 2nd Workshop on Computational Linguistics for Political Text Analysis (CPSS-2022) (Potsdam, Germany, 2022).

El-Assady, M. & Hautli-Janisz, A. Discourse Maps - Feature Encoding for the Analysis of Verbatim Conversation Transcripts (CSLI lecture notes (CSLI Publications, Center for the Study of Language and Information, 2019).

Hautli-Janisz, A. et al. QT30: A corpus of argument and conflict in broadcast debate. In Proceedings of the Thirteenth Language Resources and Evaluation Conference , 3291–3300 (European Language Resources Association, Marseille, France, 2022).

Somasundaran, S. et al. Towards evaluating narrative quality in student writing. Trans. Assoc. Comput. Linguist. 6 , 91–106 (2018).

Nadeem, F., Nguyen, H., Liu, Y. & Ostendorf, M. Automated essay scoring with discourse-aware neural models. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications , 484–493, https://doi.org/10.18653/v1/W19-4450 (Association for Computational Linguistics, Florence, Italy, 2019).

Prasad, R. et al. The Penn Discourse TreeBank 2.0. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08) (European Language Resources Association (ELRA), Marrakech, Morocco, 2008).

Cronbach, L. J. Coefficient alpha and the internal structure of tests. Psychometrika 16 , 297–334. https://doi.org/10.1007/bf02310555 (1951).

Article MATH Google Scholar

Wilcoxon, F. Individual comparisons by ranking methods. Biom. Bull. 1 , 80–83 (1945).

Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6 , 65–70 (1979).

MathSciNet MATH Google Scholar

Cohen, J. Statistical power analysis for the behavioral sciences (Academic press, 2013).

Freedman, D., Pisani, R. & Purves, R. Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007).

Scipy documentation. https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.pearsonr.html . Accessed 09 June 2023.

Windschitl, M. Framing constructivism in practice as the negotiation of dilemmas: An analysis of the conceptual, pedagogical, cultural, and political challenges facing teachers. Rev. Educ. Res. 72 , 131–175 (2002).

Download references

Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and affiliations.

Faculty of Computer Science and Mathematics, University of Passau, Passau, Germany

Steffen Herbold, Annette Hautli-Janisz, Ute Heuer, Zlata Kikteva & Alexander Trautsch

You can also search for this author in PubMed Google Scholar

Contributions

S.H., A.HJ., and U.H. conceived the experiment; S.H., A.HJ, and Z.K. collected the essays from ChatGPT; U.H. recruited the study participants; S.H., A.HJ., U.H. and A.T. conducted the training session and questionnaire; all authors contributed to the analysis of the results, the writing of the manuscript, and review of the manuscript.

Corresponding author

Correspondence to Steffen Herbold .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary information 1., supplementary information 2., supplementary information 3., supplementary tables., supplementary figures., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Herbold, S., Hautli-Janisz, A., Heuer, U. et al. A large-scale comparison of human-written versus ChatGPT-generated essays. Sci Rep 13 , 18617 (2023). https://doi.org/10.1038/s41598-023-45644-9

Download citation

Received : 01 June 2023

Accepted : 22 October 2023

Published : 30 October 2023

DOI : https://doi.org/10.1038/s41598-023-45644-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Defense against adversarial attacks: robust and efficient compressed optimized neural networks.

Insaf Kraidia
Afifa Ghenai
Samir Brahim Belhaouari

Scientific Reports (2024)

AI-driven translations for kidney transplant equity in Hispanic populations

Oscar A. Garcia Valencia
Charat Thongprayoon
Wisit Cheungpasitporn

How will the state think with ChatGPT? The challenges of generative artificial intelligence for public administrations

Thomas Cantens

AI & SOCIETY (2024)

Students’ Holistic Reading of Socio-Scientific Texts on Climate Change in a ChatGPT Scenario

Kason Ka Ching Cheung
Jack K. H. Pun

Research in Science Education (2024)

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

Write an essay in French

Beyond the fact that writing an essay in French can be a good practice to improve your writing, you may also be asked to write one during your schooling. So, it is important to study the topic of French essay writing and get some useful tips..

» Tips and tricks for your French essay » The structure of a French essay » Sample French Essay

Tips and tricks for your French essay

When writing a French essay for school, you should always use a structured approach and good French skills to present your arguments in a focused way. Beyond French skills, there are also important formal requirements for a successful French essay. We will come back to this in detail later. First, you will find some useful tips and tricks that will help you write more compelling and better French essays in the future.

Have a clear thesis and structure
Do sufficient research and use reliable sources
Use examples and arguments to support your thesis
Avoid plagiarism and cite correctly
Always check structure, grammar and spelling

When you write your essay at school or university, you need to make sure that the general structure of your essay, the presentation of the arguments and, above all, your French language skills play a role in the mark you will get. This is why you should definitely take a closer look at the structure of an essay as well as the most important grammar rules and formulations for French essays.

The structure of a French essay

In an essay, you deal at length and in detail with a usually given topic. When you write an essay in French, you must follow a certain structure. Below we show you what this structure looks like and give you some tips for writing the most important parts of your essay.

The Introduction

The introduction prepares the main body of your essay. You think of a meaningful title for your essay, you describe your thesis or your question, you give general information on the subject and you prepare your argument by giving an overview of your most important arguments.

Below are examples and phrases that you can use to write the introduction to your essay in French.

The title should be meaningful, concise and reflect the content of the essay.

Introductory paragraph

The first paragraph of your French essay should briefly introduce the topic and engage the reader. Here are some examples to help you write your essay:

Proposal or question

The central proposition or question of your French essay should be a clear and concise definition of the purpose of the essay. Use these examples to get a clearer idea of how to write theses in French:

Overview of Arguments and Structure

At the end of your introduction, describe the structure of the main part of your essay (your outline) and outline your argument. Here are some French expressions that will certainly help you write your essay:

The body of your essay

The main part of your French essay deals with the given topic in detail. The subject is studied from all angles. The main body of your essay follows a thread of argument and discusses in detail the main arguments of your thesis previously made in the introduction.

In the body of the text, you should discuss the subject of your essay in clear and concise language. To achieve this, we give you some wording aids as well as vocabulary and phrases that you can use to write your essay in French.

Formulation tools:

French vocabulary for essays.

In the conclusion of your French essay, you address the thesis of your essay, summarize the main points of your discussion in the main body, and draw a conclusion. On the basis of the arguments and the resulting conclusions, you formulate in the conclusion of your dissertation final thoughts and suggestions for the future. It is important that you do not add new information or new arguments. This should only be done in the body of your text.

Here are some wording guides to help you write your essay in French:

Sample French Essay

Les avantages des voyages linguistiques

Malgré les difficultés potentielles, les voyages linguistiques offrent aux apprenants une occasion unique d'améliorer leurs compétences linguistiques et de découvrir de nouvelles cultures, ce qui en fait un investissement précieux pour leur développement personnel et académique.

Les séjours linguistiques sont des voyages organisés dans le but d'améliorer les compétences linguistiques des participants. Ces voyages peuvent se dérouler dans le pays ou à l'étranger et durer d'un week-end à plusieurs semaines. L'un des principaux avantages des séjours linguistiques est l'immersion. Entourés de locuteurs natifs, les apprenants sont contraints de pratiquer et d'améliorer leurs compétences linguistiques dans des situations réelles.Il s'agit d'une méthode d'apprentissage beaucoup plus efficace que le simple fait d'étudier une langue dans une salle de classe.

Un autre avantage des séjours linguistiques est l'expérience culturelle. Voyager dans un nouveau pays permet aux apprenants de découvrir de nouvelles coutumes, traditions et modes de vie, et de se familiariser avec l'histoire et la culture du pays. Cela enrichit non seulement l'expérience d'apprentissage de la langue, mais contribue également à élargir les horizons et à accroître la sensibilisation culturelle.

Cependant, les séjours linguistiques peuvent également présenter des inconvénients. Par exemple, le coût du voyage et de l'hébergement peut être élevé, en particulier pour les séjours de longue durée. En outre, les apprenants peuvent être confrontés à la barrière de la langue ou à un choc culturel, ce qui peut être difficile à surmonter. Le coût et les difficultés potentielles des séjours linguistiques peuvent sembler décourageants, mais ils offrent des avantages précieux en termes d'épanouissement personnel et scolaire.

Les compétences linguistiques et les connaissances culturelles acquises peuvent déboucher sur de nouvelles opportunités d'emploi et améliorer la communication dans un cadre professionnel. Les bourses et les aides financières rendent les séjours linguistiques plus accessibles. Le fait d'être confronté à une barrière linguistique ou à un choc culturel peut également être l'occasion d'un développement personnel. Ces avantages l'emportent largement sur les inconvénients et font des séjours linguistiques un investissement qui en vaut la peine.

En conclusion, malgré les difficultés potentielles, les séjours linguistiques offrent aux apprenants une occasion unique d'améliorer leurs compétences linguistiques et de découvrir de nouvelles cultures, ce qui en fait un investissement précieux pour le développement personnel et académique. Qu'il s'agisse d'un débutant ou d'un apprenant avancé, un voyage linguistique est une expérience à ne pas manquer.

Improve your writing style in French

Learn French with us. We will help you improve your writing skills.

Improve your French with Sprachcaffe

A Year abroad for high school students

Spend a unique school year abroad

Online French courses

Learn French from the comfort of your own home with an online course

Learn French on a language trip

Learn French in a French-speaking country

Have a language expert improve your writing

Check your paper for plagiarism in 10 minutes, generate your apa citations for free.

Knowledge Base

Using AI tools

How to Write an Essay with ChatGPT | Tips & Examples

How to Write an Essay with ChatGPT | Tips & Examples

Published on June 22, 2023 by Koen Driessen . Revised on November 16, 2023.

Passing off AI-generated text as your own work is widely considered plagiarism. However, when used correctly, AI tools like ChatGPT can legitimately help guide your writing process.

These tools are especially helpful in the preparation and revision stages of your essay writing.

You can use ChatGPT to:

Write a research question
Develop an outline
Find relevant source information
Summarize or paraphrase text
Get feedback

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

Writing a research question, developing an outline, finding source recommendations, summarizing/paraphrasing text, getting feedback, other interesting articles, frequently asked questions.

You can use ChatGPT to brainstorm potential research questions or to narrow down your thesis statement . Begin by inputting a description of the research topic or assigned question. Then include a prompt like “Write 3 possible research questions on this topic.”

You can make the prompt as specific as you like. For example, you can include the writing level (e.g., high school essay, college essay), perspective (e.g., first person) and the type of essay you intend to write (e.g., argumentative , descriptive , expository , or narrative ).

You can also mention any facts or viewpoints you’ve gathered that should be incorporated into the output.

If the output doesn’t suit your topic, you can click “Regenerate response” to have the tool generate a new response. You can do this as many times as you like, and you can try making your prompt more specific if you struggle to get the results you want.

Example: Using ChatGPT to write a research question

Generate three possible research questions for an argumentative high school essay on the following topic: “The long-term impact of the Covid-19 pandemic.”
To what extent has the Covid-19 pandemic exacerbated existing social inequalities and what measures can be taken to address these disparities in the long term?
How has the Covid-19 pandemic transformed education systems, and what are the potential long-term implications for students’ learning outcomes and educational equity?
What lessons can be learned from the Covid-19 pandemic to enhance global preparedness and response to future public health crises, and how can these lessons be effectively implemented in the long term?
Based on the second question, develop three further research questions with a specific focus on distance learning.
What are the long-term effects of widespread adoption of distance learning during the Covid-19 pandemic on students’ academic performance, motivation, and overall educational outcomes?
How has the shift to distance learning impacted the social and emotional well-being of students, and what strategies can be implemented to address any negative consequences in the long term?
What are the key factors that contribute to the success of distance learning programs, and how can educational institutions and policymakers ensure equitable access to quality education in the long term, especially for marginalized and underserved student populations?

Don't submit your assignments before you do this

The academic proofreading tool has been trained on 1000s of academic texts. Making it the most accurate and reliable proofreading tool for students. Free citation check included.

Try for free

Once you’ve decided on a research question, you can use ChatGPT to develop an essay outline . This can help keep you on track by giving you a clear idea of what topics you want to discuss and in what order.

Do this by prompting ChatGPT to create an outline for a specific research question, mentioning any topics or points you want to discuss. You can also mention the writing level and the intended length of your essay so that the tool generates an appropriate outline.

You can then refine this by further prompting ChatGPT or editing the outline manually until it meets your requirements.

Examples: Using ChatGPT to generate an essay outline

Develop an outline for an argumentative high school essay with the following research question: “What are the long-term effects of widespread adoption of distance learning during the Covid-19 pandemic on students’ academic performance and overall educational outcomes?”The essay will be about 4 pages long.
Background information on the Covid-19 pandemic and the shift to distance learning
Thesis statement: The widespread adoption of distance learning during the Covid-19 pandemic has had both positive and negative long-term effects on students’ academic performance and overall educational outcomes.
Increased flexibility and personalized learning opportunities
Access to a wider range of resources and educational materials
Development of self-directed learning skills
Critiques and limitations of previous studies
Lack of face-to-face interaction and reduced social engagement
Increased potential for distractions and lack of structure
Technological barriers and unequal access to resources
Examination of studies and data on academic achievement during distance learning
Analysis of long-term effects on educational attainment and future opportunities
Discussion of potential implications for college admissions and career readiness
Strategies for promoting student engagement and motivation in distance learning
Importance of teacher-student communication and support
Addressing technological disparities and ensuring equitable access to resources
Recap of the main points discussed
Emphasize the need for further research and long-term planning to optimize distance learning experiences
Restate the thesis and provide a final thought on the potential long-term effects of distance learning on students’ academic performance and overall educational outcomes

Once you know the scope of your essay, you can find relevant primary and secondary sources to support your argument.

However, we don’t recommend prompting ChatGPT to generate a list of sources as it occasionally makes mistakes (like listing nonexistent sources). Instead, it’s a good idea to use ChatGPT to get suggestions for the types of sources relevant to your essay and track them down using a credible research database or your institution’s library.

When you have found relevant sources, use a specialized tool like the Scribbr Citation Generator to cite them in your essay.

Example: Using ChatGPT to find sources

What types of sources can I use to write an essay on the following research question?”What are the long-term effects of widespread adoption of distance learning during the Covid-19 pandemic on students’ academic performance and overall educational outcomes?”
Academic Journals and Research Articles: Look for scholarly articles and research studies published in peer-reviewed academic journals. These sources often provide in-depth analysis, empirical evidence, and statistical data on the long-term effects of distance learning.
Educational and Government Reports: Reports published by educational institutions, government agencies, or educational organizations can offer valuable insights into the impact of distance learning on academic performance and educational outcomes. These reports may include surveys, case studies, and data analysis specific to the Covid-19 pandemic and distance learning.
Official Websites and Publications: Explore the official websites of educational institutions, education ministries, or educational technology companies. They often publish articles, white papers, or research findings related to distance learning and its effects on students’ academic performance.
Expert Interviews or Opinion Pieces: Seek out interviews or opinion pieces from experts in the field of education, distance learning, or pedagogy. These sources can provide valuable perspectives and insights on the long-term effects of distance learning on students’ educational outcomes.
Online Databases and Digital Libraries: Utilize online databases and digital libraries such as JSTOR, Google Scholar, or academic databases provided by your educational institution. These platforms offer a wide range of scholarly articles, research papers, and publications that can support your arguments.
Surveys and Studies Conducted by Educational Institutions: Some schools or universities may have conducted their own surveys or studies to evaluate the impact of distance learning on students. Check if your educational institution has published any research findings or survey results that are relevant to your topic.

During your writing process, you can use ChatGPT as a summarizing tool to condense text to its essential ideas or as a paraphraser to rephrase text in clear, accessible language. Using ChatGPT in these ways can help you to understand complex material, express your own ideas more clearly, and avoid repetition.

Simply input the relevant text and prompt the tool to summarize or paraphrase it. Alternatively, you can use Scribbr’s free text summarizer and Scribbr’s free paraphrasing tool , which are specifically designed for these purposes.

Example: Using ChatGPT to summarize/paraphrase

Paraphrase the following text using clear language:”Engaging in an extensive examination of the intricate interplay between remote instructional methods and academic achievement necessitates consideration of diverse factors, including the pedagogical efficacy of virtual platforms, the socioemotional ramifications of reduced face-to-face interactions, the equitable accessibility of technological resources, and the potential long-lasting implications for students’ educational trajectories and future opportunities.”
To thoroughly explore the connection between remote teaching methods and academic success, it is crucial to take into account various factors. These factors include evaluating how well virtual platforms support effective teaching, understanding the impact of limited in-person interactions on students’ emotional well-being, ensuring fair access to technology resources, and recognizing the potential long-term effects on students’ educational paths and future prospects.

Check for common mistakes

Use the best grammar checker available to check for common mistakes in your text.

Fix mistakes for free

Once you’ve written your essay, you can prompt ChatGPT to provide feedback and recommend improvements.

You can indicate how the tool should provide feedback (e.g., “Act like a university professor examining papers”) and include the specific points you want to receive feedback on (e.g., consistency of tone, clarity of argument, appropriateness of evidence).

While this is not an adequate substitute for an experienced academic supervisor, it can help you with quick preliminary feedback.

You can also use ChatGPT to check grammar mistakes. However, ChatGPT sometimes misses errors and on rare occasions may even introduce new grammatical mistakes. We suggest using a tool like Scribbr’s free grammar checker , which is designed specifically for this purpose. Or, for more in-depth feedback, try Scribbr’s proofreading and editing service .

Example: Using ChatGPT for feedback

Feedback the above text with regard to consistency of tone, clarity of argument, appropriateness of evidence, and coherence of structure.
Clarity of Argument: The argument could be further clarified by explicitly connecting the discussed factors to their impact on academic performance. For example, explicitly stating how the proficiency of virtual platforms and equitable access to technology affect academic performance would strengthen the clarity of the argument.
Appropriateness of Evidence: The evidence provided is generally appropriate and relevant. To enhance the strength of the evidence, consider incorporating specific examples, research studies, or statistics that directly support the discussed factors and their impact on academic performance. This would provide stronger evidence for the claims made.
Coherence of Structure: The structure of the text is coherent, with a clear introduction, body paragraphs addressing different factors, and a conclusion. To improve coherence, consider adding transitional phrases or sentences at the beginning or end of paragraphs to facilitate the smooth flow of ideas between paragraphs. This would enhance the overall structure and make it easier for the reader to follow the argument.

Overall, the text demonstrates a consistent tone, a clear argument, appropriate evidence, and a coherent structure. Clarifying the argument by explicitly connecting the factors to their impact, incorporating stronger evidence, and adding transitional phrases for better coherence would further enhance the text’s effectiveness. Note Passing off AI-generated text as your own work is generally considered plagiarism (or at least academic dishonesty ) and may result in an automatic fail and other negative consequences . An AI detector may be used to detect this offense.

If you want more tips on using AI tools , understanding plagiarism , and citing sources , make sure to check out some of our other articles with explanations, examples, and formats.

Citing ChatGPT
Best grammar checker
Best paraphrasing tool
ChatGPT in your studies
Is ChatGPT trustworthy?
Types of plagiarism
Self-plagiarism
Avoiding plagiarism
Academic integrity
Best plagiarism checker

Citing sources

Citation styles
In-text citation
Citation examples
Annotated bibliography

Yes, you can use ChatGPT to summarize text . This can help you understand complex information more easily, summarize the central argument of your own paper, or clarify your research question.

You can also use Scribbr’s free text summarizer , which is designed specifically for this purpose.

Yes, you can use ChatGPT to paraphrase text to help you express your ideas more clearly, explore different ways of phrasing your arguments, and avoid repetition.

However, it’s not specifically designed for this purpose. We recommend using a specialized tool like Scribbr’s free paraphrasing tool , which will provide a smoother user experience.

No, it’s not a good idea to do so in general—first, because it’s normally considered plagiarism or academic dishonesty to represent someone else’s work as your own (even if that “someone” is an AI language model). Even if you cite ChatGPT , you’ll still be penalized unless this is specifically allowed by your university . Institutions may use AI detectors to enforce these rules.

Second, ChatGPT can recombine existing texts, but it cannot really generate new knowledge. And it lacks specialist knowledge of academic topics. Therefore, it is not possible to obtain original research results, and the text produced may contain factual errors.

However, you can usually still use ChatGPT for assignments in other ways, as a source of inspiration and feedback.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Driessen, K. (2023, November 16). How to Write an Essay with ChatGPT | Tips & Examples. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/ai-tools/chatgpt-essay/

Is this article helpful?

Koen Driessen

Other students also liked, how to write good chatgpt prompts, how to use chatgpt in your studies, what are the limitations of chatgpt, get unlimited documents corrected.

✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

'ZDNET Recommends': What exactly does it mean?

ZDNET's recommendations are based on many hours of testing, research, and comparison shopping. We gather data from the best available sources, including vendor and retailer listings as well as other relevant and independent reviews sites. And we pore over customer reviews to find out what matters to real people who already own and use the products and services we’re assessing.

When you click through from our site to a retailer and buy a product or service, we may earn affiliate commissions. This helps support our work, but does not affect what we cover or how, and it does not affect the price you pay. Neither ZDNET nor the author are compensated for these independent reviews. Indeed, we follow strict guidelines that ensure our editorial content is never influenced by advertisers.

ZDNET's editorial team writes on behalf of you, our reader. Our goal is to deliver the most accurate information and the most knowledgeable advice possible in order to help you make smarter buying decisions on tech gear and a wide array of products and services. Our editors thoroughly review and fact-check every article to ensure that our content meets the highest standards. If we have made an error or published misleading information, we will correct or clarify the article. If you see inaccuracies in our content, please report the mistake via this form .

5 ways ChatGPT can help you write an essay

ChatGPT is capable of doing many different things very well. One of the biggest standout features is its ability to compose all sorts of text within seconds, including songs, poems, bedtime stories, and essays .

The chatbot's writing abilities are not only fun to experiment with but can help provide assistance with everyday tasks. Whether you are a student, a working professional, or just trying to get stuff done, we constantly take time to compose emails, texts, reports, and more. ChatGPT can help you claim some of that time back by helping you brainstorm and even compose any text you need.

How to use ChatGPT to write: Code | Excel formulas | Resumes | Cover letters

Contrary to popular belief, ChatGPT can do much more than write an essay for you from scratch (which would be considered plagiarism). A more useful way to use the chatbot is to have it guide your writing process.

Below, we show you how to use ChatGPT for both writing and assisting and include some other helpful writing tips.

How ChatGPT can help you write an essay

If you are looking to use ChatGPT to support or replace your writing, here are five different techniques to explore.

It is also worth noting before you get started that other AI chatbots can output the same results as ChatGPT or are even better, depending on your needs. For example, Copilot , Perplexity , and Gemini also have access to the internet and include footnotes linking back to the original source for all of their responses, making the chatbots solid alternatives if you rather skip out on ChatGPT.

Also: The best AI chatbots of 2024: ChatGPT and alternatives

Regardless of which AI chatbot you pick, you can use the tips below to get the most out of your prompts and AI assistance.

1. Use ChatGPT to generate essay ideas

Before you start writing an essay, you need to flesh out the idea. When professors assign essays, they generally give students a prompt that gives them leeway for their own self-expression and analysis.

As a result, students have the task of finding the angle to approach the essay on their own. If you have written an essay recently, you know that finding the angle is often the trickiest part -- and this is where ChatGPT can help.

Also: How do AI checkers actually work?

All you need to do is input the assignment topic, include as much detail as you'd like -- such as what you're thinking about covering -- and let ChatGPT do the rest. For example, based on a paper prompt I had in college, I asked:

Can you help me come up with a topic idea for this assignment, "You will write a research paper or case study on a leadership topic of your choice." I would like it to include Blake and Mouton's Managerial Leadership Grid and possibly a historical figure.

Within seconds, the chatbot produced a response that provided me with the title of the essay, options of historical figures on which to focus my article, insight into what information I could include in my paper, and specific examples of a case study I could use.

2. Use the chatbot to create an outline

Once you have a solid topic, it's time to start brainstorming what you actually want to include in the essay. To facilitate the writing process, I always create an outline, including all the different points I want to touch upon in my essay. However, the outline-writing process is usually tedious.

With ChatGPT, all you have to do is ask it to write the outline for you.

Using the topic that ChatGPT helped me generate in step one, I asked the chatbot to write me an outline by saying:

Can you create an outline for a paper, "Examining the Leadership Style of Abraham Lincoln through Blake and Mouton's Managerial Leadership Grid."

Also: How my 4 favorite AI tools help me get more done at work

After a few seconds, the chatbot produced a holistic outline divided into seven sections, with three points under each section.

This outline is thorough and can be condensed for a shorter essay or elaborated on for a longer paper. If you don't like something or want to tweak the outline further, you can do so either manually or with more instructions to ChatGPT.

If you want ChatGPT to include links and sources throughout, you can ask it to and it will regenerate the answer using its web-browsing feature , further expediting your essay-writing process.

3. Use ChatGPT to find sources

Now that you know exactly what you want to write, it's time to find reputable sources for your information. If you don't know where to start, you can ask ChatGPT.

All you need to do is ask the AI to find sources for your essay topic. The biggest thing to remember is to include the type of source you want, whether it be web pages, books, PDFs, research, papers, etc.

Also: How to make ChatGPT provide sources and citations

The specifics are necessary because when you specify web pages, ChatGPT will activate the web browsing feature and include web links in its article. If you use a very general prompt, however, it will likely default to generating its answer from its database, which isn't up to date.

For example, I asked the following:

"Examining the Leadership Style of Abraham Lincoln through Blake and Mouton's Managerial Leadership Grid."

The chatbot outputs links, accessible right at the top of the answer under the drop-down that says "Searched # of sites." Then, within the response, it will answer your prompt conversationally, also including sources with site names and links in parathesis.

4. Use ChatGPT to write an essay

It is worth noting that if you take the text directly from the chatbot and submit it, your work could be considered plagiarism since it is not your original work. As with any information taken from another source, text generated by an AI should be identified and credited to the chatbot in your work.

In most educational institutions, the penalties for plagiarism are severe, ranging from a failing grade to expulsion from the school. A better use of ChatGPT's writing features would be to create a sample essay to guide your writing.

Also: ChatGPT vs. Microsoft Copilot vs. Gemini: Which is the best AI chatbot?

If you still want ChatGPT to create an essay from scratch, enter the topic and the desired length. For example, I input the following text:

Can you write a five-paragraph essay on the topic, "Examining the Leadership Style of Abraham Lincoln through Blake and Mouton's Managerial Leadership Grid."

Within seconds, the chatbot gave the exact output I required: a coherent, five-paragraph essay on the topic. You could then use that text to guide your own writing.

At this point, it's worth remembering how tools like ChatGPT work : they put words together in a form that they think is statistically valid, but they don't know if what they are saying is true or accurate.

As a result, the output you receive might include invented facts, details, or other oddities. The output might be a useful starting point for your own work but don't expect it to be entirely accurate, and always double-check the content.

5. Use ChatGPT to co-edit your essay

Once you've written your own essay, you can use ChatGPT's advanced writing capabilities to edit the piece for you.

You can simply tell the chatbot what you want it to edit. For example, I asked ChatGPT to edit our five-paragraph essay for structure and grammar, but other options could have included flow, tone, and more.

Also: How to use ChatGPT to make charts and tables

Once you ask the tool to edit your essay, it will prompt you to paste your text into the chatbot. ChatGPT will then output your essay with corrections made. This feature is particularly useful because ChatGPT edits your essay more thoroughly than a basic proofreading tool, as it goes beyond simply checking spelling.

You can also co-edit with the chatbot, asking it to review a specific paragraph or sentence and rewrite or fix the text for clarity. Personally, I find this feature very helpful.

Stuck in a rut at work? Here are 5 great ways to kickstart your career

How to use chatgpt to analyze pdfs (and more) for free, how to use chatgpt to write your resume.

Learn How to Write in French Easily

Everything About
The alphabet
Funny phrases
Common words
Untranslateable Words
Reading Hacks
Writing Tips
Pronunciation
Telling time
Learn FASTER
More resources

By OptiLingo • 9 minute read

Improve Your Written French Today

Whether you want to pen a love letter or submit an essay in France, you need to know how to write in French. Luckily, learning how to write in French is fairly straightforward. Since French uses the Latin Alphabet, you’re already ahead of the game. Improve your writing in French fast with these easy steps.

The Basics of French Writing for Beginners

When it comes to French writing, it’s a little different than speaking French. But, if you know how to read French well, you shouldn’t have a lot of problems.

Before you read the 8 easy steps of learning to write in French, there’s one important factor in mastering French writing: practice. The only way you can truly improve your French writing skills is with a lot of practice . Make sure you write a little bit in French every day. Soon, you’ll find that writing in French is like second nature.

1. Watch Out for French Spelling

One of the biggest obstacles that throws French learners off is spelling. Unfortunately, those silent letters that you don’t pronounce are very much there in writing. Be careful how you spell certain complicated words. You need to master all parts of French grammar to write French correctly.

2. Genders Influence Grammar in French

You may already know that nouns have genders in French. They can either be masculine or feminine. And depending on the gender, different parts of a French sentence need to be conjugated.

articles : French articles need to be conjugated to reflect the gender and the number of the noun. These can be ‘le’, ‘la’, ‘l”, and ‘les’ for definite articles, and ‘un’ and ‘une’ for indefinite articles.
pronouns : Pronouns in French are the words that replace the name of the subject in a sentence. ‘He’, ‘she’, and ‘them’ are some examples of pronouns in English. In French, you need to use different forms of pronouns depending on the gender of the subject.
adjectives : When you’re describing a noun, you use an adjective. And since the noun is the only reason the adjective’s there in the sentence, you need to make the adjective fit the noun in French. There are various ways to conjugate French adjectives depending on the gender and the number of the noun, so make sure you brush up on that knowledge before you write in French.

French writing has a lot of conjugations from genders

3. Careful with French Accent Marks

French accent marks also don’t do us any favors. While they’re extremely useful when it comes to French pronunciation, their writing isn’t as straightforward. Try to associate the sound with the written French word. There are only 5 accent marks in French. One is the cedilla (ç), which only works with the letter “c”, and another is the acute accent (é), which only sits on top of the letter “e”. So in practice, there are only 3 different kinds of accents you should look out for in French.

4. Follow the French Sentence Structures

English and French sentence structures are similar in many ways. Both follow the SVO (subject-verb-object) structure, which makes writing in French much easier. And just like in English, the French sentence structure is also flexible. You can switch the words around to emphasize a part of a sentence, but still have the same meaning.

Tomorrow , I’m going to work. Demain je vais travailler. I’m going to work tomorrow . Je vais travailler demain .

The most important part of the first sentence is the time the speaker goes to work. The second sentence focuses on the subject, the speaker instead. Still, both sentences convey the same meaning of going to work.

If you want to ask a question in French, you can do so by putting a question word at the beginning of the sentence. Common question words are:

How Comment
What Que / Qu’est-ce que queue
What kind Quel genre
When Quand
Why Pourquoi

You can also ask a question by switching the order of the verb and the pronoun around, and connecting them with a hyphen:

Do you speak English? Parlez-vous anglais ?

It’s important to remember these basic rules of French sentence structure before you start writing in French. If you want to learn how to write in French effectively, practice these 4 steps a lot.

Psst! Did you know we have a language learning app?

It teaches you useful words and phrases.
Presented in a natural, everyday context.
Spaced out over time, so you absorb your new language organically.
It’s kind of like learning the words to your new favorite song!

You’re only one click away!

How to Write in French for Intermediate Students

If you’re an intermediate French learner you’re familiar with basic French grammar, and you’re confident in writing in French. But, there’s always room to improve. Once you know the basic steps of how to write in French, it’s time to make your writing even better. You can start paying attention to style, flow, and structure. The tips below will benefit your French writing practice.

5. Try Nominalization

This useful technique will make your sentences better. Nominalization means that you make nouns in the sentence more dominant. While in English, the dominant words are verbs, in French, you can write with the focus of the noun instead, making them more meaningful. Here’s an example to demonstrate.

Normal sentence: The ice cream is cold. – La glace est froide.
Nominalized sentence: The ice cream is cold. – La glace, c’est droid.

6. Use French Conjunctions

Conjunctions are the tools to write complex French sentences. Without them, you’re limited to simple and boring sentence structures. As an intermediate student, you can start connecting two equal or unequal sentences to make an even more interesting phrase. Here are the different kinds of French conjunctions you can use to write better in French:

Coordinating Conjunctions:

You use these kinds of conjunctions to connect two equal sentences. The most common coordinating conjunctions in French are:

Subordinating Conjunctions:

If one of the sentences in unequal or dependent on the other, you need to use subordinating conjunctions. These connectors often show causality. The most common conjunctions in French for this category are:

7. Style and Flow

Now that you wield the power of conjunctions, you have to be careful with it. As fun as it is to write long and complicated sentences in French, it doesn’t sound good. Make sure you use appropriate sentence lengths as you’re writing in French.

Aim for shorter sentences. Make them explain your point well. But, feel free to mix the flow up with the occasional longer sentences. That’s how you write in French with a nice and smooth flow. And that’s how you perfect your French writing too. It will be a pleasure to read your work.

Writing in French for Advanced Learners

Once you mastered all of the French writing rules, you’re officially an advanced French learner. But, there may still be room to improve your French writing. If you’re looking to kick your projects up a notch, you can learn how to write essays and dissertations in French. These pointers will be useful if you ever attend school or university in France, or you want to take a language exam.

8. Get Familiar with French Essay Structure

When you’re writing an essay, you have to structure it for readability. If you want to learn how French high schoolers are taught to write their essays, this is the structure they follow: thèse-antithèse-synthèse (thesis-antithesis-synthesis). Learn how to write French essays using a traditional French essay structure.

Introduction : You begin your essay by having an introduction, which is a context for argument.
Thesis : In this section, you present and defend the statement of your thesis. You need to write everything that supports the topic of your essay.
Antithesis : The antithesis follows the thesis. This is where you state conflicting evidence and explain other potential substitutes for your essay. Including an antithesis doesn’t mean that you disagree with your original thesis. You just need to show that you thought of all possibilities before arriving to your conclusion.
Synthesis : This is your conclusion. This is where you summarize your arguments, and explain why you still stand by your original thesis despite the antithesis.

Advanced French learners can always improve their writing skills

9. Use Introduction and Conclusion Vocabulary

Certain words can encourage sentence flow by introducing or concluding some parts of your work.

tout d’abord (firstly)
premièrement (firstly)
deuxièmement (secondly)
ensuite (then)
enfin (finally)
finalement (finally)
pour conclure (to conclude)

You can use these words when introducing a new idea to your dissertation or essay. These words will signal the readers that they are encountering a new part or thought of your writing process.

10. Writing a Dissertation in French

This is the form of writing you encounter in French higher education. It’s a very complex form of French writing, only the most advanced and fluent French learners should attempt it. It’s also a longer piece of academic writing. It may take you weeks to complete research and write your French dissertation.

The French dissertation is similar to essay structure. But, there’s one main difference: your thesis isn’t a statement, but rather a question. It’s your job in the dissertation to take the reader through your thought process and research to answer your question. This logic is known as “ Cartesian logic .” It comes from Descartes , who was a well known French philosopher.

History of Written French

French was used in Strasbourg Oaths, and it first appeared in writing in 842 AD. Before then, Latin was the only language used for literature in Europe. However, in the 10th and 11th centuries, French appeared in some religious writings and documents but was not used up to the late 12th century or early 13th century. The first greatest French Literature work, the Song of Roland (Chanson de Roland), was published around the year 1200.

Writing in French Alone Won’t Make You Fluent

You need to learn how to write in French to be proficient in the language. But, it won’t make you fluent. The only way to become fluent is to practice speaking French. While it’s crucial to develop every area of your French knowledge, if you want to be fluent in French, you need a reliable language learning method like OptiLingo.

OptiLingo is an app that gets you speaking, not typing a language. It gives you the most common French words and phrases, so you’re guaranteed to learn the most useful vocabulary. Don’t waste time trying to learn French you’ll never use. Complement your French writing practice with fun speaking exercises when you download OptiLingo !

there are plenty of french words used in english every day

50+ French Words Used in English Today

Top 10 Differences Between French and English

French Possessive Adjectives: Mon, Ton, Son, and More

Everything About French Adjectives

Many people believe they aren’t capable of learning a language. we believe that if you already know one language, there’s no reason you can’t learn another..

COMMENTS

The best French chatbots (and a few to avoid)
Gliglish. Gliglish is an online chatbot that you can access for free for 10 minutes (50 messages) a day. Or you can sign up for the paid version of Gliglish, which features up to 20 hours of conversation a month. Unlike some of the other chatbots on our list, Gliglish is a stand-alone, not part of a learning app.
Top 6 French Chatbots for Language Practice
2. Duolingo. Duolingo is another popular language learning app that also introduced its chatbot feature in 2016. This app provides users with an on-demand way to practice French conversation without the awkwardness. There are several chatbots with different personalities you can talk to about various topics.
9 Ways to Use ChatGPT for Language Learning
Spanish, French, or German ... Using ChatGPT to write a college essay; Using ChatGPT to write an introduction; ... The popular AI-powered chatbot ChatGPT can produce responses in a wide range of different languages, even switching between languages in one conversation. Because of this, it can be a powerful tool to help you with language learning.
I Used ChatGPT To Teach Me French FAST: Here Is What I Learned ...
Write in French: Take some time each day to write in French. You can start by writing short sentences and then gradually build up to longer pieces. 2. Join an online French discussion group: There ...
The Top 3 French Chatbots for Realistic Language Practice
Mondly. This is a well-known French language learning app that launched their chatbot back in 2016. It offers both text chatting and speech recognition so that you can actually talk out loud to the bot. Not only does the French chatbot already understand over a million phrases, it responds with a voice as well.
French AI Chatbot by Lingua Fresca. Practice your French conversationally
Tips. To practice speaking (with French keyboard enabled), use the microphone feature on your mobile device's keyboard. Use Lingua Fresca's French AI chatbot to practice your French conversationally. Type or speak to the chatbot.
5 Chatbots for Practicing Conversational Skills in a Foreign ...
Cost: Free to download, $5.99 a month for premium. Eggbun Education is designed to help beginning language students practice their skills. The artificial intelligence chatbot acts like a tutor. Lanny, as she's called, focuses on providing you with guidance and direction in learning your target language.
Engage with Chat GPT Français: A New Era in AI Technology
Chat GPT Français is a cutting-edge AI technology that opens up a new era of seamless French conversation and transformative linguistic capabilities. Developed by OpenAI, this chatbot has gained global recognition and become a phenomenon since its release in mid-November 2022.With millions of users embracing its functionalities, Chat GPT Français has proven its versatility in various tasks ...
How to Learn with French ChatGPTs AI tool? [Free Guide]
7 Ways to Learn French with ChatGPT. There are several effective ways to use ChatGPT to learn French. Here are some suggestions: Conversational Practice: Engage in conversational practice with ChatGPT to improve your speaking skills. Initiate conversations on various topics, ask questions, and respond to prompts.
How to Write an Essay in French
Before we get to the four main types of essays, here are a few French phrases that will be especially helpful as you delve into essay-writing in French: Introductory phrases, which help you present new ideas. French. English. tout d'abord. firstly. premièrement.
AI-Powered french learning with OpenAI ChatGPT
April 5, 2023. In order to offer a unique and unprecedented learning experience for French as a Foreign Language (FLE), French Lab has integrated artificial intelligence, through ChatGPT, into its FLE chatbot. With a combination of scripts and AI, the French Lab chatbot can offer a pedagogical narrative based on the learner's questioning - thus ...
Using ChatGPT to efficiently write French reading activities
Dictée: Once students have read the ChatGPT stories, you can turn them into a dictée. Practice listening skills as well as reading with the same passages. Scrambled sentences: After the students have read the paragraphs, scramble the sentences and have them put them back in the correct order. Act out the story: Have your students work in ...
Robots vs. Humans: Does ChatGPT Pose a Challenge to Second Language
Reduced workload: Chatbots can help to reduce the workload of teachers by automating the process of providing feedback on writing assignments. Mixed results: However, it is important to note that the effectiveness of chatbots in teaching second language writing may vary, as some students may prefer more traditional methods of instruction and ...
Free AI French Homework Helper
StudyMonkey AI can tutor complex French homework questions, enhance your essay writing and assess your work—all in seconds. No more long all-nighters. 24/7 solutions to French questions you're stumped on and essays you procrastinated on. No more stress and anxiety.
How to Write an Excellent French Essay (Resources Included)
1. L'explication de texte. An explication de texte is a type of essay for which you complete a close reading. It is usually written about a poem or a short passage within a larger work. This close reading will elucidate different themes and stylistic devices within the text. When you are completing an explication de texte, make sure to follow ...
Building a Custom Language Model (LLM) for Chatbots: A ...
Introduction. Building a custom Language Model (LLM) enables us to create powerful and domain-specific chatbots that can provide intelligent responses tailored to our desired context. This article ...
AI bot ChatGPT writes smart essays
The bot is free for now and can produce uncannily natural, well-referenced writing in response to homework questions. ... powered chatbot that creates surprisingly intelligent-sounding text in ...
A large-scale comparison of human-written versus ChatGPT-generated essays
The corpus features essays for 90 topics from Essay Forum 42, an active community for providing writing feedback on different kinds of text and is frequented by high-school students to get ...
How to write an essay in French
First, you will find some useful tips and tricks that will help you write more compelling and better French essays in the future. Have a clear thesis and structure. Do sufficient research and use reliable sources. Use examples and arguments to support your thesis. Avoid plagiarism and cite correctly. Always check structure, grammar and spelling ...
How to Write an Essay with ChatGPT
For example, you can include the writing level (e.g., high school essay, college essay), perspective (e.g., first person) and the type of essay you intend to write (e.g., argumentative, descriptive, expository, or narrative ). You can also mention any facts or viewpoints you've gathered that should be incorporated into the output.
Using chatbots to scaffold EFL students' argumentative writing
Research suggests that English as a foreign language (EFL) students' argumentative writing benefits from interactions with peers. However, finding an ideal partner to interact with can be difficult in practice, and chatbots have been suggested as a potential solution to this problem. Chatbots are a form of artificial intelligence (AI ...
5 ways ChatGPT can help you write an essay
1. Use ChatGPT to generate essay ideas. Before you start writing an essay, you need to flesh out the idea. When professors assign essays, they generally give students a prompt that gives them ...
Learn How to Write in French in 8 Easy Steps
Soon, you'll find that writing in French is like second nature. 1. Watch Out for French Spelling. One of the biggest obstacles that throws French learners off is spelling. Unfortunately, those silent letters that you don't pronounce are very much there in writing. Be careful how you spell certain complicated words.