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Theories of Motivation in Education: an Integrative Framework

• Review Article
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• Published: 30 March 2023
• Volume 35 , article number  45 , ( 2023 )

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• Detlef Urhahne   ORCID: orcid.org/0000-0002-7709-0011 1 &
• Lisette Wijnia   ORCID: orcid.org/0000-0001-7395-839X 2  

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Several major theories have been established in research on motivation in education to describe, explain, and predict the direction, initiation, intensity, and persistence of learning behaviors. The most commonly cited theories of academic motivation include expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory. To gain a deeper understanding of the similarities and differences among these prominent theories, we present an integrative framework based on an action model (Heckhausen & Heckhausen, 2018 ). The basic model is deliberately parsimonious, consisting of six stages of action: the situation, the self, the goal, the action, the outcome, and the consequences. Motivational constructs from each major theory are related to these determinants in the course of action, mainly revealing differences and to a lesser extent commonalities. In the integrative model, learning outcomes represent a typical indicator of goal-directed behavior. Associated recent meta-analyses demonstrate the empirical relationship between the motivational constructs of the six central theories and academic achievement. They provide evidence for the explanatory value of each theory for students’ learning.

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Introduction

Motivation is one of the most studied psychological constructs in educational psychology (Koenka, 2020 ). The term is derived from the Latin word “movere,” which means “to move,” as motivation provides the necessary energy to people’s actions (Eccles et al., 1998 ; T. Jansen et al., 2022 ). In the scientific literature, motivation is often defined as “a process in which goal-directed activity is instigated and sustained” (Schunk et al., 2014 , p. 5). Research on academic motivation focuses on explaining why students behave the way they do and how this affects learning and performance (Schunk et al., 2014 ).

Several major theories have been established in research on motivation in education to describe, explain and predict the direction, initiation, intensity, and persistence of learning behaviors (cf. Linnenbrink-Garcia & Patall, 2016 ). Each theory has its own terms and concepts to designate aspects of motivated behavior, contributing to a certain inaccessibility of the field of motivation theories. In addition, motivation researchers create their own terminology, differentiate, and extend existing theoretical conceptions, making it difficult to draw precise boundaries between the models (Murphy & Alexander, 2000 ; Schunk, 2000 ). This leads to the question of whether it would be possible to consider the most important theories of academic motivation against a common background to gain a deeper understanding of the similarities and differences among these prominent theories.

In the past, several researchers have worked to provide an integrative meta-theoretical framework for classifying motivational processes. Hyland’s ( 1988 ) motivational control theory used a system of hierarchically organized control loops to explain the direction and intensity of goal-orientated behavior. Locke ( 1997 ) postulated an integrated model for theories of work motivation, starting from needs, values and personality, and environmental incentives through goal choice and mediating goal and efficacy mechanisms to performance, outcomes, satisfaction, and organizational commitment. Murphy and Alexander ( 2000 ) classified achievement motivation terms into the four domains of goal, interest, intrinsic vs. extrinsic motivation, and self-schema. De Brabander and Martens ( 2014 ) tried to predict a person’s readiness for action primarily from positive and negative, affective and cognitive valences in their unified model of task-specific motivation. Linnenbrink-Garcia and Wormington ( 2019 ) proposed perceived competence, task values, and achievement goals as essential categories to study person-oriented motivation from an integrative perspective. Hattie et al. ( 2020 ) grouped various models of motivation around the essential components of person factors (subdivided into self, social, and cognitive factors), task attributes, goals, perceived costs, and benefits. Finally, Fong ( 2022 ) developed the motivation within changing culturalized contexts model to account for instructional, social, future-oriented, and sociocultural dynamics affecting student motivation in a pandemic context.

In this contribution, we present an integrative framework for theories of motivation in education based on an action model (Heckhausen & Heckhausen, 2018 ). The action model is a further development of an idea by Urhahne ( 2008 ) to classify the most commonly cited theories focusing on academic motivation, including expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory, into a common frame (Schunk et al., 2014 ). We begin with introducing the basic motivational model and then sort the main concepts and terms of the prominent motivation theories into the action model. Associated recent meta-analyses will illustrate the empirically documented value of each theory in explaining academic achievement.

The Basic Motivational Model

The basic motivational model in Fig. 1 shows the determinants and course of motivated action. The model is grounded on the general model of motivation by Heckhausen and Heckhausen ( 2018 , p. 4) to introduce the universal characteristics of motivated human action. Heckhausen ( 1977 ) had worked early on to organize constructs from different theories into a cognitive model of motivation. The initial model differentiated four types of expectations attached to four different stages in a sequence of events and helped group intrinsic and extrinsic incentive values of an action as well (Heckhausen, 1977 ). Later, Heckhausen and Gollwitzer ( 1987 ) extended the model to the Rubicon model of action phases to define clear boundaries between phases of motivational and volitional mindsets (Achtziger & Gollwitzer, 2018 ; Gollwitzer et al., 1990 ). The four phases of the Rubicon model can be described as follows: In the predecisional phase of motivation, individuals select or set a goal for action on the basis of their wishes and desires. The postdecisional phase of volition is a time of preparation and planning to translate the goal into action. This is followed by the actional phase of volition that involves the actual process of action. Once the action is completed or abandoned, the postactional phase of evaluating the outcome and its consequences has begun (Heckhausen & Heckhausen, 2018 ). Since the Rubicon model depicts the entire action process from an emerging desire to the final evaluation of the action outcome, it provides a broad basis for classifying various current motivational theories.

The basic motivational model

Specifically, our model proposes that motivated behavior arises from the interaction between the person and the environment (Murray, 1938 ). In Fig. 1 , possible incentives such as the prospect of rewards and opportunities of the situation stimulate the motives, needs, wishes, and emotions of a person’s self, which come to life through generating an action goal (Dweck et al., 2003 ; Roeser & Peck, 2009 ). A person’s current goal is translated into an action at a suitable opportunity. The action is carried out, and the action’s outcome indicates whether and to what extent the intended goal has been achieved. The outcome has to be distinguished from the consequences of the action, which may consist of self- and other evaluations, rewards and punishments, achievement emotions, or effects of the outcome on long-term goals (Heckhausen & Heckhausen, 2018 ). The basic model is intentionally parsimonious and somewhat reflects considerations by Hattie et al. ( 2020 ) on integrating theories of motivation that distinguish between self, goals, task (action), and costs and benefits (consequences) as major dimensions of motivation. Similarities also emerge to Locke ( 1997 ), who bases the integrative model of work motivation theories on a comparable action sequence. The specificities of each component of the basic motivational model are now explained in more detail.

The situation represents the social, cultural, and environmental context in which individuals perform motivated actions (Ford, 1992 ). Recently, there has been a trend within motivation research to place greater emphasis on situating motivation (Eccles & Wigfield, 2020 ; Nolen, 2020 ; Nolen et al., 2015 ; Pekrun & Marsh, 2022 ; Wentzel & Skinner, 2022 ). Researchers want to better account for the social and cultural differences between persons (Usher, 2018 ) or take note of the embeddedness of individuals in multiple contexts (Nolen et al., 2015 ). The basic motivational model includes these extensions of current motivation theories and refers to the situatedness of motivation. The situation represents the overarching context for the complete action sequence, even though it is depicted in the basic motivational model by only one box. The situation and the person’s self are intimately interwoven, and motivation can be regarded as a result of their interaction (Roeser & Peck, 2009 ). The situation evokes motivational tendencies in the self, and the self contains experiences about the motivation to avoid or master certain situations (King & McInerney, 2014 ).

The self has not played a major role in motivation research for a long time (Weiner, 1990 ). This was partly due to Freud’s psychoanalytic theories, which recognized the id rather than the ego as the motivational driver of behavior. Moreover, behavioristic approaches that characterized motivation and learning as fully controllable from the outside also neglected mental constructs such as the self (McCombs, 1991 ). It was only with the greater prevalence of cognitive and social-cognitive theories that the self found its way back to motivational research (Weiner, 1990 ). The self is now frequently addressed in hypothetical constructs such as self-efficacy (Bandura, 1977 ), self-determination (Deci & Ryan, 1985 ), self-regulation (Bandura, 1988 ), self-theories (Dweck, 1999 ), ego orientation (Nicholls, 1989 ), self-based goals (Elliot et al., 2011 ), self-serving bias (McAllister, 1996 ; Miller & Ross, 1975 ), and identity (Eccles, 2009 ).

In our model, the self is the starting point of motivated action. It enables people to select goals, initiate behaviors, and sustain them until goals are accomplished (Baumeister, 2010 ; McCombs & Marzano, 1990 ; Osborne & Jones, 2011 ). Thus understood, the self is an active agent that translates a person’s basic psychological needs, motives, feelings, values, and beliefs into volitional actions (McCombs, 1991 ; Roeser & Peck, 2009 ). James ( 1999 ) referred to this part of the self as the “I-self,” the thinking and acting person itself, to distinguish it from the “Me-self,” the reflection of oneself through its physical and mental attributes. The “Me-self” is central to constructs such as self-concept, self-worth, or self-esteem (Harter, 1988 ) and remains important in depicting different motivational constructs in the course of action. However, in the basic motivational model, the “I-self” is recognized as the repository of motivational tendencies and the energizer of motivated action (King & McInerney, 2014 ).

This view of the self corresponds with insights from neuroscientific research. In Northoff’s ( 2016 ) basis model of self-specificity, the self, and in particular self-specificity, is viewed as the most fundamental function of the brain. Self-specificity and self-relatedness refers to “the degree to which internal or external stimuli are related to the self” (Hidi et al., 2019 , p. 15) and references the I-self, the self as subject and agent (Christoff et al., 2011 ). Self-specificity involves spontaneous brain activity—the resting state of the brain and independent of specific tasks or stimuli external to the brain—and is viewed as fundamental in influencing basic and higher-order functions, such as perception, the processing of reward, emotion, memory, and decision-making (Hidi et al., 2019 ; Northoff, 2016 ). Furthermore, Sui and Humphreys ( 2015 ) indicated that self-related information processing functions as an “integrative glue” that influences the integration of different stages of processing, such as linking attention to decision-making. Neuroscientific findings, therefore, seem to support the view of the self as the starting point of motivated behavior.

The goal contains the cognitive representation of an action’s anticipated incentives and consequences. Goals are the basis of all motivated behavior (cf. Elliot & Fryer, 2008 ). This view is consistent with Schunk et al. ( 2014 ), who defined motivation as a process to instigate and sustain goal-directed behavior. Cognitive theories on motivation place special emphasis on the goals that people pursue (Elliot & Hulleman, 2017 ). Goals are intentional rather than impulsive, consciously or unconsciously represented, and guide an individual’s behavior. People are not always aware of the various influences on their goals. Sensations, perceptions, thoughts, beliefs, and emotions that affect goal pursuit are potentially experiential, but typically not consciously perceived (Bargh & Gollwitzer, 2023 ; Dweck et al., 2023 ). Goals are closely related to the person’s self. In line with Dweck et al. ( 2003 , p. 239), we assume that “contents of the self—self-defining beliefs and values—come to life through people’s goals.”

The action is carried out to either approach or avoid an anticipatory goal state (Beckmann & Heckhausen, 2018 ). Thus, motivated behavior can be directed to either approach a positive event or avoid a negative one (Elliot & Covington, 2001 ). An action can be brief or extended over a longer period. If an action goal is considered unattainable, it is devalued, and the action is directed toward other more attractive goals (Heckhausen & Heckhausen, 2018 ). The action may or may not be visible to an observer. Thus, to act is to engage in any form of noticeable or indiscernible behavior, especially cognitive behavior, to reach a desired or avoid an undesired goal state.

The outcome is any physical, affective, or social result of an individual’s behavior. The action outcome is an important indicator of mastering a standard of excellence (Heckhausen, 1991 ). It is often accompanied by intrinsic valences such as feelings of self-worth, self-actualization, or appropriate accomplishment (Mitchell & Albright, 1972 ).

The consequences of an action are far more varied than the mere outcome. Vroom’s ( 1964 ) instrumentality theory considered the outcome of an action as instrumental for reaching subsequent consequences. Vroom ( 1964 ) suggested that the valence of an outcome depends on the valence of the consequences. For example, the value of school grades should depend on how the students themselves, classmates, and parents evaluate the grades achieved, what rewards, punishments, and achievement emotions are associated with the school grades, and whether the grades help achieve long-term goals such as moving up to the next grade level. The consequences of an action are often accompanied by extrinsic valences such as authority, prestige, security, promotion, or recognition (Mitchell & Albright, 1972 ).

In addition, the manifold consequences of an action affect the design of future situations and the goals that can be pursued within these situations. New possibilities to act open up and novel incentives of the situation start to interact with the self. A new action sequence, as shown in Fig. 1 , has begun.

In the following sections, we will use the action model to explain and classify six central motivation theories. Motivated action in the educational context serves to attain academic achievement, and we will make use of meta-analyses to underline what is currently known about the predictive strength of the major theoretical models. Academic achievement is certainly not the only reportable variable related to motivation. However, this visible evidence of learning is an appropriate indicator to convince individuals of the theory’s nature and value (Hattie, 2009 ). The role of affective factors in the action model is explained in more detail in the discussion.

Expectancy-Value Theory

Grounded on the research by Tolman ( 1932 ) and Lewin ( 1951 ), expectancy-value theories depict motivation as the result of the feasibility and desirability of an anticipated action (Achtziger & Gollwitzer, 2018 ; Schnettler et al., 2020 ). The expectancy is usually triggered by the incentives of the situation and expresses the subjective probability of the feasibility of the current action (Atkinson, 1957 ). The value indicates the desirability of an action which is determined by the incentives of the situation and the anticipated consequences of the action. In Atkinson’s ( 1957 ) achievement motivation theory, expectancy and value were assumed to be inversely related. The greater the desirability, the more difficult the feasibility of an action and vice versa. Thus, knowing the subjective probability of success was regarded as sufficient to determine the incentive value of a task. However, it turned out that the assumption of a negative correlation between expectancy and value was not tenable (Wigfield & Eccles, 1992 ). In a more modern view, expectancy and value beliefs are assumed to jointly predict achievement-related choices and performance (Eccles et al., 1983 ; Trautwein et al., 2012 ).

Situated expectancy-value theory (Eccles & Wigfield, 2020 ; Wigfield & Eccles, 2000 ) is a modern theoretical framework for explaining and predicting achievement-related choices and behavior. Expectancy of success and subjective task values are regarded as proximal explanatory factors determined by a person’s goals and self-schemas. These, in turn, are shaped by the individual’s perception and interpretation of their developmental history and sociocultural background. Eccles and Wigfield ( 2020 ) refer to their theory as situated to highlight the importance of the underlying influences on currently held expectancy and value beliefs.

The expectancy component in the situated model (Eccles & Wigfield, 2020 ) is called expectation of success (Atkinson, 1957 ; Tolman, 1932 ). It represents individuals’ belief about how well they will do on an upcoming task, targeting the anticipated outcome of an action. The expectancy component of Eccles’ motivation theory shows some similarity to self-concept of ability and self-efficacy (Bandura, 1977 ; Harter, 2015 ; Schunk & DiBenedetto, 2016 ; Schunk & Pajares, 2009 ). However, the expectation of success does not focus on the present ability (Bong & Skaalvik, 2003 ) but the future (Wigfield & Eccles, 2000 ), and it targets the perceived chances of success rather than the perceived probability of performing an action which may lead to success (Bandura, 1977 ; Muenks et al., 2018 ).

The value component of the situated model is divided into three types of value beliefs and three types of costs that contribute to approaching or avoiding certain tasks (Eccles & Wigfield, 2020 ). The three value beliefs are attainment value, intrinsic value, and utility value. The three types of costs are named opportunity costs, effort costs, and emotional costs (cf. Flake et al., 2015 ; Jiang et al., 2018 ).

Attainment value represents the importance of doing well on a task (Eccles & Wigfield, 2020 ). This belief is strongly associated with the person’s self, as aspects of one’s identity are touched upon during performing an important task (Wigfield et al., 2016 ). Intrinsic value is the enjoyment a person gets from doing a task. Intrinsic value is considered a counterpart to intrinsic motivation in self-determination theory (Ryan & Deci, 2009 ) and interest in person-object theory (Krapp, 1999 ). However, enjoyment and interest should not be viewed as synonyms, making differentiations necessary (Ainley & Hidi, 2014 ; Reeve, 1989 ). Utility value is derived from the meaning of a task in achieving current and future goals (Wigfield et al., 2006 ). Accomplishing the task is only a means to an end; therefore, utility value can be considered a form of extrinsic motivation. Utility value is derived from the meaning of a task in achieving current and future goals (Wigfield et al., 2006 ) in social, educational, professional, or everyday contexts (Gaspard et al., 2015 ).

Opportunity costs arise because the time invested in a task is no longer available for other valued activities. Especially in the case of learning, conflicts with other interests threaten learners’ self-regulation, and opportunity costs can be high (Grund & Fries, 2012 ). Effort costs address the perceived effort in pursuing a task and whether it is worthwhile to finish the task at hand (Eccles, 2005 ). Emotional costs include the perceived affective consequences of participating in an academic activity, such as fear of failure or other negative emotional states (Eccles & Wigfield, 2020 ; Wigfield et al., 2017 ).

Central constructs of the situated expectancy-value framework (Eccles & Wigfield, 2020 ) can be placed within the basic motivational model (see Fig. 2 ). Expectation of success, a person’s subjective estimate of the chances of obtaining a particular outcome, can be represented as a directed link between self and outcome. The expectation of achieving a future outcome with a certain probability is formed in the self and is directed on the desired outcome of the prospective action. This view of expectancy of success is consistent with Skinner’s ( 1996 ) classification of agent-ends relations as individuals’ beliefs about how well they will do on an upcoming task.

Integrating situated expectancy-value theory into the basic motivational model

Figure 2 further shows that the three task values are linked to different processes in the action model. The attainment value of a task is related to the personal significance of the outcome (Eccles & Wigfield, 2020 ). The higher the relative personal importance of the outcome, the higher the attainment value. More recent analyses show that the attainment value can be divided and measured as the importance of achievement and personal importance related to one’s identity (Gaspard et al., 2015 , 2018 , 2020 ). The self, however, is not the valued object but the importance of accomplishing a task to an individual’s identity (Perez et al., 2014 ). In classifying this construct, we chose to focus more on the importance of the outcome and less on the reference to the self. At this point, however, a different mode of presentation is also conceivable. The intrinsic value of the task is linked to the positive aspects of the action. The more pleasurable the action, the higher the intrinsic value. Eccles and Wigfield ( 2020 ) conceptualized the intrinsic value as the anticipated enjoyment of doing a particular task as well as the experienced enjoyment when performing the task. The utility value of a task is linked to the consequences. The more positive the anticipated consequences of an action, the higher the perceived usefulness. As a form of extrinsic motivation, the utility value does not result from performing the task, but from the anticipated consequences of an action to fulfill an individual’s present or future plans (Eccles & Wigfield, 2020 ).

The three types of costs also become relevant at different stages in the action process (see Fig. 2 ). Opportunity costs occur when a decision has been made in favor of a certain action. Alternative courses of action are ruled out as soon as a person is committed to a goal (Locke et al., 1988 ). Opportunity costs are consequently linked to the goal of the action. The person’s time and skills, which from now on are put into the pursuit of intentions, are no longer available for other activities (Eccles & Wigfield, 2020 ). Effort costs are tied to the action itself and are based on the anticipated effort of conducting the task. Effort costs rise with the duration and intensity of an action so that the person needs to anticipate whether the desired action is worth the effort required (Eccles & Wigfield, 2020 ). Finally, emotional costs such as anticipated fear of failure or negative emotional states are connected to the anticipated consequences of an action. These costs arise when the action does not go as desired and are therefore considered as the “perceptions of the negative emotional or psychological consequences in pursuing a task” (Rosenzweig et al., 2019 , p. 622).

Eccles’ expectancy-value framework has often been used to investigate and understand gender differences in motivational beliefs, performance, and career choices, especially in science, technology, engineering, and mathematics (Lesperance et al., 2022 ; Parker et al., 2020 ; Wan et al., 2021 ). In contrast, there has been less meta-analytic research as to whether constructs of the expectancy-value model can predict academic achievement. To not preempt other theoretical conceptions, we only report here findings with a clear relation to the Eccles model.

Generally, expectations of success compared to achievement values are stronger predictors of subsequent performance (cf. Wigfield et al., 2017 ). A meta-analysis by Pinquart and Ebeling ( 2020 ) found a moderate association of expectancies for success with both current ( r = .34) and future academic achievement ( r = .41). Conversely, however, past academic performance could also predict expectancies for success ( r = .35). Credé and Phillips ( 2011 ) reported small relationships for a combination of the three task values with GPA ( r = .12) and grades ( r = .17). The relations in meta-analyses were somewhat higher when individual task values were examined. Camacho-Morles et al. ( 2021 ) found an association of r = .27 between activity-related enjoyment represented in the intrinsic value and academic performance. Barroso et al. ( 2021 ) reported a meta-analytic relationship of r = − .28 between math anxiety, as a form of emotional costs, and mathematics achievement.

Social Cognitive Theory

Within the frame of social cognitive theory, Bandura ( 1977 , 1986 , 1997 ) extended the expectancy concept from achievement motivation theory (Atkinson, 1957 ). Expectancy of success, the subjective probability of attaining a particular outcome, was differentiated by means of two beliefs (Schunk & Zimmerman, 2006 ; Usher, 2016 ). Competence beliefs take effect when learners consider means and processes to accomplish certain tasks (Skinner, 1996 ). Control beliefs signify the perceived extent to which the chosen means and processes lead to the desired outcomes (Schunk & Zimmerman, 2006 ).

For competence beliefs, Bandura ( 1977 ) coined the term self-efficacy to express expectations about one’s capabilities to organize and execute courses of action to produce specific outcomes (Bandura, 1997 ; Schunk & Zimmerman, 2006 ). The belief in self-efficacy is regarded as an essential condition to initiate actions leading to academic success (Klassen & Usher, 2010 ). For control beliefs, Bandura ( 1977 ) used the term outcome expectations to express the perceived relations between possible actions and anticipated outcomes. While expectancy of success sometimes involves competence beliefs, sometimes control beliefs, and sometimes both (Schunk & Zimmerman, 2006 ), Bandura’s construct of self-efficacy has contributed to a necessary differentiation in the course of action and can be viewed as a central variable in research on motivation in education (Schunk & DiBenedetto, 2016 ).

Social cognitive theory is much broader than self-efficacy and outcome expectations and assumes a system of interacting personal, behavioral, and environmental factors (Schunk & diBenedetto, 2021 ). The idea that human agency is neither completely autonomous nor completely mechanical, but is subject to reciprocal determinism, plays a decisive role (Linnenbrink-Garcia & Patall, 2016 ). Thus, personal factors such as perceived self-efficacy enable individuals to initiate and sustain behaviors that translate to effects on the environment. Thoughtful reflection on those actions and their impact feeds back to the person and can, in turn, influence their sense of self-efficacy (Bandura, 1989 ).

Figure 3 shows how the key components of social cognitive theory fit into the action model. The upper part of Fig. 3 is devoted to expectations. Self-efficacy expectations arise when the self has the necessary capabilities to organize and execute courses of action. Outcome expectations, in contrast, refer to the assessment of whether the anticipated action will lead to the desired outcome. The presentation of the two expectations is consistent with Skinner’s ( 1996 ) view in which self-efficacy expectations are referred to as agent-means relations and outcome expectations are referred to as means-ends relations. The lower part of Fig. 3 depicts the model of reciprocal interactions consisting of personal, behavioral, and environmental processes (Schunk & DiBenedetto, 2020 ). Personal processes, as described by Schunk and DiBenedetto ( 2020 ) in a publication on motivation and social cognitive theory, are primarily associated with the self and the goal. The self contains information on self-efficacy, values, expectations, attribution patterns and enables social comparison processes. The goal contains standards for self-evaluations of the action’s progress. Behavioral processes such as activity selection, effort, persistence, regulation, and achievement are closely related to action and outcome of the action model. Environmental processes such as acting of social models, providing instructions, or setting standards for action stem, on the one hand, from the situation, where they set the stage for action. Environmental processes are, on the other hand, located in the consequences, where feedback, opportunities for self-evaluation, and rewards indicate an action’s success or failure (Schunk & DiBenedetto, 2020 ). The listing of the individual components that make up the three interacting processes in reciprocal determinism is not always done in the same way. For example, Schunk and DiBenedetto ( 2021 ) referred to self-efficacy, cognitions, and emotions as personal factors; classroom attendance and task completion as behavioral factors; and classroom, teachers, peers, and classroom climate as environmental factors. However, this does not affect the representation of the three main classes of reciprocal determinism in the basic motivational model and opens up space for the classification of different components.

Integrating social cognitive theory into the basic motivational model

Several meta-analyses have shown that self-efficacy is moderately positively related to academic achievement (Multon et al., 1991 ; Robbins et al., 2004 ). Credé and Phillips ( 2011 ) examined several constructs of social cognitive theory based on the Motivated Strategies for Learning Questionnaire (Pintrich & De Groot, 1990 ). Control beliefs showed small positive correlations with college GPA ( r = .12) and current semester grades ( r = .14). However, of all the constructs measured, self-efficacy showed the strongest associations with GPA ( r =. 18) and grades ( r = .30). Further meta-analyses with university students supported the significant but moderate relationship between academic self-efficacy and academic achievement with correlation coefficients of r = .31 (Richardson et al., 2012 ) and r = .33 (Honicke & Broadbent, 2016 ). Sitzmann and Ely ( 2011 ) reported meta-analytic correlations of r = .18 for pre-training self-efficacy and r = .29 for self-efficacy with learning.

To further clarify the direction of the relationship, Sitzmann and Yeo ( 2013 ) conducted an insightful meta-analysis. They were able to show that self-efficacy expectations are more likely to be a product of past performance ( r = .40) than a driver of future performance ( r = .23). Talsma et al. ( 2018 ) supported these findings with a meta-analytic cross-lagged panel study. They found that prior performance exerted a stronger effect on self-efficacy (β = .21) than existing self-efficacy on subsequent performance (β = .07).

Self-Determination Theory

Self-determination theory by Deci and Ryan ( 1985 , 2000 ) is macro-theory for understanding human motivation, personality, and well-being. The theory has its roots in early explorations of the concept of intrinsic motivation (Deci, 1971 , 1975 ; Ryan & Deci, 2019 ). Self-determination is regarded as the basis for explaining intrinsically motivated behavior where the action is experienced as autonomous and does not rely on controls and reinforcers (Deci & Ryan, 1985 ). Self-determination theory provides a counterweight to expectancy-value theory and social cognitive theory, where the external incentives such as expected or real rewards to motivate behavior are still visible.

The overarching framework of self-determination theory encompasses six mini-theories: basic psychological needs theory, cognitive evaluation theory, organismic integration theory, causality orientations theory, goal contents theory, and relationship motivation theory (Ryan & Deci, 2017 ). Each mini-theory explains specific motivational phenomena that have been tested empirically (Reeve, 2012 ; Ryan & Deci, 2017 ; Vansteenkiste et al., 2010 ; see also Ryan et al., in press ). In the following explanations, we focus on the first three sub-theories with the highest popularity.

Basic psychological needs theory argues that humans are intrinsically motivated and experience well-being when their three innate basic psychological needs for autonomy, competence, and relatedness are satisfied (Conesa et al., 2022 ; Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000a , 2000b , 2017 , 2020 ; Vansteenkiste et al., 2020 ). Autonomy refers to a sense of ownership and the need for behavior to emanate from the self. Competence concerns a person’s need to succeed, grow, and feel effective in their goal pursuits (Deci & Ryan, 2000 ; White, 1959 ). Finally, relatedness refers to establishing close emotional connections to others and a sense of belonging to significant others such as parents, teachers, or peers.

Cognitive evaluation theory describes how the social environment affects intrinsic motivation (Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000b , 2017 , 2020 ). The mini-theory states that cognitive evaluation of external rewards impacts learners’ perception of their intrinsically motivated behavior. Rewards perceived as controlling weaken intrinsic motivation, whereas rewards providing informational feedback can strengthen acting on one’s own initiative (Deci et al., 1999 ).

Organismic integration theory focuses on the development of extrinsic motivation toward more autonomous or self-determined motivation through the process of internalization (Ryan & Deci, 2017 ). The mini-theory proposes a self-determination continuum that ranges from intrinsic motivation to amotivation, with several types of extrinsic motivation in between (Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000a , 2000b , 2017 , 2020 ). The results from the meta-analysis by Howard et al. ( 2017 ) largely supported the continuum-like structure of self-determination theory. Intrinsically motivated individuals engage in activities because they are fun or interesting, whereas extrinsic motivation concerns all other reasons for engaging in activities. Four types of extrinsic motivation are distinguished, and two of these types are assumed to be higher in quality than the other two (Deci & Ryan, 2008 ; Ryan & Deci, 2000b ).

Integrated and identified regulations are considered high-quality autonomous, extrinsic motivation types characterized by volitional engagement in activities. Integrated regulation is the most autonomous form of extrinsic motivation. People with integrated regulation recognize and identify with the activity’s value and find it congruent with their core values and interests (e.g., attending school because it is part of who you are; see Ryan & Deci, 2020 ). In identified regulation, people identify with or personally endorse the value of the activity (e.g., doing schoolwork to learn something from it) and, therefore, experience high degrees of volition.

The other two types of extrinsic motivation are forms of controlled motivation (Deci & Ryan, 2008 ; Ryan & Deci, 2000a , 2000b ). Introjected regulation concerns partially internalized extrinsic motivation; people’s behavior is regulated by an internal pressure to feel pride or self-esteem or to avoid feelings of anxiety, shame, or guilt. Extrinsic regulation refers to behavior regulated by externally imposed rewards and punishments, such as demands from parents or teachers.

The action model in Fig. 4 shows how core concepts of the self-determination theory fit into the course of action. The three basic psychological needs for autonomy, competence, and social relatedness are an integral part of the self (Connell & Wellborn, 1991 ). Ryan and Deci ( 2019 ) regarded the self as responsible for assimilating and aligning a person’s internal needs, drives, and emotions to the external determinants of the sociocultural situation. Intrinsic motivation is part of the action when the activity itself is experienced as exciting, interesting, or intrinsically satisfying. On the other hand, extrinsic motivation is tied to an action’s consequences, as externally motivated learners seek pleasant consequences and try to avoid unpleasant ones.

Integrating self-determination theory into the basic motivational model

Forms of extrinsic motivation of the organismic integration theory can be distinguished according to the extent to which the action is integrated into the self. The more internalized the motivation, the more it becomes part of a learner’s identity (Ryan & Deci, 2020 ). In external regulation, there is no involvement of the self, as the person’s actions are entirely determined by the incentives of the situation and the action’s consequences (see Fig. 4 ). In introjected regulation, there is already some ego involvement: The self becomes involved with the consequences of one’s action to experience approval from oneself or others (Ryan & Deci, 2000a ). In identified regulation, the individual starts to value an activity consciously, and the self connects with the action. In integrated regulation, a congruence is established between the self and the self-initiated action (Ryan & Deci, 2000a ). Values and needs of the self are in balance with the autonomous and unconflicted action (see Fig. 4 ). As seen in Fig. 4 , identified and integrated regulation share overlap. In line with this presentation, the meta-analysis by Howard et al. ( 2017 ) showed that integrated regulation was hard to distinguish from intrinsic and identified regulation and called for a revision of the theory by either excluding integrated regulation or finding new ways to operationalize and conceptualize the hypothetical construct.

In line with basic psychological needs theory, the Bureau et al. ( 2022 ) meta-analysis confirmed that the satisfaction of basic psychological needs is positively associated with autonomous forms of motivation. Relative weight analysis showed that the need for competence most strongly predicted intrinsic and identified motivation, followed by the needs for autonomy and social relatedness.

Several meta-analyses investigated the association between the different motivation types and academic achievement, and some of these meta-analyses only reported the association between intrinsic motivation and school performance. For example, Cerasoli et al. ( 2014 ) reported a meta-analytic correlation between intrinsic motivation and school performance of ρ = .26, whereas Richardson et al. ( 2012 ) reported a small positive correlation of r = .17 with the GPA at college or university.

Taylor et al. ( 2014 ) and Howard et al. ( 2021 ) investigated the meta-analytic correlations of the different types of motivation with school performance. Concerning the autonomous motivation types, Taylor et al. ( 2014 ) reported positive associations of intrinsic motivation ( d = .27) and identified regulation ( d = .35) with school achievement. Howard et al. ( 2021 ) also found that both identified and intrinsic motivation were equally positively associated with school performance. However, higher associations were found for self-reported (intrinsic ρ = .32, identified ρ = .29) than for objective performance measures (intrinsic ρ = .13, identified ρ = .11).

Concerning the controlled motivation types, Taylor et al. ( 2014 ) reported weak but significant negative associations with academic achievement for introjected ( d = − .12) and external regulation ( d = − .22). In contrast, Howard et al. ( 2021 ) found that introjected and external regulation were not significantly related to self-reported (introjected ρ = .07, external ρ = − .02) or objective school performance (introjected ρ = − .01, external ρ = − .03).

Interest Theory

Interest stems from the Latin word “interesse” and etymologically indicates that there is something in between. Interest connects two entities that would otherwise be separated from each other. Dewey ( 1913 ) viewed interest as an engagement and absorption of the self with an objective subject matter. In today’s person-object theory (Krapp, 2002 ), interest is similarly understood as a relational concept that builds a connection between a person and an object. Objects of interest can be very diverse and may include tangible things, people, topics, abstract ideas, tasks, events but also activities such as sports (Hidi & Renninger, 2006 ). A prerequisite for interest to arise is an object in the real world and a person who has at least rudimentary but often considerable knowledge about this object (Alexander et al., 1994 ; Renninger & Wozniak, 1985 ; Rotgans & Schmidt, 2017 ). Interest is a unique motivational concept (Hidi, 2006 ) that establishes a link between the objective appearance and the subjective representation of an object and triggers actions with the object of interest.

Being in a state of interest is accompanied by certain intrinsic qualities (Krapp, 2002 ). Interest-driven activities need no external incentives or rewards to be initiated and sustained. Interest is a form of intrinsic motivation that is characterized by the three components of affect, knowledge, and value (Hidi & Renninger, 2006 ) and can thereby be distinguished from related constructs such as curiosity (Berlyne, 1960 ; Donnellan et al., 2022 ; Peterson & Hidi, 2019 ) or flow experience (Csikszentmihalyi, 2000 ). The affective component of interest is typically associated with a state of pleasant tension, an optimal level of arousal, and positive feelings in the engagement with the object of interest. The cognitive component shows itself in the epistemic tendency to want to learn about the object of interest (Hidi, 1990 ). The value component becomes evident in the object’s connection to the self through the attribution of personal significance (Schiefele, 1991 ).

The most important distinction in interest theory is between long-lasting individual interest and short-term situational interest (Hidi & Renninger, 2006 ; Rotgans & Schmidt, 2018 ). Individual interest describes a motivational disposition toward a particular domain. It resembles a temporally stable personality trait and is an important goal of education concerning developing subject-specific and vocational interests for life-long learning (Hoff et al., 2018 ). Situational interest arises from the stimulus conditions of the environment, without any individual interest of the person having to be simultaneously present. Situational interest provides favorable motivation for learning and leads to increased short-term attention and enhanced information processing (Hidi, 2006 ). This interested turn of the person to certain topics, tasks, or activities is due to favorable characteristics of environmental stimuli such as novelty, importance, or attractiveness and is considered to be well-studied in research on text comprehension (Schraw et al., 2001 ). The change and maintenance of short-term situational interest to long-term individual interest are explicitly described in the four-phase model of interest development (Hidi & Renninger, 2006 ).

It is important to note that both individual and situational interest can be associated with a psychological state of interest (Ainley, 2017 ; Hidi, 2006 ) that arises when individuals interact with the object of interest. This state can be promoted both by the individual interest that a person brings to the situation and situational interest due to salient environmental cues (Knogler, 2017 ). In this state of interest, the two basic components of interest complement and merge with each other (Krapp, 2002 ; Renninger et al., 1992 ).

Figure 5 shows the classification of the three central constructs of interest theory in the action model. Situational interest is triggered by environmental stimuli (Hidi & Renninger, 2006 ) and is thus associated with the situation. This fleeting and malleable psychological state needs support from others or through instructional design to not disappear right away (Renninger & Hidi, 2019 , 2022a ). Individual interest is a relatively enduring disposition of the person to re-engage particular content over time (Hidi & Renninger, 2006 ) and is thus a fixed characteristic of the self. This psychological predisposition is independent of the concrete content and represented as stored knowledge and stored value with relations to the self (Renninger & Hidi, 2022b ). “The self … may also provide an explanation of why interest, once triggered, is then maintained and continues to develop” (Hidi et al., 2019 , p. 28). The state of interest arises in interaction with the object of interest (Knogler, 2017 ) and is connected with the action in the model. This state of interest can be differentiated from a less-developed situational interest. While state of interest refers to an action-related, current experience (Knogler, 2017 ), less-developed situational interest marks the initial phase of a well-developed individual interest (Renninger & Hidi, 2022a ).

Integrating interest theory into the basic motivational model

Individual interest in content or subject matter is a stable predictor of academic achievement. Schiefele et al. ( 1992 ) determined a mean correlation coefficient of r = .31 between interest and academic achievement for studies in K-12 classes. In a more recent large-scale study, Lee and Stankov ( 2018 ) examined the relationship between mathematics interest and mathematics achievement in standardized tests. They found mean within-country correlations of r = .16 and r = .15 for data from PISA 2003 and PISA 2012, respectively. The effect of individual interest on academic achievement remained significant even when researchers controlled for students’ gender, nonverbal intelligence, or socio-economic status (M. Jansen et al., 2016 ). The strongest associations were found in the domains of mathematics and science (M. Jansen et al., 2016 ; Schiefele et al., 1992 ), which seem to be particularly suitable for initiating interventive measures (e.g., Crouch et al., 2018 ; Renninger et al., 2023 ). No meta-analyses are yet known for situational interest. However, Sundararajan and Adesope ( 2020 ) have analyzed how seductive details (i.e., interesting but irrelevant information) can affect learning outcomes. They found an average negative effect of g = − .33 for the relation between seductive details and recall or transfer of presented information.

Achievement Goal Theory

Anyone working as a teacher may have noticed that some students are very interested in learning something new, while others are motivated by obtaining good grades and avoiding poor ones (Eison, 1981 ; Eison et al., 1986 ). This fundamental distinction between individuals concentrating on the process of learning and individuals focusing on the external reasons for learning, can also be found in achievement goal theory (Elliot & Thrash, 2001 ). The theoretical framework has evolved steadily over four decades and is nowadays a key approach in motivation research (Elliot, 2005 ; Elliot & Hulleman, 2017 ; Urdan & Kaplan, 2020 ).

Achievement goals can be characterized by the intention to engage in competence-related behaviors (Elliot & Hulleman, 2017 ). In an attempt to further develop achievement motivation theory, Nicholls ( 1984 ); Nicholls & Dweck, 1979 ) called attention to two types of achievement behavior. Task-oriented individuals pursue the goal of developing high abilities. Ego-oriented learners care deeply about proving high abilities to themselves or others and avoid demonstrating low abilities. Later, the terms mastery goal and performance goal have been established to signify this basic distinction between the two achievement goals (Ames & Archer, 1988 ; Dweck, 1986 ; Elliot & Hulleman, 2017 ).

A first differentiation of the achievement goal theory has been made by including an approach and an avoidance component (Elliot, 1999 ). Research findings made clear that performance-approach goals were mainly associated with adaptive outcomes, whereas performance-avoidance goals were often associated with maladaptive outcomes (Harackiewicz et al., 2002 ). Originally, approach and avoidance components were assumed only for performance goals (Elliot & Harackiewicz, 1996 ). Later, researchers also addressed mastery avoidance goals, which concerns an individual’s striving to avoid mastering tasks worse than before or avoiding a decline in skills or knowledge (Elliot & McGregor, 2001 ; Van Yperen et al., 2009 ).

A second differentiation became necessary because competence-related behavior can be oriented toward very different standards (Elliot et al., 2011 ). Competencies may be reflected in whether certain tasks are fulfilled, performance is improved, or is better than the performance of others. The 3 × 2 achievement goal model by Elliot et al. ( 2011 ) incorporates the different aims of attaining competencies by differentiating between task-based, self-based, and other-based goals. Task-based goals are oriented toward the absolute demands of a task where the action’s outcome signals the attainment of an absolute standard. Self-based goals are a bit more complicated and require reference back to past performance anchored in the “Me-self” (Elliot et al., 2011 ). Competencies in terms of self-based goals refer to meeting or exceeding intrapersonal evaluation standards. Individuals with other-based goals, however, strive to meet interpersonal evaluation standards and to perform tasks better than others in a normative sense. The full 3 × 2 achievement goal model results from completely crossing absolute, intrapersonal, and interpersonal evaluation standards with approach and avoidance tendencies (Elliot et al., 2011 ).

Furthermore, the empirical distinction of performance goals into normative and appearance goals has gained a lot of popularity (Hulleman et al., 2010 ; Senko & Dawson, 2017 ; Urdan & Mestas, 2006 ). However, performance goals in the sense of seeking normative comparisons express the achievement goal concept of attaining competence much better than demonstrating ability to others (Elliot & Hulleman, 2017 ; Senko, 2019 ; Urdan & Kaplan, 2020 ). Therefore, we omit the distinction between normative and appearance goals in the model representation and report their effects only in the meta-analytic part.

Figure 6 illustrates how the 3 × 2 achievement goal model (Elliot et al., 2011 ) can be placed within the basic motivational model. The arrows in the illustration point to the cognitively represented aim of the action in a particular goal state. In task-based goals, the focus is on striving for a desired outcome or avoiding not to attain a desired outcome (see Fig. 6 ). The conceptualization of task-based goals is consistent with the original idea of mastery goals of understanding the content and doing well (Ames & Archer, 1988 ). To represent mastery goals, however, a second arrow would be appropriate from the goal to the action and not just to the outcome of learning. Through the action and the continuous comparison of the current and intended outcome of the action, the individual can master the task, develop new competencies or enhance existing ones (Dweck, 1999 ; Grant & Dweck, 2003 ). We have chosen to present the 3 × 2 achievement goal model (Elliot et al., 2011 ) with task-based goals oriented to the standard of task accomplishment and with a clear focus on the outcome (cf. Senko & Tropiano, 2016 ). Also belonging to mastery goals are the newly added self-based goals (Elliot et al., 2011 ). In self-based goals, the focus is on being better or avoiding being worse than in the past or as it corresponds to one’s own potential. For this purpose, the agent’s view goes back to the abilities and skills of the self (see Fig. 6 ) before the person tries to expand their competencies or avoid the loss of competencies in the action process. Self-based goals use one’s own intraindividual trajectory as the standard for evaluation. Goal setting starts with a look at one’s past, but more important seems to be a look on one’s future potential (Elliot et al., 2015 ). In other-based goals, the course of action is dominated by the anticipated consequences (see Fig. 6 ). The aim of attaining competence is based on an interpersonal standard of being better than others or not being worse than others. This conceptualization of other-based goals coincides with the normative notion of performance goals (Dweck, 1986 ; Senko et al., 2011 ).

Integrating the 3 × 2 achievement goal framework into the basic motivational model

Several meta-analyses have accumulated evidence on the empirical relationships of achievement goals with academic achievement (Baranik et al., 2010 ; Burnette et al., 2013 ; Huang, 2012 ; Hulleman et al., 2010 ; Murayama & Elliot, 2012 ; Richardson et al., 2012 ; Van Yperen et al., 2014 ; Wirthwein et al., 2013 ). The small but significant effects are remarkably consistent across different meta-analyses (for an overview, Scherrer et al., 2020 ). Mastery approach goals correlate between r = .10 (Baranik et al., 2010 ; Huang, 2012 ; Richardson et al., 2012 ) and r = .14 (Burnette et al., 2013 ; Van Yperen et al., 2014 ) with grades and test performance. Mastery avoidance goals show small negative relationships to academic achievement with correlations ranging from r = − .07 (Van Yperen et al., 2014 ) to r = − .12 (Hulleman et al., 2010 ). The correlation coefficients of performance approach goals to academic achievement are consistently positive, ranging from r = .06 (Hulleman et al., 2010 ) to r = .16 (Burnette et al., 2013 ). However, Hulleman et al. ( 2010 ) caveated that normative performance goals ( r = .14) were associated with significantly better performance outcomes than appearance performance goals ( r = − .14). Negative associations were also found between performance avoidance goals and academic achievement with values ranging from r = − .12 (Murayama & Elliot, 2012 ; Wirthwein et al., 2013 ) to r = -.22 (Burnette et al., 2013 ).

Attribution Theory

Attribution theory addresses the issue of how individuals make causal ascriptions about events in the environment (Graham & Taylor, 2016 ). Persons act like intuitive scientists searching for the perceived causes of success and failure (Stiensmeier-Pelster & Heckhausen, 2018 ). In the attribution process, the person tries to determine the cause of an outcome. Causal inferences are drawn based on the covariation of an observed effect with its possible causes (Kelley, 1973 ). The attributional process starts when the outcome of an event is considered important, unexpected, or negative (Graham, 2020 ), which is often accompanied by happiness in case of success or sadness and frustration in case of failure (Weiner, 1986 ).

The causes are then located in a three-dimensional space. The first fundamental dimension of the attribution theory is called the locus of causality (deCharms, 1968 ; Rotter, 1966 ; Weiner, 1986 ). It can be traced back to the pioneering ideas of Heider ( 1958 ), who found that people identify either the situation or dispositional characteristics of the person as the main reasons for people’s behavior. Individuals differentiate between external causes such as task characteristics or luck and internal causes such as ability or effort. The second causal dimension of attribution theory is entitled stability over time. Weiner ( 1971 ) distinguished between stable causes of outcomes such as ability or task characteristics and unstable causes such as effort or luck. Complete crossing of the locus and stability dimensions yielded a 2 × 2 classification scheme for the perceived causes of achievement outcomes. An outcome can be attributed either internally to the person or externally to circumstances. Furthermore, the cause of the outcome can be perceived as stable or variable over time. Finally, Weiner ( 1979 ) introduced a third causal dimension, controllability, as there was still considerable variability within the cells of the suggested classification scheme. For example, mood and effort are both internal and unstable causes, but effort is more subject to volitional control than mood. By combining two levels of locus with two levels of stability and two levels of control, Weiner ( 1979 ) extended the classification scheme to its current state of eight separable causes of success and failure.

The action model in Fig. 7 depicts the basic idea of attribution theory as stated by Heider ( 1958 ) and Weiner ( 1986 ). Attributions occur at the end of an action process. These causal ascriptions are elicited when the outcome is particularly important, unexpected, or negative (Weiner, 1985 ). Depending on the outcome, the person responds with positive affect in case of success or negative affect in case of failure. This front part of Fig. 7 coincides with current illustrations of the attributional theory of motivation (cf. Graham, 2020 ). Representing causal ascriptions and classifying reasons for success or failure on causal dimensions can only be done in a simplified manner in the basic motivational model. The action outcome is further attributed to dispositions of the self, such as perceived ability or effort, or the characteristics of the situation, such as task difficulty or chance (Stiensmeier-Pelster & Heckhausen, 2018 ). After ascribing the outcome to different causal dimensions, other emotions and future achievement strivings emerge as psychological and behavioral consequences of the attribution process (Weiner, 1986 ).

Integrating attribution theory into the basic motivational model

The three causal dimensions are linked to particular psychological and academic outcomes (Graham, 2020 ). Using meta-analytic structural equation modeling, Brun et al. ( 2021 ) found direct relationships between controllability and performance as well as mediated relationships of locus of causality, perceived competence, and performance. While the latter was most evident in the case of success, in the case of failure, the mediated relationship between the stability dimension, expectancy of success, and performance turned out to be significant. Further meta-analytic research showed that school children attribute success more to internal causes and failure more to external causes (Whitley Jr. & Frieze, 1985 ). This egotistic bias manifests in relating success to ability ( g = .56) and effort ( g = .29), and failure to task difficulty ( g = .45) but not to luck ( g = − .03). Fittingly, Fong et al. ( 2017 ) reported that greater internality and controllability of causal ascriptions are associated with better academic achievement among college students ( r = .14). In addition, Gordeeva et al. ( 2020 ) found that an optimistic attribution style, in which positive events are attributed to stable, internal, and global causes, is weakly related to academic performance ( r = .11). In contrast, a meta-analysis by Richardson et al. ( 2012 ) with university students did not reveal any relationships between academic performance and a pessimistic attribution style ( r =. 01).

The integrative model presented in this paper aims to provide a better overview of the most prominent motivation theories in education. The basic motivational model relies on the general model of motivation by Heckhausen and Heckhausen ( 2018 ) in its sequence of events and adopts considerations from Locke ( 1997 ) and Hattie et al. ( 2020 ) on the integration of motivation theories. The basic model allows for the classification of central motivation constructs into the course of action, highlighting in particular the differences between and within the six most popular motivation theories of our time. It makes us aware of the fact that the major theories cannot be easily merged into one another. Expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory have all shaped our understanding of why, when, and how individuals learn (Anderman, 2020 ). In the basic motivational model, learning outcomes represent a typical indicator of goal-directed behavior. Associated recent meta-analyses demonstrate the empirical relationship between the motivational constructs of the six central theories and academic achievement. They provide evidence for the explanatory value of each theory for students’ learning.

Particular features of the basic motivational model include parsimony (Hattie et al., 2020 ) and the role of situation, self, and goal as cornerstones of a modern conception for building motivation theories (Eccles & Wigfield, 2020 ; Graham, 2020 ; Liem & Senko, 2022 ; Ryan & Deci, 2020 ; Schunk & DiBenedetto, 2021 ; Urdan & Kaplan, 2020 ). Occam’s razor ensures to give preference to a model with fewer parameters over a more complex one. A theory with few variables in a clear, logical relationship to each other can be easily tested and can lead more quickly to unambiguous findings than a more expansive one. A basic motivational model should therefore be deliberately kept simple and specify only the decisive factors. This is what we have been trying to achieve. A closer look at current research on motivation in education shows that often only a particular set of constructs from much broader psychological theories is empirically investigated: self-efficacy expectations from social cognitive theory (Schunk & diBenedetto, 2020 ), expectancy and value beliefs from situated expectancy-value theory (Eccles & Wigfield, 2020 ), or causal ascriptions from attribution theory (Graham, 2020 ). Therefore, for reasons of parsimony, it seems advisable not to try to represent the entire wealth of motivation theories in an integrative model, but only their most important constructs (cf. Anderman, 2020 ; Hattie et al., 2020 ).

While achievement motivation theory posits an interplay of incentives of the situation and motives of the person as the basis for all motivated behavior (Atkinson, 1957 ), social-cognitive and sociocultural theories have significantly altered views on motivation (Eccles & Wigfield, 2020 ; Graham & Weiner, 1996 ; Liem & Elliot, 2018 ; Roeser & Peck, 2009 ; Wigfield et al., 2015 ). We attempted to account for these changing views in our basic motivational model. First, rather than viewing the situation as limited to its potential incentives, we recognized the social, cultural, historical, and environmental context represented in the situation as having a significant impact on the opportunities for motivated action (Nolen, 2020 ). Second, by differentiating the person into self and goal, we could more accurately describe the process of motivated behavior. We mapped the person’s needs, motives, and wishes to the self-system (Roeser & Peck, 2009 ). Driven by its needs, motives, aspirations, and desires, the “I-self”, the consciously experiencing subject, takes influence on the selection of goals and decision-making (Dweck et al., 2003 ; Sui & Humphreys, 2015 ). The self offers the underlying reason for behavior, whereas the goal contains the concrete aim to guide behavior (cf. Elliot et al., 2011 ; Sommet & Elliot, 2017 ).

Affective factors can be active in all phases of the motivation process and take influence on the course of action. At the beginning of the action process, there is typically an awareness of contextual cues or situational stimuli that can trigger emotions such as situational interest, curiosity, or surprise (Gendolla, 1997 ; Hidi & Renninger, 2019 ). Anchored in the self are emotional dispositions of the person such as hope for success, fear of failure, or individual interest. These activating emotions, aroused by situational incentives, are energizers of the action process (Atkinson, 1957 ; Pekrun et al., 2023 ; Renninger & Bachrach, 2015 ). Having goals and being oriented toward them, is also accompanied by emotional states (Linnenbrink & Pintrich, 2002 ). Mastery approach goals are typically associated with the presence of positive emotions and performance avoidance goals with the presence of negative emotions, whereas performance approach goals show weak relations to both positive and negative emotions (Huang, 2011 ; Korn et al., 2019 ). Research within the frame of the 3 × 2 achievement goal model could confirm these findings (Lüftenegger et al., 2016 ; Thomas, 2022 ). Positive emotions such as enjoyment and the state of interest (Hidi & Baird, 1986 ; Krapp et al., 1992 ) or negative emotions such as boredom and anger are expressed in accomplishing the action (Pekrun et al., 2023 ). Other emotions are attached to the outcome of the action: Positive outcomes are related to feelings of happiness, and negative outcomes go along with feelings of frustration and sadness (Graham, 2020 ). As consequences of the action, emotions such as pride, relief, or gratitude are prevalent in the case of success, whereas emotions such as guilt, shame, or disappointment emerge in the case of failure (Pekrun et al., 2023 ; Weiner, 1986 ). Overall, each phase of the action process is accompanied by certain affective states, which makes us aware of the close relationship between motivation and emotion.

While we have limited ourselves in this contribution to the six most common theoretical approaches (cf. Linnenbrink-Garcia & Patall, 2016 ), there are considerations of how other theories of motivation in education fit into the basic motivational model. These theories have not been researched by the same amount of scientists as the theories presented. Nevertheless, constructs such as grit, flow, and social motivation also offer suitable explanations for understanding the reasons behind human action. Grit theory (Duckworth et al., 2007 ) holds two trait-like constructs responsible for high motivation during task engagement. Meta-analytic results show that grit ( r = .19) is a consistent predictor of academic achievement with its dimension perseverance of effort ( r = .21) being more strongly related to academic achievement than the dimension consistency of interest ( r = .08; Lam & Zhou, 2022 ). In the integrative model, these two personality traits would be associated with the self and constantly impact goal pursuit (Duckworth et al., 2007 ). Flow theory (Csikszentmihalyi, 1990 , 2000 ) focuses on experiencing an optimal state of simultaneous absorption, concentration, and enjoyment (Tse et al., 2022 ). As a form of intrinsic motivation (Rheinberg, 2020 ), flow experience would be assigned to the action of the integrative model. Social goals (Wentzel et al., 2018 ) are not located on an intrapersonal level but on an interpersonal level. Two basic motivational models arranged in parallel could be used to map, for example, motivation in teacher-student relationships (Wentzel, 2016 ). This would provide a simple way to represent the reciprocal interactions between the goals and actions of teachers and students.

The integrative model also facilitates an understanding of the interrelationships between different motivational constructs. Howard et al. ( 2021 ) examined in a meta-analysis the relations of different types of motivation from self-determination theory with achievement goals and self-efficacy. Intrinsic and identified motivation showed high correlations with mastery-approach goals, moderate correlations with self-efficacy, and low correlations with performance-approach goals. In contrast, introjected and external motivation showed a reserve pattern and lowly correlated with mastery-approach goals and self-efficacy but moderately with performance-approach goals. To explain these correlative patterns, it can be deduced from the integrative motivation model that intrinsic motivation, identified motivation, mastery-approach goals, and self-efficacy share a common focus on action. In contrast, introjected motivation, extrinsic motivation, and performance-approach goals share a common focus on the consequences of the action. While such post-hoc explanations are of modest scientific value, it may be possible in the future to derive and empirically test predictions about the relationships among motivational constructs based on the integrative model.

A future application of the integrative model is to combine it with neuroscientific research on motivation (Kim, 2013 ; Kim et al., 2017 ). Kim ( 2013 ) proposed a tentative neuroscientific model of motivation processes, in which—similar to the action model—motivation is viewed as a series of dynamic processes. An added value of neuroscientific research is that it can help determine if seemingly overlapping constructs from different theories are unique or similar by examining the patterns of neural activity that are triggered (Kim, 2013 ; Kim et al., 2017 ). It additionally allows for the investigation of unconscious aspects of motivation. Neuroscientific studies can further help identify the mechanism of motivational processes relating to the generation, maintenance, and regulation of motivation. The integrative model can help in identifying overlapping constructs and investigating the mechanisms of motivational processes.

Another application of the integrative model is in using a person-oriented approach to study motivation (Linnenbrink-Garcia & Wormington, 2019 ; Ratelle et al., 2007 ; Wormington & Linnenbrink-Garcia, 2017 ). The person-oriented approach takes advantage of the fact that many motivational variables are often highly correlated with each other. Therefore, rather than singling out one motivational variable and analyzing its influences, it seems useful to create groups or profiles of students based on several different motivational variables. Thereby, it is recommended to use an integrative framework to relate the different motivational constructs: “A person-oriented approach can be particularly useful with an integrative theoretical perspective because it allows researchers to model the relations among motivation constructs across theoretical frameworks that may be conceptually related to one another” (Linnenbrink-Garcia & Wormington, 2019 , p. 748).

In the context of the integrative model, we have presented meta-analytic results on the relationship between motivation and academic achievement. Small to medium correlations emerged for the different types of motivation with students’ learning outcomes. Through its sequence of action stages, the integrative model suggests a causal order in which motivation is crucial for achieving academic outcomes. However, findings on the expectancy component show that the other direction may be considered equally probable, and academic achievement influences learners’ motivation (Pinquart & Ebeling, 2020 ; Sitzmann & Yeo, 2013 ). Therefore, the basic motivational model should also be understood as suggesting that prior academic achievement, cognitively represented in the self, helps shape motivation for new learning tasks.

Theories of motivation in education have increasingly expanded and differentiated over time (Schunk et al., 2014 ). Six major theories of motivation have been established (Linnenbrink-Garcia & Patall, 2016 ), which we have considered against the background of an integrative action model. The framework model is intended to contribute to a deeper understanding of the major theories of academic motivation and to show the focus of each theoretical conception. In this way, difficulties of understanding with which novices try to open up the field of academic motivation theories should be overcome to a certain extent. From the placement of the theories in the basic motivational model, it becomes clear that the various approaches to motivation cannot simply be merged into one another. Nonetheless, opportunities arise from the integrative model to reflect on the meta-analytic findings regarding the interrelations of motivational theories and constructs (Howard et al., 2021 ; Huang, 2016 ) and to speculate about the underlying mechanims of the connection. Similarly, possibilities arise to debate the changing understanding of motivational constructs or to situate new theories and constructs in the course of action to clarify their meaning.

Motivation in education is a very lively field of research with a variety of approaches and ideas to develop further beyond the basic theories. This includes a stronger inclusion of situational, social, and cultural characteristics in the explanatory context (Nolen, 2020 ), the use of findings from neuroscience to objectify assumptions about motivational processes (Hidi et al., 2019 ), the interaction of motivation and emotion in learning and performance (Pekrun & Marsh, 2022 ), the analysis of motivational profiles based on a person-centered approach (Linnenbrink-Garcia & Wormington, 2019 ), or the development of motivation interventions originating in sound theoretical approaches (Lazowski & Hulleman, 2016 ). To ensure that these developments in an increasingly broad field of research do not diverge, it is important to obtain a common understanding of the basic models and conceptions of motivation research. We hope to have made such a contribution by placing key theories and constructs of motivation within an integrative framework model.

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Chan Choong Foong , Peng Yen Liew; The relationships between academic motivation and academic performance of first-year chemical engineering students. AIP Conf. Proc. 26 October 2022; 2433 (1): 020012. https://doi.org/10.1063/5.0072668

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Academic motivation is linked to benefits in terms of learning effectiveness. This study investigated motivation of pursuing an engineering degree among first year chemical process engineering students. Forty-six students (n=46) who were in their first week of study completed a self-administered online questionnaire, that is the Academic Motivation Scale (AMS). The results showed that students had higher intrinsic motivation, higher extrinsic motivation and lower amotivation upon enrolling into the degree. Next, students’ academic performance in the first semester was collected. Correlations between motivation and academic performance were studied. The results indicate that extrinsic motivation is correlated significantly with academic performance. Recommendations were made to improve teaching and learning effectiveness, using the Self-Determination Theory perspective.

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ORIGINAL RESEARCH article

The influence of achievement motivation on college students’ employability: a chain mediation analysis of self-efficacy and academic performance.

• 1 Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Nakhon Pathom, Thailand
• 2 School of Foreign Languages and Cultures, Panzhihua University, Panzhihua, Sichuan, China
• 3 Faculty of Economics, Srinakharinwirot University, Bangkok, Thailand

Employability of college students has been attached great importance by higher education institutions, employers, and governments because college graduates are the strategic human resource for the sustainable growth of universities, organizations, and countries across the world. It is also receiving growing attention from academic community. This study aimed to examine the psychological mechanism that impacts college students’ employability. It adopted an empirical approach by collecting data from 646 final-year students from 9 universities in the mainland of China. SPSS 25.0 was used for description, correlation, and regression analysis. AMOS 24.0 was utilized for path analysis. Model 6 Bootstrap method of PROCESS Version 3.5 was adopted for mediation analysis. The results showed that achievement motivation positively predicted self-efficacy, academic performance, and employability among undergraduates. Participants’ self-efficacy did not significantly impact their employability or play a mediating role in the relationship between achievement motivation and employability, while academic performance was a significant mediator of this association. Self-efficacy and academic performance served as chain mediators in the prediction of achievement motivation on college students’ employability. After controlling gender and family residence, achievement motivation still had significant and positive impact on employability of college students. This research made several noteworthy contributions to the existing studies on college students’ employability and provided insight for practitioners in strengthening their employability through these psychological constructs.

Introduction

A growing number of students are graduating from higher education institutions across the world in recent years. On the one hand, converting these potential human resources into available talents to satisfy social needs is a significant way to promote economic development and social progress. These newly graduated talents can ensure the competitive advantage of organizations and innovation-driven development of nations. On the other hand, mounting pressure is laid on the shoulders of employers and governments to provide sufficient job positions for them. The rage of COVID-19 pandemic worsened the worrying situation due to economic slowdown ( Leslie and Wilson, 2020 ) and financial uncertainties ( Volenec et al., 2021 ). As a result, it became increasingly important for college students to enhance their employability to secure a job after graduation and contribute to sustainable economic growth.

Employability of college students has become a hot research field in academia in the past few years in various disciplines such as human resource management ( Donald et al., 2019 ; Nimmi and Donald, 2022 ), educational management ( Peng et al., 2021 ), psychology ( Wang et al., 2021 ), sociology ( Ingram and Allen, 2019 ), etc. Higher education institutions are striving to integrate employability developing programs into their educational system to ensure that the college students can be equipped with necessary knowledge, skills, attributes, and behaviors for a successful transition from campus to workplace ( Yawson and Yamoah, 2020 ). Scholars have been making continuous academic efforts from the perspectives of definition ( Harvey, 2001 ), influencing factors ( Nimmi and Donald, 2022 ), models ( Dacre Pool and Sewell, 2007 ), and other aspects of undergraduates’ employability to help tertiary institutions improve the performance of talent cultivation.

Among these existing studies, achievement motivation was tested to be positively associated with employability ( Diao, 2015 ). Achievement motivation is an intrinsic desire that motivates people to develop their capabilities to successfully achieve the dreams they pursue in their daily lives and in a variety of activities ( Suny and Suardiman, 2019 ). Motivation theories in contemporary education-related studies embody a variety of properties, such as goals, needs, desires, emotions, values, and interests ( Wang et al., 2020 ). Motivation has a significant correlation with individuals’ behavior, to be specific, positive motivation is able to stimulate good behavior, while negative motivation holds back such behavior ( Chiang et al., 2018 ). Achievement motivation has an impact on students’ success and excellence in the process of academic study ( Nofrizal et al., 2020 ), which, in turn, influences their employment prospects upon graduation ( Kamaliah et al., 2018 ). Prior studies have confirmed that achievement motivation significantly impacts the employability of college students, but only a few studies investigated the underlying mechanism of such influence. More specifically, no studies have been found to examine the path from achievement motivation to undergraduates’ employability through the chain mediating effect of self-efficacy and academic performance.

According to the social cognitive theory that interprets how the mechanisms of self-influence and self-regulation stimulate and govern human behavior ( Owusu-Agyeman and Fourie-Malherbe, 2019 ), self-efficacy is identified as a dominant behavior determinant ( Lee et al., 2018 ). It reflects an individual’ beliefs about his or her ability to take actions, accomplish tasks, and reach goals under different situations ( Bandura, 1986 ). Previous research revealed that achievement motivation and self-efficacy were significantly correlated ( Rui et al., 2011 ; Sabti et al., 2019 ), and self-efficacy was tested to have significant and positive influence on employability ( Lian et al., 2021 ). However, the majority of these studies concentrated on exploring the impact of self-efficacy on employability through the mediation of achievement motivation ( Wang et al., 2022 ). Less attention was paid to examine the influence of achievement motivation on employability through the mediation of self-efficacy among college students.

Additionally, achievement motivation from social cognitive perspective comprises of expectancy and value components in a broad sense, and previous studies based on such social cognitive model found that students’ motivational beliefs had significant and positive predicting effect on their academic performance ( Muenks et al., 2018 ; Steinmayr et al., 2019 ). In the meanwhile, several studies showed a significant positive relationship between students’ self-efficacy and their academic performance ( Shoval et al., 2021 ; Macakova and Wood, 2022 ). In terms of the research objects of the current study, students’ academic performance at the university was tested to have a significant positive contribution to their employment outcomes ( Chhinzer and Russo, 2018 ; Tentama and Abdillah, 2019 ). As a result, it could be of great theoretical and practical importance to explore the functioning mechanism through which achievement motivation, self-efficacy, and academic performance influence undergraduates’ employability, which has not yet been empirically investigated.

By conducting a questionnaire survey among undergraduates in the mainland of China, this study aims to examine how achievement motivation impacts self-efficacy and subsequently influences academic performance and employability under the psychological mechanism of social cognitive theory. The findings could provide theoretical insight and empirical evidence for the research on the correlation between crucial psychological constructs and undergraduates’ employability. The results would also offer feasible positive interference for higher education institutions to enhance the employability of their students.

Literature review and hypothesis development

Employability.

Employability is a combination of knowledge, skills, thought, and personal traits that improve an individual’s prospects of finding and maintaining jobs that are both satisfying and profitable to them ( Dacre Pool and Sewell, 2007 ). It refers to the integration of traits such as capability, personality, desire, and social resources to ensure employment, including the knowledge and skills a person possesses in the course of career development, and a variety of extensive adjustments to the work environment ( Yorke, 2006 ). It enables people to effectively accomplish work assignments by giving full play to their career-related abilities with proactive occupational behaviors ( Schreuder and Coetzee, 2011 ).

Since the subjects of the current research are students in higher education institutions, the specific definition of college students’ employability can be viewed as a set of capabilities that assist students to find jobs upon graduation and attain success in the process of their career development, such as occupational knowledge, skills, self-regulation, communication skills, and interpersonal relationship ( Harvey, 2001 ). It reflects the integrative abilities to accomplish satisfying work performance derived from learning ability and has turned into a critical factor for the career success of college graduates. Cultivating students’ career-related competencies and traits has become a core strategy for the transformation and development of higher education in many countries ( White et al., 2021 ). Strong employability skills can empower college students with competitive advantages in the job market and ensure their success in the workplace of the future ( Millican and Bourner, 2011 ).

Achievement motivation

Achievement motivation refers to the intrinsic drive within individuals that motivates them to accomplish important and meaningful tasks and leads them to excel at what they do ( Ye and Hagtvet, 1992 ). It is a complicated construct that includes several components such as self-perceived competency, task values, goals, and motives ( Steinmayr et al., 2019 ), which refers to the kind of motivation that drives individuals for excellent performance, competitive advantage, perseverance, and growing efforts in fulfilling activities or tasks ( Smith et al., 2019 ). As an internalized competency, it allows individuals to mobilize and manage their social and physical resources in a manner that improves performance and builds personal skills for success ( Werdhiastutie et al., 2020 ). Student achievement motivation theory holds that students with this psychological trait are fully motivated to achieve goals successfully, develop their own abilities more confidently, and avoid failure in a variety of changing situations ( Ishihara et al., 2018 ). Prior research found that achievement motivation had significant and positive correlation with the attainment of employability skills ( Diao, 2015 ) because it can implant a stronger desire into individuals to strive for success and alleviate fear of failure ( Tanjung and Musa, 2021 ). Individuals with strong achievement motivation have higher possibility to be accepted by job vacancies in the social contexts ( Huang et al., 2022 ). Hence, the following hypothesis was put forward:

H1 : Achievement motivation can positively predict employability of college students.

Self-efficacy

Self-efficacy refers to individuals’ beliefs that they can perform a specific behavior and achieve anticipated outcomes ( Bandura, 1977 ). It plays an important part in influencing people’s confidence in their ability to take actions and persevere under adversity ( Yang et al., 2021 ). Self-efficacy leads individuals to believe that they have the capability to make productive use of motivational and cognitive resources to achieve the ultimate effect of the expected actions ( Luthans, 2002 ). It is an important behavior-oriented factor that can affect students’ determination of learning objectives, choice of learning tasks, persistence of learning activities, and attribution of learning results.

Achievement motivation and self-efficacy

Individuals with strong intrinsic motivation to finish tasks and achieve goals tend to have self-confidence in taking specific actions and reaching desired objectives. For example, Wei et al. (2013) conducted a quantitative study on 336 Chinese students in higher education institutions and found that achievement motivation was positively correlated to self-efficacy in career decision. Damrongpanit (2019) suggested that achievement motivation was significantly and positively related with students’ self-efficacy in mathematics performance according to the research on 2,205 students and 117 teachers in Thailand. The study of 100 undergraduate students from two Iraqi public universities revealed that achievement motivation exhibited a significant positive correlation with self-efficacy in English writing ( Sabti et al., 2019 ). Therefore, H2 was proposed as follows:

H2: Achievement motivation can positively predict self-efficacy among college undergraduates.

Self-efficacy and employability

Self-efficacy has been widely studied in a variety of research fields because it was positively related to learning strategies ( Mornar et al., 2022 ), job performance ( Downes et al., 2021 ), occupational success ( Chughtai, 2018 ), self-esteem ( Ouyang et al., 2020 ), and commitment ( Yang et al., 2021 ). It is positively correlated with job search behavior and plays a crucial role in the employment of college graduates. Wang et al. (2022) found that self-efficacy was positively related to the levels of employability among college students in a quantitative study across six provinces in the Chinese mainland. A higher level of self-efficacy tends to make students more confident in seeking jobs when they graduate ( Lian et al., 2021 ) and more employable in the job market ( Chow et al., 2019 ). Thus, Hypothesis 3 was proposed:

H3 : There is a positive prediction of self-efficacy on college students’ employability.

Achievement motivation, self-efficacy, and employability

The previous studies revealed that achievement motivation had a positive impact on students’ self-efficacy, and higher level of self-efficacy led to stronger sense of employability of students in colleges and universities. It implied that self-efficacy may have a mediating effect in the relationship between achievement motivation and employability. As a result, the following hypothesis was proposed:

H4 : Self-efficacy played a mediating role in the correlation between achievement motivation and employability among college students.

Academic performance

Currently, academic performance has no universally agreed-upon definition in the research field of higher education. Many researchers believe that college students’ academic achievements are the sum of their learning results, behaviors, and attitudes during the period of higher education, mainly including college students’ behavioral performance and objective achievements ( Choi, 2005 ; Poropat, 2009 ; Stajkovic et al., 2018 ). Chamorro-Premuzic and Furnham (2003) measured academic performance by overall exam marks and final-year project performance. O’Connor and Paunonen (2007) argued that academic performance includes the grades of exams, essays, and courses as well as grade point average (GPA) and classroom performance. In general, the majority of the studies used GPA as a measure and indicator of students’ academic performance ( Endalamaw Yigermal, 2017 ; Eakman et al., 2019 ; Lou, 2021 ). For example, Gatzka and Hell (2018) conducted a meta-analysis on the correlation between six facets of openness and postsecondary academic performance with students’ official GPA from higher education institutions as the criterion for their academic performance. Jan et al. (2020) made correlation analysis between emotional intelligence, library anxiety, and academic achievement among college undergraduates with GPA as the indicator for academic performance. Based on the previous research, the current study takes GPA as the measurement for academic performance.

Achievement motivation and academic performance

Many researchers have found that students’ achievement motivation is closely and positively correlated with academic performance ( She et al., 2019 ; Gamazo and Martínez-Abad, 2020 ). Various constructs of motivation such as perceived control, values, and self-perception can be used as a supplement to intelligence tests to positively predict the academic performance ( Daniels and Dueck, 2022 ). Achievement motivation of students influences their psychological and behavioral characteristics such as hope of success, coping with failure, persistence in adversity, and willingness to take more challenging courses ( Yeager et al., 2019 ; Kapasi and Pei, 2022 ), which ultimately have an impact on their academic performance. A study on 4, 290 medical students from 10 Latin American countries indicated that their motivation was closely associated with achieving good academic performance during their college years ( Torres-Roman et al., 2018 ). Hence, the following hypothesis was proposed:

H5 : Achievement motivation plays a positive role in academic performance for college students.

Academic performance and employability

Several studies confirmed that academic performance is linked to college students’ employability ( Dong et al., 2019 ; Tentama and Abdillah, 2019 ). There is a statistically significant relationship between academic achievement and employability and a positive correlation between employers’ perceptions of graduates’ employability and academic achievement ( Chhinzer and Russo, 2018 ). Pinto and He (2017) found that higher academic performance led to greater job suitability and employability skills among business graduates from Peking University in China. A study on the graduate recruiters and employers who are looking for job applicants in the United Kingdom context revealed that academic achievements significantly affected the perceived employability of college graduates ( Byrne, 2022 ). Hence, Hypothesis 6 was put forward as follows:

H6: Academic performance has a positive impact on college students’ employability.

Achievement motivation, academic performance, and employability

Based on the above arguments, achievement motivation can positively predict students’ academic performance, and better academic performance result in higher level of employability, which indicated that academic performance may mediate the effect of achievement motivation on employability. Therefore, this study proposed the following hypothesis:

H7 : Academic performance played a mediating role in the correlation between achievement motivation and undergraduates’ employability.

Chain mediating effect of self-efficacy and academic performance

It has been found that students’ self-efficacy is significantly correlated with their academic performance ( Shoval et al., 2021 ; Macakova and Wood, 2022 ). A meta-analysis showed that self-efficacy was an influential factor to improve academic performance in online learning environment ( Yokoyama, 2019 ). College students’ self-efficacy was found to have a positive effect on their academic performance in online English classes in China in the midst of the COVID-19 pandemic ( Chang and Tsai, 2022 ). A systematic literature review on 27 articles revealed that self-efficacy and academic performance had significant and positive relationship among Latino students in America across all levels of education and with different measuring instruments ( Manzano-Sanchez et al., 2018 ). Thus, the following hypothesis was proposed:

H8 : College students’ self-efficacy has a positive impact on their academic performance.

In the light of the social cognitive theory, human functioning relies on the interaction between personal behavior (actions, choices, and verbal statements), internal personal factors (beliefs, expectations, attitudes, and knowledge), and environmental factors (resources, family, other people; Bandura, 1986 , 1997 ). Students who are highly motivated to strive for excellence would have higher level of self-efficacy ( Li and Li, 2018 ), generate better academic outcomes ( Liu et al., 2019 ), and become more employable in the labor market ( Dong et al., 2019 ). As a result, Hypothesis 9 was put forward:

H9 : Self-efficacy and academic performance play chain mediating roles in the relation between college students’ achievement motivation and their employability.

Control variables

Previous studies on employability have taken gender as a control variable ( De Cuyper and De Witte, 2011 ; Misra and Mishra, 2016 ; González-Romá et al., 2018 ). Cifre et al. (2018) highlighted the necessity to delve into employability from the perspective of gender. At the same time, Mamaqi et al. (2011) included economic sectors as a control variable in their study on employability. In the current research, economic sectors refer to the family background of the participants. To be more specific, it takes the family residence in rural or urban areas of the sample into the regression model to test the effect as a control variable because students from urban families are usually in more favorable financial situations than their rural counterparts ( Yang, 2010 ).

Materials and methods

Sample and procedure.

The study was conducted at nine universities in the mainland of China. The convenience sampling method was employed to recruit participants ( Assari, 2019 ). The objectives of the study and the policies of anonymity and confidentiality were presented before the participants filled the questionnaire. At last, 646 final-year college students participated in the survey with valid questionnaire. Among these respondents, 38.1% ( N  = 246) were male students, and 61.9% ( N  = 400) were female undergraduates. In terms of the family background, 46.1% ( N  = 348) of them were from rural households, and 53.9% ( N  = 298) were from urban families. As for the branches of academic disciplines that they studied in the universities, 45% ( N  = 291) were enrolled in Arts, 21.7% ( N  = 140) in Engineering, 30.2% ( N  = 195) in Management, and 3.1% ( N  = 20) in Medicine.

Achievement motivation was measured with the Chinese version of The Achievement Motive Scale ( Gjesme and Nygard, 1970 ). It originally had two dimensions: hope for success and fear of failure. Previous studies found that The Achievement Motive Scale with 30 items was unable to guarantee an acceptable fit to a two-dimension model ( Lang and Fries, 2006 ). The current study ultimately kept the factor of “hope for success” with seven items after conducting exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The present research adopted the Chinese version of The Morgan-Jinks Student Efficacy Scale ( Jinks and Morgan, 1999 ) to measure the construct of self-efficacy of college students. Two dimensions were included in this study: effort and context. Various studies have proved the validity and reliability of the scale in measuring students’ self-efficacy ( Magogwe and Oliver, 2007 ).

College Students’ Employability Scale ( He, 2019 ) was utilized to test undergraduates’ employability in this study. Four dimensions with 15 items in total were used: (1) application of knowledge; (2) teamwork; (3) communication and coordination; (4) self-learning; and (5) self-management.

Figure 1 illustrates the hypothesized research model.

Figure 1 . Hypothesized research model.

Data analysis

This study conducted a three-step analysis of the data. First, SPSS 25.0 was utilized for explanatory factor analysis, descriptive analysis, correlation analysis between the studied variables, and regression analysis of the effect of the control variables. Second, AMOS 24.0 was used to conduct confirmatory factor analysis and path analysis to test the hypothesis. Third, PROCESS version 3.5 was adopted to test the mediating effect.

Common method bias test

A common method deviation can occur when data is collected by self-report scales. Harman single-factor method was adopted in this study to examine the items of achievement motivation, self-efficacy, academic performance, and employability in an exploratory factor analysis. The results showed that there were six factors with initial eigenvalues greater than 1, which explained 65.049% of variance. Only 19.544% of the variance was explained by the principal factor, which is far less than the threshold of 40% ( Liu et al., 2020 ). Therefore, Harman single-factor test indicated that common method bias was unlikely to be concerned in the present study.

Validity and reliability of the scale

The overall scale and subscales used in the present study showed good reliability and validity. The values of Cronbach’s α and McDonald’s omega were used to evaluate the internal consistency of scales. The generally accepted threshold for the Cronbach’s α coefficient states that 0.9 ≤  α is deemed excellent, 0.7 ≤  α  < 0.9 good, 0.6 ≤  α  < 0.7 acceptable; 0.5 ≤  α  < 0.6 poor; α  < 0.5 unacceptable ( Kulthanan et al., 2019 ). The Cronbach’s α value of the overall scale is 0.927. Table 1 shows that the values of each variable are greater than 0.8 and that of each subfactor greater than 0.7. The overall AM scale had a good reliability with Cronbach’s α coefficient of 0.862. The Cronbach’s α value of SE was 0.751, and that of its two subfactors are greater than 0.7. The entire EMP scale had an excellent reliability because the Cronbach’s α coefficient reached 0.950 and its five factors were all greater than 0.7. Values of McDonald’s Omega greater than 0.7 were deemed acceptable ( Sharif Nia et al., 2018 ). As shown in Table 1 , the coefficients of McDonald’s Omega were all greater than 0.7 except for the SMG because this dimension only had two items after CFA, while McDonald’s Omega estimate requires at least three items.

Table 1 . Reliability and validity of the scale.

In order to determine the construct validity, both convergent and discriminant validity were examined. A strong indication of convergent validity can be found when the average variance extracted (AVE) is at least 0.5 ( Azizi and Khatony, 2019 ) as well as the composite reliability (CR) being greater than 0.7 ( Kheirollahpour et al., 2020 ). Table 1 shows that values of AVE for each scale were greater than 0.5 and CR values are all above 0.8, which indicated a good convergent validity. A construct needs a higher AVE square root than the correlation coefficient between it and other constructs in order to have acceptable discriminate validity ( Fornell and Larcker, 1981 ). As shown in Table 2 , the square roots of achievement motivation, self-efficacy and employability are 0.715, 0.741 and 0.738, respectively. All constructs in this study had an AVE square root greater than their correlation with other constructs.

Table 2 . Discriminate validity of the scale.

Differences in demographic variables

The demographic variables in this study included gender, family residence, and discipline. Independent-samples T-tests and One-way ANOVA were performed concerning achievement motivation, self-efficacy, academic performance, and employability among the participated final-year undergraduates.

Table 3 shows that self-efficacy scores of male students were significantly higher ( M  = 3.29, SD  = 0.51) than their female counterparts ( M  = 3.15, SD  = 0.44), t  = 3.728, p  < 0.001. Academic performance scores of the participants from urban families ( M  = 3.54, SD  = 0.67) are significantly higher than those from rural ones ( M  = 3.37, SD  = 0.67), t  = 3.198, p  < 0.01. The scores of employability were higher for those from urban families ( M  = 3.85, SD  = 0.58) than those from rural households ( M  = 3.68, SD  = 0.70), t  = 3.282, p  < 0.01. Employability scores of students majoring in engineering were higher ( M  = 3.87, SD  = 0.66) than those in arts ( M  = 3.71, SD  = 0.61), management ( M  = 3.83, SD  = 0.66), and medicine ( M  = 3.51, SD  = 0.60), F  = 3.857, p  < 0.01. Other than that, there were no significant differences in other variables between genders, family residences, and among different branches of academic discipline ( p  > 0.05).

Table 3 . Basic description of the variables ( N  = 646).

Correlations between the variables

As shown in Table 4 , the mean values of achievement motivation, self-efficacy, and employability and their subfactors of college students were all above 3. It suggested that the college students participated in this study basically had adequate levels of achievement motivation, self-efficacy, and employability. According to Table 4 , achievement motivation had a significant correlation with undergraduates’ self-efficacy and employability (including their respective subdimensions). A noteworthy result is that although the overall self-efficacy was significantly related to employability in general, the context factor of self-efficacy only had a significant association with the application of knowledge dimension of employability. No significant correlation existed between the context factor and the other four dimensions of college students’ employability, while the effort factor of self-efficacy had significant and positive correlation with overall employability and its subfactors. Academic performance had significant and positive relation with achievement motivation, self-efficacy, employability, and their subdimensions except the context factor of self-efficacy.

Table 4 . Means, standard deviations and correlations between variables.

Direct effect on employability

Before testing the hypotheses, this study conducted confirmatory factor analysis via AMOS 24.0 to examine the fitness of the proposed model. The results showed that the research model had a good fit ( χ 2 /df = 3.599, GFI = 0.891, CFI = 0.926, NFI = 0.901, TLI = 0.915, SRMR = 0.0574, RMSEA = 0.063). AMOS 24.0 was also utilized to conduct path analysis to test the proposed hypothesis. As shown in Table 5 , achievement motivation can positively predict employability at 0.001 level. Thus, H1 was supported. Achievement motivation can also positively predict self-efficacy at 0.001 level. Hence, H2 was supported. The path coefficient between self-efficacy and employability was not significant ( p  = 0.074 > 0.05). Therefore, H3 was rejected. Achievement motivation was tested to have positive prediction on academic performance at 0.001 level. Hence, H5 was supported. Academic performance was identified to have a positive impact on employability at 0.001 level. Therefore, H6 was supported. Self-efficacy was found to have a significant prediction on academic performance at 0.01 level ( p  = 0.009). Thus, H8 was supported.

Table 5 . Test results of the proposed hypothesis.

The regression analysis was conducted by SPSS Version 25.0. Gender and family residence were included as control variables in the regression equation. The result showed that achievement motivation of college students generated a significant and positive impact upon their employability after controlling the influence of the participants’ gender and family background ( β  = 0.551, p  < 0.001).

This research adopted PROCESS Version 3.5 to examine the mediating effect of self-efficacy and academic performance on the association between achievement motivation and employability of college students. Model 6 was selected in PROCESS with Bootstrap samples of 5,000. Bias Corrected for Bootstrap CI method was chosen and the level of confidence for all confidence intervals was set at 95%. A statistically significant mediating effect occurs if the interval between BootLLCI and BootULCI does not include 0 ( Preacher and Hayes, 2008 ).

After running the macro in SPSS 25.0, the following results were generated as shown in Table 6 . It demonstrated that the total indirect effect of the prediction of achievement motivation on undergraduates’ employability was 0.34. The indirect effect of self-efficacy on the relationship between achievement motivation and college students’ employability was 0.017. The 95% confidence interval included 0 (BootLLCI = −0.005, BootULCI = 0.046), which indicated that the mediating effect is not statistically significant. Hence, H4 was rejected. Self-efficacy did not play a mediating role in the relationship between achievement motivation and undergraduates’ employability. The indirect effect of self-efficacy and academic performance on the correlation between achievement motivation and employability was 0.019. The 95% confidence interval did not include 0 (BootLLCI = 0.005, BootULCI = 0.038), which confirmed a significant mediating effect. Thus, H9 was supported in this research. Self-efficacy and academic performance had a chain mediating effect on the correlation between achievement motivation and undergraduates’ employability. The indirect effect of academic performance on the correlation between achievement motivation and employability was 0.303.0 and was not included in the 95% confidence interval (BootLLCI = 0.247, BootULCI = 0.367), which identified a significant mediating effect. Hence, H7 was supported. Academic performance functioned as a mediator in the correlation between achievement motivation and undergraduates’ employability.

Table 6 . Mediating effect of self-efficacy and academic performance on the correlation between achievement motivation and employability.

Direct relationships

The current study confirmed that achievement motivation has a direct impact on employability of college students. The finding could provide theoretical and practical implications for both higher education providers and receivers. As for higher education administrators and teachers, they are propelled to pay high attention to students’ psychological factors to improve the overall quality of their graduates. Systematic integration of achievement motivation cultivation into educational plans and teaching curriculum to enhance students’ employability skills ( Laguna-Sánchez et al., 2020 ) emerges as an urgent mission for the sustainability of higher education. In terms of college students, they need to be aware of the significant and positive influence of psychological attributes on their employment prospects and personal growth. Even if they encountered setbacks in academic activities or daily life on campus, they should stay motivated to achieve planned goals and acquire necessary knowledge and skills instead of “lying flat” (a recently widespread phenomenon among Chinese young people that rejects hard working and constant competition; Gao et al., 2022 ).

Many previous studies revealed that self-efficacy and achievement motivation were significantly correlated, but most of the studies examined the prediction of self-efficacy on achievement motivation ( Liu et al., 2021 ; Huang et al., 2022 ). The present study added new evidence to the argument that achievement motivation had positive impact on self-efficacy at 0.001 level in the context of higher education. Students with intrinsic desire to attain achievements turned to be confident in their abilities in interacting with environmental factors and performing positive behaviors, which showed the valid application of social cognitive theory in China’s higher education sector.

Although a variety of prior studies found that self-efficacy had a significant and positive impact on employability of college students ( Chow et al., 2019 ; Wang et al., 2022 ), the current research showed that the prediction of self-efficacy on employability was not statistically significant, which echoed with the research result by Coetzee and Oosthuizen (2012) who found self-efficacy was not significantly related to employability among adult learners enrolled in the open distance learning programs. Self-efficacy scores of the samples were relatively low ( M  = 3.20, SD = 0.47) in the current study, which indicated that the participants did not have much confidence in their devotion to studies and their capabilities to accomplish academic tasks. Two dimensions of self-efficacy were examined in the questionnaire survey. The mean score of “effort” dimension was 3.45, indicating that students generally believed that they were able to obtain satisfying grades when they worked hard. The “context” dimension had the lowest score ( M  = 3. 06, SD = 0.55) among all the 11 variables. It revealed that the participants had doubts about the purpose of receiving higher education and felt unsatisfied with the amount of attention received from their teachers. This might be related to the growing employment pressure on college students since they had a lot of difficulties in securing a job or even became unemployed after graduation ( Wu et al., 2022 ). Furthermore, as a result of the expansion of enrollment of higher education in China ( He et al., 2020 ), teachers have to face a large number of students in one class and teach several classes in one semester. For example, the minimum class size in Panzhihua University in Sichuan Province is 60 for compulsory courses and 120 for optional courses. The teachers there are normally assigned four different classes in each semester. As a result, teachers were unable to give sufficient attention to each student. At the same time, this research found that the context factor of self-efficacy was only positively correlated with the “application of knowledge” dimension of employability. It was not significantly related to any other factor of undergraduates’ employability. The “context” mainly refers to the external factors that influence a person’s belief in their own ability ( Beck and Quinn, 2011 ). The findings of the current research revealed that students attached more importance to their “effort” in developing employability attributes. This could be partly explained by the advancement of information technology that enables students to have access to numerous educational resources ( Li et al., 2021 ) and borderless social networking ( Smirnov, 2019 ) across the world. As long as they are determined to develop skills, they would not have much impediment in reaching external educational resources.

Academic achievements that students obtained in college had a significant impact on their employability. On one hand, students with higher academic performance are often characterized by goal-orientation, perseverance in adversity, courage in taking daunting tasks, etc. ( Lerang et al., 2019 ; Lam and Zhou, 2022 ), which are also highly-valued qualities in workplace and critical factors to ensure sustainable career success. On the other hand, higher academic performance indicates sound mastery of specific knowledge and professional skills in the given field, which are basic requirements in job responsibilities. However, higher education institutions in China are undergoing dramatic transformation. Many of them are becoming application-oriented and giving strategic priority to work-integrated learning, integration of production and education, integration of occupational qualifications, etc. ( Zhang and Chen, 2022 ). As a result, they are running risk of attaching more importance to the needs from the industries than the actual academic performance of the students. The current study highlighted the significant and positive prediction of academic performance on undergraduates’ employability. It reminds the policy-makers and administrators to put the cultivation of students’ academic achievements at the first place to ensure the sustainable development of higher education.

Mediated relations

The test results showed self-efficacy did not serve as a mediator in the relationship between achievement motivation and employability among the participants in this study. Achievement motivation was tested to have a significant prediction on self-efficacy and employability, but self-efficacy did not significantly enhance the impact of achievement motivation on undergraduates’ employability. This could be the result of the above-mentioned generally low self-efficacy scores of the participants and their uncertainties about the future after graduation. In the meanwhile, students with high level of achievement motivation would naturally mobilize cognitive, social, intellectual, and emotional resources ( Zamroni et al., 2022 ) to attain set goals and become more employable in the labor market.

Academic performance was tested to mediate the relationship between achievement motivation and employability. College students are confronted with many challenges in their academic studies, campus life, and peer competition. Achievement motivation drives students to move forward in their learning activities, daily life, and acquisition of skills, which was confirmed to have a positive prediction on undergraduates’ employability in this study and previous research ( Kamaliah et al., 2018 ). Stronger achievement motivation could keep them in a healthy mental state and equip them with positive attitudes, which, in turn, strengthens their study effects and improves their academic performance. Academic achievements are closely related to knowledge and skills that students acquired in higher education institutions, which lays a solid foundation for their professional competencies and career success ( Thiele et al., 2018 ). As a result, academic performance enhanced the effect of achievement motivation on employability in the context of tertiary education.

Chain mediating relation

The present study showed that self-efficacy and academic performance jointly mediated the impact of achievement motivation and employability of college students from the mainland of China. Based on the social cognitive theory, behavior, cognition, and environment are interconnected and mutually determined ( Almuqrin and Mutambik, 2021 ). Students’ cognitive factors have a significant influence on their behavior. Their interactions with classmates, teachers, administrators, and other environmental factors reinforced their achievement motivation, self-efficacy, academic performance, and finally, the acquisition of necessary employability skills. Strong intrinsic motive to attain achievements stimulate positive self-efficacy and generate better academic outcomes, which effectively enhances their employability. The test results underlined the significance of developing students’ self-efficacy in the pedagogical endeavors in addition to enhancing their motive to succeed because self-efficacy determines individuals’ belief in performing behaviors and, in turn, affects their efforts and prospects in accomplishing specific tasks. When students are highly motivated and also believe in their ability to achieve the goals ( Yang et al., 2021 ), they would be equipped with strong employability skills that are most sought after by employers.

This study empirically examined the relationship between achievement motivation, self-efficacy, academic performance, and employability among undergraduates. Based on the previous findings in academic literature about employability, the present research proposed and tested the hypothesis by collecting data from different universities in China. The results showed that achievement motivation positively predicted self-efficacy, academic performance, and employability of college students. Self-efficacy was tested to have no significant impact on employability of the participants and play no significant mediating role in the correlation between achievement motivation and undergraduates’ employability, while academic performance significantly mediated such relationship. The findings showed that self-efficacy and academic performance played chain mediating roles in the prediction of achievement motivation on employability of college students. After controlling gender and family residence, achievement motivation still significantly and positively affects employability of college students.

The findings of this research add new understanding to the existing literature on college students’ employability. The study identified the chain mediating effect of self-efficacy and academic performance in the relationship between undergraduates’ achievement motivation and employability and found that self-efficacy had no significant direct and indirect effect on employability in this sample. It provides timely evidence that higher education institutions should give students’ academic performance top priority against the background of current application-orientation transformation. They also need to take immediate actions to make students realize the value and meaning of attending colleges to ensure the sustainability of higher education because students have insufficient confidence in finding employment after graduation. This study has several valuable implications for future practice of improving students’ employability for higher education providers since these graduates will be the most valuable assets of organizations, highly skilled knowledge workers in the labor market, and the main force in sustainable development.

Research limitations and future research directions

Although the study contributed to the existing literature on employability of college students in a number of theoretical and practical ways, it does have several limitations that need to be considered in future studies. Firstly, the latest official data from the Ministry of Education of China released on 30 September 2021 showed that there are 1, 270 higher education institutions in Chinese mainland offering bachelor’s degrees with 12 different academic disciplines. Only 9 public schools and 4 academic disciplines were surveyed in the current research due to the limited length of time and available contacts. When respondents were recruited from different types of universities and different branches of academic disciplines, the results might be different from those in this study. As a result, it would be necessary to test the results with a wider sample of participants in order to come to more general conclusions about the relationship between achievement motivation, self-efficacy, academic performance, and employability among university students. Secondly, the study examined the employability of college students in terms of subdimensions such as application of knowledge, teamwork, communication, coordination, self-learning, and self-management. Other potential dimensions of undergraduates’ employability were not yet paid attention to in the current analysis. Future studies are encouraged to examine other aspects of college students’ employability to gain a more comprehensive assessment. Thirdly, this research relies largely on questionnaire as its main research approach. A qualitative method might be helpful in revealing the profound correlation between the studied variables and provide valuable interpretation of the research findings from different perspectives.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by the Institutional Ethics Committee of the School of Foreign Languages and Cultures at Panzhihua University (approval code: no. HRECA21-006 and date of approval: 8 November 2021). The patients/participants provided their informed consent to participate in this study.

Author contributions

RP: conceptualization. XL and RP: data curation, investigation, and methodology. RP and NP: supervision and writing–review and editing. XL: writing–original draft. All authors contributed to the article and approved the submitted version.

This research was funded by the Ph.D. Research Start-up Fund of Panzhihua University (no. 035200187).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: achievement motivation, employability, self-efficacy, academic performance, college students, higher education

Citation: Li X, Pu R and Phakdeephirot N (2022) The influence of achievement motivation on college students’ employability: A chain mediation analysis of self-efficacy and academic performance. Front. Psychol . 13:972910. doi: 10.3389/fpsyg.2022.972910

Received: 04 July 2022; Accepted: 20 September 2022; Published: 06 October 2022.

Reviewed by:

Copyright © 2022 Li, Pu and Phakdeephirot. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ruihui Pu, [email protected] ; Xiang Li, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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The Relationship Between Motivation and Academic Performance Among Medical Students in Riyadh

Khalid a bin abdulrahman.

1 Family and Community Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, SAU

Abdulrahman S Alshehri

2 Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, SAU

Khalid M Alkhalifah

3 Family Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, SAU

Ahmed Alasiri

4 Psychiatry, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, SAU

Mohammad S Aldayel

Faisal s alahmari, abdulrahman m alothman, mohammed a alfadhel.

Background: Motivation is the process whereby goal‐directed activities are initiated and sustained. Motivation is a crucial factor in academic achievement. The study aims to measure students' demographic factors and external environments' effect on their motivation and determine the impact of students' motivation and self-efficacy on their learning engagement and academic performance.

Methodology: This is a cross-sectional study that involved distributing an online digital questionnaire, which was applied in the capital of Saudi Arabia, "Riyadh." The students’ motivation was assessed using three scales that are designed to measure the students' intrinsic/extrinsic motivation, self-efficacy, and learning engagement.

Results: In this study, we collected 429 responses from our distributed questionnaire among medical students where males represented 60.1% of the sample. Moreover, we classified the satisfaction level into five subcategories: very satisfied, satisfied, neutral, unsatisfied, and very unsatisfied. We found that most of the students (38.7%) were satisfied with their academic performance, while 17.7% were strongly satisfied. The mean enrollment motivation score in this study was 19.83 (SD 2.69), and when determining its subcategories, we found that the mean intrinsic motivation score was 10.33 (out of 12) and the mean extrinsic motivation score was 10.23 (out of 12). Moreover, the mean self-efficacy score was 9.61 and the mean learning engagement score was 8.97 (out of 12). Moreover, we found that a longer duration needed by the students to reach the college from their residence is significantly associated with lower learning engagement reported by the students (8.54 vs. 9.13 in shorter times, P=0.034). Finally, we found that students who entered medical school as their first choice had significantly higher intrinsic motivation, extrinsic motivation, self-efficacy, and learning engagement.

Conclusion: A student's preference for entering medical school will affect their motivation, self-efficacy, and learning engagement. Moreover, intrinsic and extrinsic motivations significantly correlate with self-efficacy and satisfaction with academic performance; however, they have no effect on the grade point average (GPA) of the last semester. The only factor that positively correlates with students' GPA is learning engagement.

Introduction

"Motivation is the process whereby goal‐directed activities are initiated and sustained"[ 1 ]. However, there is no consensual definition of motivation regarding the dozens of theories built around the concept. Among these, the social cognitive approach has gained considerable importance in studying motivation because it is considered a highly integrative and holistic way of understanding the concept of motivation to learn. According to this approach, motivation to learn is determined by both the individual himself and the environment. More precisely, it results from the constant interaction between a student's perceptions of his learning environment, learning behavior, and environmental factors [ 2 ]. All human beings share the motivation to secure their basic survival needs, including communication with each other, food, water, sex, and adaptation. To achieve these needs, motivation is a fundamental requirement at the right time. The concept of motivation is a useful summary concept for how the organism's internal physiological states, current environmental conditions, and the organism's history and experiences interact to modulate goal-directed activity [ 3 ].

Motivation is a crucial factor in academic achievement [ 4 ]. Precisely, the higher the motivation of medical students, the better their quality of learning, their learning strategies, persistence, and academic performance [ 2 ]. Motivation is a concept that has attracted researchers for many decades. Medical education has recently become interested in motivation, having always believed that medical students should be motivated because of their involvement in highly specific training, leading to a particular profession. However, medical students who have an absence of motivation are discouraged and have lost interest in their studies, with a feeling of powerlessness or resignation [ 2 ].

Academic motivation is one of the concepts studied with respect to student engagement. A previous study conducted by Skinner et al. looked at student participation as a result of their initiatives [ 5 ]. In addition, without engagement, there is no effective psychological cycle in learning and development. Moreover, Dörnyei found that students, even those with a high level of self-efficacy, find it difficult to understand the whole unless they are actively involved in learning [ 6 ]. Lin discussed the relationship between academic motivation and student engagement and considered academic motivation as a form of discipline that affects a person's behavior positively or negatively [ 7 ]. In addition, academic motivation, along with student involvement, influences one's goals, past experiences, cultural background, and the opinions of teachers and peers. Self-efficacy expresses one's belief in overcoming adversity [ 8 ]. Bandura et al. defined the word as an individual achieving the desired academic results. If students believe they can complete a task, they are more likely to engage in it. After Bandura et al. introduced the definition, the relationship between self-efficacy and academic success was discovered [ 9 ]. According to the results of the study, students with high levels of participation are more self-efficient than students with low levels of participation; It has been observed that these students spend a lot of time learning [ 10 ].

The impact and the influence of motivation on students' academic achievements and how motivation plays a vital role in learning have been well researched; many well-conducted studies over the past decades have shown that students' motivation has a high positive correlation with their academic performance. Internationally, a recent cross-sectional study in China in 2020 investigated the relationships between medical students' motivation and self-efficacy, learning engagement, and academic performance. They collected data from 1930 medical students by using an electronic questionnaire and data provided by their institutions; they found that the effectiveness of intrinsic motivation (e.g., if they have a strong interest in medicine) on academic performance is larger than that of extrinsic motivation (e.g., if their family or friends strongly encourage them to choose medicine). The direct effect of self-efficacy on academic performance was not significant. In addition, in this study, gender plays an important role. They found that male students have higher intrinsic motivation but surprisingly lower academic performance in comparison to females [ 11 ]. In a subsequent cross-sectional study conducted in 2018, 4,290 medical students from 10 countries in Latin America were among the students. This study investigates if the motivation that pushed Latin American students to choose a medical career is associated with their academic performance during their medical studies [ 12 ].

Different types of motivation have been shown to positively impact study technique, academic performance, and adjustment in students in education areas other than medical education [ 13 ]. Studying motivation, especially in medical students, is very important because clinical education is not quite the same as general education in different aspects. Some of them require clinical work alongside study. A recent study in the Netherlands created motivational profiles of medical students using high or low intrinsic and controlled motivation. It assessed whether different motivational profiles are associated with various academic performance results. They found high intrinsic motivation with low controlled motivations related to great study hours, deep learning strategy, good academic performance, and low exhaustion from studying. High intrinsic high controlled motivation was also associated with a good learning profile, except that those students with this profile showed high surface strategy. Low intrinsic high controlled and low intrinsic low controlled motivation was related to the least desirable learning practice [ 14 ]. Another study conducted in Iran investigated the relationship between academic self-efficacy and academic motivation among Iran's medical science students. Two hundred sixty-four undergraduate students at Qom University of Medical Sciences were selected through a random sampling method. They completed a questionnaire consisting of three sections: demographic characteristics, academic motivation, and academic self-efficacy. They found that achievement scores at the end of each semester and all scores on self-efficacy were altogether associated with academic motivation, while there was no noteworthy relationship between some demographic factors (e.g., age, gender) and academic motivation [ 15 ]. That confidence in academic performance outside of the classroom resulted in students' success. Such performance encourages the student to have faith in themselves and their self-efficacy and be more academically motivated. As time goes on, year after year, students lose their motivation.

Our study aims to measure students' demographic factors and external environments' effect on their motivation and determine the impact of students' motivation and self-efficacy on their learning engagement and academic performance. With that being stated, we believe motivation is a critical aspect of elevating academic performance. We aim to explore the relationship between motivation and academic performance in Riyadh medical schools to promote motivation and improve academic performance and outcomes.

Materials and methods

Study design and setting

This is a cross-sectional study that involved distributing an online digital questionnaire, which was applied in the capital of Saudi Arabia, "Riyadh."

Study subjects

The study population is all current medical students in medical schools in Riyadh, Saudi Arabia. The sample size was estimated via calculation using the sample size formula to assume that the number of medical students in Riyadh is 6,000, 95% confidence level, and 5% margin of error resulting in a sample size of 362. Inclusion criteria encompassed all current medical students in Riyadh, while students outside Riyadh were excluded.

Study tools

In this study, we depended on the questionnaire that was validated and used in a previous study conducted in a different setting [ 11 ]. The questionnaire consisted of two main parts: the first part included questions about the demographic factors of the students including gender, level, time needed from student’s residency to reach the university, and method of admission to medical school. The second part was divided into three parts including enrollment motivation, self-efficacy, and learning engagement. The three subscales were designed to measure the students' intrinsic/extrinsic motivation, self-efficacy, and learning engagement, respectively. In particular, the enrolment motivation scale was adapted from the academic motivation scale (AMS) [ 16 ]. The AMS scale consisted of 20 items which represent 42.2% of the total variance and discovered three factors: self-discovery, using the knowledge, and discovery. Internal consistency changed between 0.72 and 0.88 in both factors, and the total scale’s Cronbach alpha value was 0.92 [ 17 ], while the learning engagement scale was adapted from the Utrecht Work Engagement Scale (UWES) for students [ 18 ]. The UWES-9S is a nine-item self-report scale grouped into three subscales with three items each: vigor, dedication, and absorption [ 19 ]. All items were scored on a seven-point frequency rating scale ranging from 0 (never) to 6 (always).

Statistical analysis

The collected data was cleaned, entered, and analyzed using SPSS Statistics version 23 (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.). Frequency and percent were used for the description of categorical variables, while mean, SD, maximum, and minimum were used for the description of ongoing variables. ANOVA test was used to find the correlation between the scores of both tools with the status of vision. All statements were considered significant if the p-value was less than 0.05.

Ethical consideration

The study was conducted after receiving ethical approval from Imam Mohammed Ibn Saud Islamic University, College of Medicine (19-2021). All patients had to provide consent before participating in the questionnaire.

In this study, we collected 429 responses from our distributed questionnaire among medical students with an 85% response rate, where males represented 60.1% of the sample. Considering the marital status of the students, we found that almost all of the students were single. Moreover, 41.7% of students claimed that getting to their medical school from their residence required them to travel for 15 to 30 minutes each day, while 31.9% needed less than 15 minutes and 26.3% needed more than half an hour. Furthermore, 24.9% of the students were in year 1, while 23.1% were in year 3, and 22.8% were in year 2. Moreover, we found that 93.7 % of the students entered medical school as their first choice and 41.3% indicated that they had a grade point average (GPA) of 4.75-5 in the last semester. Furthermore, we found that 71.8% of the students thought that they had the complete motivation to complete their education, whereas family members were the main persons who gave them the motivation (69%), as shown in Table ​ Table1 1 .

GPA: grade point average

As represented in Figure ​ Figure1, 1 , we found that 38.7% of the students were satisfied with their academic performance, while 17.7% were strongly satisfied; however, 16.1% of the students were unsatisfied with their academic performance, while 5.4% were very unsatisfied.

Moreover, in this study, we used three scales to assess three factors of the students including their enrollment motivations, self-efficacy, and learning involvement. Enrollment motivation scores in this study ranged from 8 to 24 with a mean score of 19.83 (SD: 2.69), and when determining its subcategories, we found that the mean intrinsic motivation score was 10.33 (out of 12), and the mean extrinsic motivation score was 10.23 (out of 12). Moreover, the self-efficacy score ranged from 2 to 12 with a mean score of 9.61, and the mean learning engagement score was 8.97 (out of 12), as shown in Table ​ Table2 2 .

In this study, we found that entering medical school as the first choice or not significantly affects enrolment motivations, where students who entered medical school as their first choice had significantly higher intrinsic motivation, extrinsic motivation, self-efficacy, learning engagement, students’ motivation, and enrollment motivation. Moreover, we did not find any significant differences among students with different GPAs depending on their motivation, self-efficacy, or learning engagement. However, when dividing the students into two groups with GPAs lower and higher than 4.5, we found a significant difference between the two groups. Intrinsic motivation was significantly higher in students with higher GPAs than other students (10.35 vs. 10.06, P=0.04), as well as considering self-efficacy where students with GPAs higher than 4.5 reported a higher level of self-efficacy (9.79 vs. 9.34, P=0.012) and higher learning engagement in students with GPAs higher than 4.5 (9.15) than those with GPAs lower than 4.5 (8.72) (P=0.035). Extrinsic motivation was higher in students with higher GPAs but with no significant difference (P=0.175). Considering students’ enrollment motivation, we found that students with higher GPAs have a higher level of enrollment motivation and a significantly higher level of students’ motivation than those with lower GPAs (Table ​ (Table3 3 ).

* Significant at p-value less than or equal to 0.05

IM: intrinsic motivation, EM: extrinsic motivation, SE: self-efficacy, LE: learning engagement, GPA: grade point average

In Table ​ Table4, 4 , we showed the correlation between enrollment motivation and self-efficacy, learning engagement, and GPA. We found that intrinsic and extrinsic motivation significantly correlate with self-efficacy and learning engagement; however, they had no effect on the GPA of the last semester. The only factor that was positively correlated with the GPA of students was learning engagement, where the higher the learning engagement score of the students, the higher their GPA (Table ​ (Table4 4 ).

IM: intrinsic motivations, EM: extrinsic motivation, SE: self-efficacy, LE: learning engagement, GPA: grade point average

In this study, we aimed to measure the impact of students' demographic factors and external environments on their motivation and determine the impact of students' motivation and self-efficacy on their learning engagement and academic performance.

The results of this study showed that neither the gender, grade of the students, nor how far their residency had an impact on their motivation. Moreover, a student's preference for entering medical school will affect their motivation, self-efficacy, and learning engagement. Moreover, intrinsic and extrinsic motivations significantly correlate with self-efficacy and satisfaction with academic performance but have no effect on the GPA of the last semester. The only factor that positively correlated with the students' GPAs was learning engagement. A study by Javadi et al. found that the mean intrinsic and extrinsic motivation score was higher in females than in males and in freshmen than higher-level students [ 20 ]. A study by Wu et al. found that male students reported significantly higher intrinsic motivation but surprisingly lower levels of academic performance than female students [ 11 ]. In another study conducted by Kusurkar et al., females had higher intrinsic motivation than males in medical education settings [ 14 ]. The only factor that affected the students’ motivation, whether intrinsic or extrinsic motivation, was their willingness to enter medical school; students who reported that entering medical school was their first choice had a significantly higher motivation than those who said it wasn't. Considering demographic factors affecting self-efficacy, we found that students' gender, grade, and willingness to enter medical school are all factors that affect their level of self-efficacy; males, older students, and those who indicated that entering medical school was their first choice all reported having higher levels of self-efficacy. Moreover, we found that there was no difference reported between genders in terms of learning engagement. However, we found that the time it takes to get to the college from residency has a significant impact on learning engagement, where students at farther residency would have lower learning engagement than those at closer residency. This result was also reported in previous studies [ 21 , 22 ]. Furthermore, we found that students who enter medical school as their first choice have a higher level of learning engagement, contrary to those who didn’t choose medical school as their first choice. These results indicated that the main factors affecting student’s motivation, self-efficacy, and learning engagement are their choice and will to enter medical school. Therefore, one of the important recommendations in this study is to let students choose their career destination [ 23 ]. In Saudi Arabia, as well as many other Arabic countries, entering medical school is a great achievement from the point of view of parents and society [ 24 ]. Therefore, this could put pressure on students to enter medical school even though this is not what they want. According to our study, this will affect their motivation, self-efficacy, and learning motivations.

Moreover, the results of this study showed that intrinsic and extrinsic motivation significantly correlate with self-efficacy, learning engagement, and satisfaction with academic performance but have no effect on the GPA of the last semester. The only factor that positively correlates with the GPA of students was learning engagement where the higher the learning engagement score of the students, the higher their GPA. This indicates that the motivations of the students have a significant impact on their learning engagement and academic performance. These results contradict those of Javadi et al. who found no significant correlation between intrinsic and extrinsic motivation and academic performance [ 20 ]. Previous studies, including that of Wu et al., found that intrinsic and extrinsic motivation was significantly and positively associated with self-efficacy and learning engagement. However, in this study, extrinsic motivation had no significant association with the students’ academic performance while intrinsic motivations had [ 11 ]. Moreover, these results were also found in other studies including that of Fan et al. [ 25 ], Walker et al. [ 26 ], Bakker [ 27 ], and Baker [ 28 ]. Moreover, previous studies confirmed a positive relationship between learning engagement and academic performance found in this study [ 29 , 30 ].

Limitations

This study has some limitations. One of these limitations is the dependence on self-reported questionnaires which could lead to some personal bias including the desire of students to appear better. Moreover, we depended on students’ self-report of their GPA of the last semester which could lead to some bias including remember bias and personal bias where students would tend to report higher scores. The study’s sample size and gender distribution might limit the generalizability of the findings. Addressing these limitations through diverse samples and longitudinal studies would enhance the study’s quality and enrich the insights drawn from its results.

Conclusions

In conclusion, we found that students’ will to enter medical school is the main factor affecting their motivation, self-efficacy, and learning engagement. Moreover, intrinsic and extrinsic motivations significantly correlate with self-efficacy, learning engagement, and satisfaction with academic performance but have no effect on the GPA of the last semester. The only factor that positively correlates with the students' GPA is learning engagement.

The authors have declared that no competing interests exist.

Author Contributions

Concept and design:   Abdulrahman S. Alshehri, Khalid A. Bin Abdulrahman, Khalid M. Alkhalifah, Ahmed Alasiri, Mohammad S. Aldayel, Faisal S. Alahmari, Abdulrahman M. Alothman, Mohammed A. Alfadhel

Drafting of the manuscript:   Abdulrahman S. Alshehri, Khalid M. Alkhalifah, Ahmed Alasiri, Mohammad S. Aldayel, Faisal S. Alahmari, Abdulrahman M. Alothman, Mohammed A. Alfadhel

Critical review of the manuscript for important intellectual content:   Khalid A. Bin Abdulrahman, Khalid M. Alkhalifah, Ahmed Alasiri, Mohammad S. Aldayel, Faisal S. Alahmari, Abdulrahman M. Alothman, Mohammed A. Alfadhel

Supervision:   Khalid A. Bin Abdulrahman

Acquisition, analysis, or interpretation of data:   Khalid M. Alkhalifah, Ahmed Alasiri, Mohammad S. Aldayel, Faisal S. Alahmari, Abdulrahman M. Alothman, Mohammed A. Alfadhel

Human Ethics

Consent was obtained or waived by all participants in this study. Imam Mohammad Ibn Saud Islamic University Institutional Review Board (IRB) issued approval 19-2021

Animal Ethics

Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.