Achievement Motivation in Education
- Judith MeeceJudith MeeceThe University of North Carolina at Chapel Hill
- and Charlotte AggerCharlotte AggerIndiana University
Achievement motivation theories are used to understand gender discrepancies in motivation across various academic domains. Early on in the field of motivation research, researchers commonly used an attribution framework to study achievement-related outcomes among men and women. Self-efficacy theory and a revised expectancy-value theory of achievement-related choices dominate the current literature on gender differences and achievement motivation. Current trends in research on gender and academic motivation include the shifting and expanding of theoretical frameworks, a new focus on the motivation and achievement of male students, and the use of advanced methodologies and cross-national data to conduct comparative research on gender and patterns of motivation.
This article provides an overview of research on gender and academic motivation. Due to the authors’ expertise, the primary focus is on youth in the United States; however, a brief mention of international studies is included as well. The article begins with current research findings on gender and educational attainment. It then provides overviews of historical and contemporary theories of achievement motivation, and concludes with a presentation of current and future trends in research regarding gender and academic motivation.
Gender-Related Trends in Academic Achievement and Educational Attainment in the United States and Abroad
Over the past several decades, educational researchers have documented trends in girls’ and boys’ academic achievement and educational attainment (see Agger & Meece, 2015, for a review). Most notably, within the United States girls have caught up with, and surpassed, their male counterparts regarding performance on school-based and national assessments. Currently, girls are also more likely to complete secondary schooling and graduate from college with a bachelor’s degree (DiPrete & Buchmann, 2013; Meece & Askew, 2012). However, despite this progress on school-based and national assessments and college completion rates, girls lag behind boys in terms of their participation in mathematics-intensive fields during the postsecondary years and beyond (National Science Foundation [NSF], 2013; Watt, 2008). Men continue to enter physical science fields (e.g., physics) at greater rates than women (NSF, 2013) and continue to pursue these disciplines at greater rates than women beyond college.
Outside of the United States and other industrialized nations, there is less research on gender-related trends in academic achievement and educational attainment. However, there is a small base of literature that has used cross-national data such as the Trends in International Mathematics and Science Study (TIMSS) and the Program for International Student Assessment (PISA) to study gender and achievement. Using these two data sources, researchers have documented patterns of gender-related achievement that are similar to those found in the United States. First, international studies show trends favoring girls on literacy-focused assessments and in terms of grade point averages and college graduation rates (Agger & Meece, 2015). In other domains, such as mathematics, boys tend to outperform girls on international assessments, although gender differences are quite small (less than 5%) in countries such as Finland, Slovenia, Sweden, Indonesia, and Russia (Organisation for Economic Co-operation and Development [OECD], 2011).
These gender-related patterns mainly appear in Western or industrialized countries. In developing counties, girls have much poorer educational outcomes (OECD, 2011), which is a result of numerous and compounding factors including poverty, geographic isolation, early marriage and pregnancy, gender-based violence, and cultural norms surrounding the status and roles of women (United Nations Educational, Scientific and Cultural Organization [UNESCO], 2015).
Moreover, even within industrialized countries, such as the United States, there is considerable variation in academic achievement and educational attainment within gender groups related to cultural norms, racial stereotypes, economic resources, and discriminatory practices. As described in the next section, current research on gender and achievement motivation is beginning to examine these larger sociocultural influences on academic achievement and educational attainment.
Historical Perspectives on Gender and Achievement Motivation
Research on gender and achievement motivation has a long history in the fields of education, educational psychology, and psychology. Motivation is defined as a “process by which achievement-related activities are instigated, sustained, or terminated” (Schunk, Meece, & Pintrich, 2014, p. 5). In the field of education, achievement motivation researchers have studied the processes that influence an individual’s choice, engagement, performance, and level of educational attainment. Whereas early theories of achievement motivation focused on gender-related personality traits, more contemporary theories focus on the formation of self-perceptions, beliefs, and identities as sources of achievement motivation.
Early theories of achievement motivation centered on differences in the achievement motives of men and women. Researchers conceptualized achievement motives as personality dispositions that were formed early on and remained stable over time (Schunk et al., 2014). In early studies, McClelland and colleagues (1953) used the Thematic Apperception Test (TAT) to assess achievement motives in college-age men and women. The TAT measure asked study participants to view and evaluate different pictures. The pictures depicted men and women in different ambiguous situations. After participants were shown the pictures, they were asked to provide a report of what they saw. Researchers showed male students pictures of two men at a machine and a man at a drafting table and researchers showed female students pictures of two women in a laboratory and a woman upholstering a chair. College students were also asked to write stories about a male (female) student who was at the top of his (her) medical class. The TAT’s operating assumption was that study participants would project their motives and desires onto the pictures and stories. For example, success-oriented people would create stories that involved a significant amount of achievement imagery. Results of the study showed that, in general, college men responded to the TAT assessments with more achievement imagery compared to their female counterparts. Based on study findings, researchers concluded that women were less success-oriented than men. In a further analysis of men’s and women’s responses, Horner (1972) reported that 65% of the college women and 8% of the college men wrote stories that showed anxiety about success in academic situations. Horner (1975) argued that “most women have a motive to avoid success, that is, a disposition to become anxious about achieving success because they expect negative consequences such as social rejection and/or feelings of being unfeminine” (p. 207). Accordingly, women’s fear of success, and how this fear could lead to diminished achievement, were topics that generated much research in the 1970s (see Frieze, Parsons, Johnson, Ruble, & Zellman, 1978).
By the late 1970s, the previous work on achievement motives and fears of success had been discredited. Problems related to biased research methodologies and findings that were not generalizable across different samples surfaced (Frieze et al., 1978). In addition to these problems, the work was also criticized because it cast male achievement as the standard to which female achievement was compared. Furthermore, the work on achievement motives and fears of success was criticized because it did not consider how gendered socialization patterns and other proximal and distal forces shape men’s and women’s academic and occupational choices (Eccles, 1994).
During the 1970s and early 1980s, attribution theory was the prevailing theory of motivation and was heavily utilized to understand differences in achievement motivation across gender. Attribution theory served as the transition into cognitive perspectives on motivation due to its emphasis on cognitive processes involved in interpreting successes and failures in achievement situations (Meece, Glienke, & Burg, 2006). This emphasis was different from earlier theories, which included personality dispositions (e.g., motives to avoid success and fear of failure). Attribution theory also served as the springboard for developmental studies of children’s conceptions of ability and definitions of success (Dweck & Elliot, 1983; Nicholls, 1984).
Weiner (1979) played a major role in developing attribution theory and applying it to educational settings. In attribution theory, individuals are viewed as “naive scientists,” trying to understand their own behaviors and also the behavior of others around them. Weiner (1985, 1986) argued that the two chief causal ascriptions people make related to success and failure are ability and effort. Weiner also argued that attributions were related to a variety of additional achievement-related beliefs such as expectations for success, achievement striving, and the affect (e.g., anxiety) associated with achievement.
An attribution framework was widely applied in studies examining gender differences in achievement motivation. Across various age groups, male participants were shown to attribute their successes to internal causes such as ability, whereas female participants attributed their failures to internal causes (Bar-Tal, 1978; Crandall, Kathkowsky, & Crandall, 1965; Frieze, 1975; McMahan, 1973). Later on, these gender-related findings were more consistently reported for sex-typed domains such as mathematics and science (Eccles et al., 1983; Frieze, Whiteley, Hanusa, & McHugh, 1982; Parsons [Eccles], Meece, Adler, & Kaczala, 1982; Wolleat, Pedro, Becker, & Fennema, 1980). In the end, researchers concluded that gender differences in causal attributions patterns were dependent on the type of academic domain, the students’ ability level, and the kinds of research methodologies employed (Parsons [Eccles] et al., 1982).
A related area of attribution research includes studies of learned helplessness. Learned helplessness occurs when individuals attribute their failure to a lack of ability and show decreases in effort when confronted with failure (Licht & Dweck, 1984). Researchers argued that girls may be more prone to learned helplessness than boys, particularly in the domain of mathematics and other male sex-typed domains, due to a tendency to attribute failure to a lack of ability (Dweck, 1986; Eccles et al., 1982; Farmer & Vispoel, 1990). However, findings were not consistently found across studies. For example, Eccles [Parsons] et al. (1982) used authentic learning tasks (e.g., number sequences) to examine gender differences in learned helplessness among students in Grades 8–10. These researchers found gender differences in attributions to ability for successes and failures on math problems, but these causal attribution patterns did not explain gender differences in persistence, expectancy judgments, or error rates (see also Kloosterman, 1990). Empirical studies provided limited support for greater learned helplessness among girls than boys.
Grounded in attribution theory, studies on students’ mindsets have shed some light on potential reasons for the underrepresentation of women in math and science fields. Work by Dar-Nimrod and Heine (2006) and Good, Rattan, and Dweck (2007; cited in Dweck, 2008) showed that differences in women’s math performance and feelings of belonging depended on whether they held a growth-mindset (i.e., holding the belief that you can significantly change your intelligence level) versus fixed-mindset (i.e., holding belief that your intelligence and ability levels are fixed). These researchers documented that female students who maintained a growth-mindset performed better on math tasks (Dar-Nimrod & Heine, 2006) and were less susceptible to the negative effects of stereotypes; when they were faced with negative stereotypes, they still felt that they belonged in math, intended to pursue math courses, and continued to earn high grades (Good et al., 2007).
To summarize, research using attribution theory sought to understand the low expectancy patterns, achievement anxiety, and learned helplessness that inhibited female achievement. Despite numerous studies, research on gender differences in causal attributions and learned helplessness is inconclusive and equivocal. Gender differences in attributions depend on the particular methodology used, the specific academic domain, the academic abilities of students, the achievement task, and the context in which the research occurs. Additionally, when gender differences are found, they are often small in magnitude and do not strongly predict behavioral responses (Eccles et al., 1983; Eccles [Parsons] et al., 1982, 1984; Hyde, 2014).
Contemporary Theories of Achievement Motivation
After the introduction of attribution theory in the 1970s, subsequent theories emphasized the role of cognitive processes in explaining gender differences in achievement motivation. Two theories have dominated research in this area: self-efficacy theory (Bandura, 1977) and a revised expectancy-value theory of achievement-related choices (Eccles et al., 1983).
The construct of self-efficacy was introduced more than 40 years ago (Bandura, 1977). Since its introduction, educational researchers and those studying academic motivation and self-regulated learning have heavily drawn upon self-efficacy theory. Self-efficacy refers to a person’s judgment of their confidence to learn, perform academic tasks, or succeed in academic endeavors (Bandura, 1986). Unlike more global beliefs such as self-concept, self-confidence, and locus of control, self-efficacy involves judgments concerning one’s ability to attain a certain level of performance in a particular activity or situation (Meece, Wigfield, & Eccles, 1990; Schunk, 1984). For example, in one study, respondents were asked to rate their level of confidence for solving a certain number of mathematics problems correctly, for obtaining a certain grade in a course, for comprehending reading passages of different levels of difficulty, or for learning technical terms in biology (Pajares, 1996b). Research has consistently shown that self-efficacy beliefs are important mediators of all types of achievement-related behaviors, such as effort and task persistence, self-regulatory strategies, course enrollment, and career choices (Bong & Skaalvik, 2003; Fast et al., 2010; Pajares, 1996b; Pintrich & Schunk, 2002; Schunk & Pajares, 2002).
Motivation researchers have used self-efficacy theory to understand gender differences in motivation and achievement. The majority of this research has focused on academic areas that are traditionally sex-typed as male or female. A plethora of studies documents that boys tend to report higher self-efficacy and expectancy beliefs than girls surrounding their performance in math and science (Anderman & Young, 1994; Pajares, 1996a, 1996b; Pintrich & De Groot, 1990; Zimmerman & Martinez-Pons, 1990), as well as computer science (Busch, 1995). The results of Huang’s (2013) meta-analysis of 187 studies of gender differences in self-efficacy beliefs showed a consistent pattern favoring male students with learning tasks related to mathematics, science, computer science, and social sciences. However, effect sizes were reported as small (.08), with the exception of respondents over the age of 23 years. In contrast, when the context is changed, and the academic domain is reading or writing, the gender difference is reversed and girls are favored (Huang, 2013; Pajares & Valiante, 2001a, 2001b; Williams & Takaku, 2011).
Self-efficacy researchers have identified several confounding factors that may contribute to gender differences in self-efficacy. First, gender differences were nonsignificant when previous achievement was controlled for; that is, when self-efficacy beliefs of students are analyzed at the same level of academic ability, fewer differences in self-beliefs appear (Pajares, 1996a). Second, the measurement process itself may be responsible for differences. Researchers have observed that boys tend to be more “self-congratulatory” in their responses (i.e., expressing overconfidence), whereas girls tend to be more modest (Wigfield, Eccles, & Pintrich, 1996). Additionally, recent studies have explored gender differences in sources of self-efficacy. Mastery experiences tend to be predictive of both girls’ and boys’ self-efficacy beliefs in school settings (Usher & Pajares, 2006, 2008). Given the positive influence of self-efficacy on achievement and motivation, a better understanding of gender- and age-related differences in the development of self-efficacy beliefs is needed.
Contemporary Expectancy-Value Theory
Building on the work of Atkinson (1957, 1964) and Weiner (1985), Eccles and colleagues (1983) proposed a social cognitive model of achievement choice for understanding adolescent performance and choice in the domain of mathematics. Eccles et al.’s (1983) model has several unique features that take it beyond traditional expectancy-value models. First, it elaborates upon both the expectancy and value components. Eccles and colleagues challenged Atkinson’s premise that expectancies and values are inversely related. Second, it stresses the fluid nature of the processes underlying choice. The new model identifies developmental sources of children’s and adult’s expectancy and value beliefs. More specifically, the development of expectancies and task values are influenced, directly and interactively, by proximal psychological constructs (e.g., goals and affective memories) as well as by socialization agents such as parents, peers, and teachers. Last, the Eccles et al. (1983) model of achievement motivation emphasizes the role of the cultural milieu of the developing child.
Motivation researchers have used expectancy-value theory as a framework to examine gender differences in motivation and achievement behavior. Originating with the research of Atkinson (1957), expectancy-value theory proposes that individuals are most likely to approach and perform achievement activities when they expect to succeed and when they attach value to that task. The Eccles et al. (1983) model has been applied to different achievement domains (mathematics, science, and sports) as well as career choices and trajectories of young adults. To date, research has identified gender-related differences in key components of the expectancy-value model.
In the Eccles et al. (1983) expectancy-value model of academic choice, competency beliefs are defined as estimations of one’s ability to perform or to succeed at an activity. Research with children, adolescents, and adults has shown that competency beliefs have a particularly strong relation to academic performance (Eccles et al., 1983; Wigfield & Eccles, 1995). Over the past few decades, much has been learned about children’s competency beliefs and gender differences associated with these perceptions. First, as early as first grade, children begin to engage in making judgments about their abilities in a variety of domains, including mathematics, reading, music, and sports (Eccles, Wigfield, Harold, & Blumenfeld, 1993). Second, small gender differences in children’s competency beliefs also emerge in early elementary school (Eccles et al., 1993). These gender differences tend to align with gender-role stereotyped domains and tend to occur on novel tasks. The results of several studies show that boys hold more positive competence beliefs for sports and mathematics, whereas girls hold more positive competence beliefs for instrumental music and reading (Eccles et al., 1993; Jacobs et al., 2002). These gender differences emerge even though boys and girls are performing equally well in these domains (Eccles et al., 1993). However, the sizes of these differences are relatively small and should be interpreted with caution, given that they are dependent on other factors such as stage of development, type of activity, country where the research was conducted, subpopulations within the country, and historical time period (Wigfield et al., 2015).
Cross-sectional and longitudinal research has indicated that children report declines in their competency beliefs as they progress through schooling (Wigfield & Eccles, 2000; Wigfield, Eccles, Yoon, & Harold, 1997), although the precise rate of change is dependent on domain and gender. This research has documented the fact that girls’ perceptions of the math abilities decline at a slower rate than boys’, leading to an overall decrease in the gender gap for mathematics competence over time (Fredericks & Eccles, 2002; Jacobs et al., 2002). In domains other than mathematics, such as language arts, boys’ competence steadily declines in elementary school, and by middle school there are significant differences in boys’ and girls’ competency ratings for language arts. However, these language arts gaps become somewhat small by high school (Jacobs et al., 2002). In sports domains, gender differences favoring boys remain stable across all grades of school (Fredericks & Eccles, 2002; Jacobs et al., 2002).
In the Eccles et al.’s (1983) expectancy-value model of achievement choices, the influence of competence perceptions is moderated by the value attached to achievement activities. Task value is comprised of four components: (1) perceived importance of being good at an activity; (2) perceived usefulness of the activity for obtaining short- or long-term goals; (3) perceived interest or liking of the activity; and (4) perceived cost of engaging in the activity (e.g., time taken away from other activities, amount of effort needed to succeed, etc.). By fifth grade, children are able to differentiate what activities may not hold much interest for them but are necessary to achieving a short- or long-term goal (Eccles et al., 1993). The subjective value of a particular achievement-related activity predicts engagement and participation rates. For example, the value adolescents attach to mathematics predicts their decision to enroll in optional mathematics courses (Eccles, 1994; Feather, 1988; Meece et al., 1990). Similarly, the value attached to sports predicts participation in athletic activities (Eccles & Harold, 1991).
Beginning with elementary school, gender differences are evident in the value children and adolescents attach to different academic domains. As with competency beliefs, the patterns follow gender norms and stereotypes. In a longitudinal study of first- through fourth-grade students, Eccles and her colleagues (1993) reported gender differences favoring boys in the valuing of sports activities (d = .04), whereas girls placed greater value than boys on musical and reading activities (d’s = .06 and .03, respectively). Interestingly, there were no gender differences in the value attached to mathematics for elementary school children. In this study, task values were defined as a composite score representing the perceived interest, enjoyment, importance, and usefulness of an academic domain.
Subsequent studies with older children and adolescents show similar patterns of gender differences in achievement task values. When values were defined as liking of an achievement domain (mathematics, English, and sports), Wigfield and his colleagues (1991) reported that students’ perceptions of the value of mathematics, reading, and sports declined at the transition to junior high school (Grade 7). In general, young adolescents placed more value on social activities and sports than on English and mathematics. As with younger students, girls reported more liking than boys for English (d = .50), whereas boys placed greater value than girls on sports (d = .49). However, more recent research indicates that boys and girls now value math equally, but girls report less interest in physical and computer sciences and engineering compared to boys and do not enroll in these courses during the postsecondary years (Eccles, 2013; Wang, Eccles, & Kenny, 2013). International studies show similar trends. In many countries, girls report valuing math as much as boys do, but they also believe that they are not as good at math and do not aspire to careers involving the physical sciences, computers, and technology at the same rates as boys do (Jerrim & Schoon, 2014)
Summary of Contemporary Theories
Contemporary theories of achievement motivation emphasize motivation beliefs, goals, and aspirations. Of the theories examined in this section, Eccles et al.’s (1983) expectancy-value model of achievement behavior has been the most widely applied in studies of gender differences in achievement motivation. Research using this framework has documented how boys and girls begin school with varying interests and differing views of their abilities. Boys begin school with higher perceptions of their math abilities, whereas girls report higher perceptions of their language arts abilities. Over the course of schooling, gender gaps in the perceptions for mathematics decrease and increase for language arts. In addition, gender differences can vary depending on how task value is defined. For example, when task values are defined as interest and importance, there are no gender differences in students’ valuing of mathematics. Although it seems more likely that declines in competency and value beliefs might happen during or directly after schooling transitions, analyses using growth modeling procedures indicate that the most rapid period of decline in both competency and value perceptions occurs in the elementary school years (Jacobs et al., 2002). Additionally, numerous studies have shown that children’s and adolescents’ competence beliefs are important predictors of their performance in different domains. In contrast, value perceptions are a stronger predictor of students’ choice to participate in an activity or task. Predictive relations for competency and value perceptions are found as early as first grade and increase with age (Eccles, 1994; Eccles et al., 1983; Eccles, Adler, & Meece, 1984; Meece et al., 1990; Wigfield & Eccles, 1992).
Current and Future Trends in Research
Thus far, this article has discussed findings from research on gender and academic motivation both in the United States and abroad and has provided historical and contemporary overviews of theories of achievement motivation. We will now shift to an exploration of current and future trends in research about gender and academic motivation. These current and future trends in research include an altering and expanding of theoretical frameworks, an increased focus on the achievement and motivation of male students, and the proliferation of new methodologies and sources of data.
Shifting and Expanding of Theoretical Frameworks
A decade ago, Perry, Turner, and Meyer (2006) asserted that “contextual understandings are more integral to research on motivation today, reflecting the general shift in educational research toward situated and social perspectives on learning” (p. 328). Since then, researchers have begun to incorporate more contextual variables into the study of student motivation, answering the call of Perry and colleagues (2006) and others.
One theoretical framework that has been used to study the intersection of contextual variables is the Eccles et al. (1983) developmental model of achievement motivation. The Eccles et al. (1983) model has a strong socialization component, which has been used to examine how socialization experiences create and reinforce gender-related differences in motivation and achievement. For example, Eccles, Wong, and Peck (2006) looked at the intersection of ethnicity, motivation, and achievement and reported that daily racial discrimination during seventh and eighth grades predicted declines in grades, academic ability self-concepts, and academic task values. In another study, Graham, Taylor, and Hudley (1998) studied how gender, ethnicity, and discrimination related to motivation. Graham and her colleagues (1998) found that African American boys demonstrated a higher likelihood of devaluing academic success under conditions of racial discrimination. On the other hand, African American girls placed more emphasis on relationships and approval from peers and teachers when self-concepts were threatened by ethnic discrimination. Work by Benner and Graham (2009) featured a Latino sample and documented how perceptions of discrimination were higher for boys and that, cumulatively, higher levels of discrimination had an effect on academic outcomes via the influence on perceptions of school climate. As schools become increasingly ethnically diverse, research that reflects the unique contributions of ethnicity, social class, and community is imperative.
Educational researchers are beginning to integrate variables from different contexts in researching gender and motivation. Hyde (2014) argues that future research focused on gender should move toward intersectionality and situated contexts. Intersectionality refers to simultaneously considering multiple categories of identity, difference, and disadvantage, such as gender, race, class, and sexual orientation (Cole, 2009). This perspective is rooted in the idea that gender cannot be studied or understood apart from context, such as the context of ethnicity or social class. Similarly, a situated perspective on research is, as Turner and Nolen (2015) wrote, “one that interprets individuals’ beliefs and behaviors as arising through their participation in social, cultural, and historical contexts or systems” (p. 168). These paradigms may also be applied to work on gender and academic motivation. One example of taking a situated perspective related to gender and motivation is illustrated by Nolen, Horn, and Ward (2015). These researchers showed how a situative study of a girl’s motivation to become a skilled chess player would include both her interest in becoming competent at chess moves and also her inclination to develop these skills in a local park with elders. They explained that a situated study would consider the fact that the majority of expert chess players are male, how this puts the girl in a particular social position, and how her interactions with others before, during, and after playing chess were integral in studying her chess-related motivation and engagement.
More Research on Male Students
Most of the early work on gender and academic motivation was focused on explaining why girls lagged behind boys in their performance in and motivation for math and science. Research conducted in the 1980s and 1990s highlighted the discrepancies between boys’ and girls’ achievement in and motivation for these academic subjects. As girls achieved relative parity with boys on national and school-based assessments in math and science, another trend began to take shape: boys’ underperformance in school (Cornwell, Mustard, & Van Parys, 2013; Taylor & Lorimer, 2003) and on national assessments (NCES, 2012). Male students currently graduate high school and college at lower rates and do not demonstrate clear aspirations for higher education compared to their female counterparts (Meece & Askew, 2012).
Researchers have applied motivation theories to explain these gender-differentiated trends in academic motivation and achievement. For example, Jacobs et al. (2002) conducted a longitudinal study of 761 students from 10 Midwestern schools and found declines in both girls’ and boys’ competency beliefs, which varied based on domain and gender. These researchers found that boys’ and girls’ perceptions of ability in language arts were similar at the beginning of elementary school, but boys’ ability beliefs declined more rapidly started in the late elementary school. Jacobs et al. (2002) also documented declines in value-related beliefs across the school years for mathematics and language arts subjects. Specifically, boys demonstrated a more rapid decline in language arts than girls. Although these declines in competency and value beliefs may explain gender differences in academic achievement, Jacobs and colleagues (2002) did not specifically examine those relations. Given the trends in boys’ lower academic motivation and achievement, there is a clear need for more research that looks at the mechanisms underlying male students’ underperformance.
Researchers have also used motivation theories to study gender and academic outcomes beyond elementary and middle school. However, studies utilizing motivational constructs to investigate postsecondary aspirations, college enrollment patterns, and postsecondary attainment are few in number. In one very recent study, Meece, Askew, Agger, Hutchins, and Byun (2014) used a nationwide sample of rural youth to investigate how familial, geographic, and economic variables influenced gender-related differences in educational and occupational aspirations. Findings revealed a favoring of girls in terms of educational aspirations, occupational aspirations, and aspirations for nontraditional careers. The study also showed that key motivation variables, particularly school-related values and perceptions of parental educational expectations, predicted rural youths’ gender-related aspirations. Focusing on African American adolescents in the Southeast, another study by Wood, Kurtz-Costes, and Copping (2011) used an expectancy-value framework to test a model linking parental expectations, youths’ motivation, and youths’ postsecondary educational progress. They found gender differences in the youths’ pathways to college, and findings highlighted the importance of academic motivation as a resource for African American boys along their educational trajectories. In another study, using the Michigan Study of Adolescent Life Transitions, Wang (2012) looked at the moderating influence of gender in a longitudinal analysis of classroom environment, motivational beliefs, high school course enrollment, and career aspirations. Consistent with prior research based on Eccles et al. (1983) expectancy-value theory, Wang reported that girls, compared to boys, reported lower math expectancies and intentions to consider careers in math-related fields, even though girls enrolled in just as many math courses, received relatively equivalent grades, and attached similar levels of task values to math as their male peers. Results of the study suggest that classroom influences may play a role in explaining these discrepancies. Taken together, these studies suggest that studies examining gender differences in educational attainment need to include a broad array of sociocultural influences that extend beyond personal beliefs related to academic competencies and values.
New Methodologies and Cross-Cultural Data
This section outlines several recent methodological approaches used by researchers to investigate gender and academic motivation. It also provides information on the proliferation of cross-national datasets researchers are using to explore patterns of gender-related academic motivation and achievement across cultures.
Researchers studying gender and motivation continue to apply increasingly sophisticated quantitative and qualitative methodologies. Person-centered approaches, which take into account both the actual and relative level of one variable to another to form homogeneous groups, are used more and more in work on student motivation. Currently, these approaches are largely used to investigate motivation profiles and achievement (e.g., Conley, 2012; Luo, Paris, Hogan, & Luo, 2011; Wang & Peck, 2013). A recent study by Wang, Eccles, and Kenny (2013) performed latent profile analysis of math and verbal scores to create competence profiles of students. These researchers used profiles to predict occupations at age 33 and found that mathematically capable individuals who also exhibited high verbal skills were less likely to be in STEM careers, compared to individuals with high math skills and moderate verbal skills. Future work could use these new techniques to study gendered patterns of dropout, persistence, and choice. It is also important to continue utilizing mixed methods approaches to studying the more nuanced and layered influences of social context on motivation.
Using Cross-Cultural Data
Although several studies using cross-national data were mentioned at the beginning of this article, a large limitation of much of the gender-related achievement motivation work lies in its limited scope. Research on gender-related motivation patterns has generally stemmed from theory and empirical research generated in the United States and in other industrialized countries (e.g., England, Australia, Germany, and Canada). For example, Watt et al. (2012) examined how gender-related motivational processes affect high school mathematics participation, educational aspirations, and career plans using samples from Australia, Canada, and the United States. However, outside of these industrialized nations, and among more developing nations in particular, there is a dearth of information about the role of student motivation in schooling, especially as it relates to gender.
Some researchers have argued that the scarcity of cross-cultural research has led to Western models of achievement motivation, which are further criticized as being culturally entrenched in an ideology of individualism (Otsuka & Smith, 2005). Cross-national studies are beginning to arise and address whether current findings related to academic motivation and gender can be generalized across myriad nations and cultures (e.g., De Castella, Byrne, & Covington, 2013). This work is especially needed in developing nations.
This article on achievement motivation in education provided historical and contemporary overviews of theories of achievement motivation, discussed findings from research on gender and academic motivation both in the United States and abroad, and outlined current and future trends in research. Moving forward, these current and future trends in research include an altering and expanding of theoretical frameworks, an increased focus on the achievement and motivation of male students, and the proliferation of new methodologies (e.g., person-centered approaches) and sources of data (e.g., cross-national data). Theories of achievement motivation have significantly evolved over the last several decades, and research grounded in these theories influences and informs teaching practices, parent involvement activities in schools, and educational interventions targeted at students, administrators, teachers, and parents.
- Agger, C. A., & Meece, J. L. (2015). Gender and academic motivation. In J. D. Wright (Ed.), International encyclopedia of the social & behavioral sciences (2nd ed., Vol. 9, pp. 677–681). Oxford: Elsevier.
- Anderman, E. M., & Young, A. J. (1994). Motivation and strategy use in science: Individual differences and classroom effects. Journal of Research in Science Teaching, 31(8), 811–831.
- Atkinson, J. W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 64, 359–372.
- Atkinson, J. W. (1964). An introduction to motivation. Oxford: Van Nostrand.
- Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.
- Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
- Bar-Tal, D. (1978). Attributional analysis of achievement-related behavior. Review of Educational Research, 48(2), 259–271.
- Benner, A. D., & Graham, S. (2009). The transition to high school as a developmental process among multiethnic urban youth. Child Development, 80(2), 356–376.
- Bong, M., & Skaalvik, E. M. (2003). Academic self-concept and self-efficacy: How different are they really? Educational Psychology Review, 15(1), 1–40.
- Busch, T. (1995). Gender differences in self-efficacy and attitudes toward computers. Journal of Educational Computing Research, 12(2), 147–158.
- Chiu, M. M., & Chow, B. W. Y. (2010). Culture, motivation, and reading achievement: High school students in 41 countries. Learning and Individual Differences, 20(6), 579–592.
- Cole, E. R. (2009). Intersectionality and research in psychology. American Psychologist, 64(3), 170–180.
- Conley, A. M. (2012). Patterns of motivation beliefs: combining achievement goal and expectancy-value perspectives. Journal of Educational Psychology, 104, 32–47.
- Cornwell, C., Mustard, D. B., & Van Parys, J. (2013). Noncognitive skills and the gender disparities in test scores and teacher assessments: Evidence from primary school. Journal of Human Resources, 48(1), 236–264.
- Crandall, V. C. (1969). Sex differences in expectancy of intellectual and academic reinforcement. In C. P. Smith (Ed.), Achievement-related motives in children (pp. 11–45). New York: Russell Sage Foundation.
- Crandall, V. C., Kathkovsky, W., & Crandall, V. J. (1965). Children’s belief in their own control of reinforcement in intellectual-academic achievement situations. Child Development, 36, 91–109.
- Dar-Nimrod, I., & Heine, S. J. (2006). Exposure to scientific theories affects women’s math performance. Science, 314(5798), 435.
- De Castella, K., Byrne, D., & Covington, M. (2013). Unmotivated or motivated to fail? A cross cultural study of achievement motivation, fear of failure, and student disengagement. Journal of Educational Psychology, 105(3), 861–880.
- Diener, C. I., & Dweck, C. S. (1978). An analysis of learned helplessness: Continuous changes in performance, strategy, and achievement cognitions following failure. Journal of Personality and Social Psychology, 36(5), 451–462.
- DiPrete, T. A., & Buchmann, C. (2013). The rise of women: The growing gender gap in education and what it means for American schools. New York: Russell Sage Foundation.
- Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040–1048.
- Dweck, C. S. (2008). Mindsets and math/science achievement. Report prepared for the Carnegie Corporation of New York-Institute for Advanced Study Commission on Mathematics and Science Education Carnegie Corporation: New York. Retrieved from https://www.growthmindsetmaths.com/uploads/2/3/7/7/23776169/mindset_and_math_science_achievement_-_nov_2013.pdf.
- Dweck, C. S., & Elliot, E. S. (1983). Achievement motivation. In E. M. Hetherington (Ed.), Handbook of child psychology. Socialization, personality, and social development (Vol. 4, pp. 643–691). New York: John Wiley.
- Eccles, J. S. (1994). Understanding women’s educational and occupational choices: Applying the Eccles et al. model of achievement-related choices. Psychology of Women Quarterly, 18, 585–609.
- Eccles, J. (2011). Gendered educational and occupational choices: Applying the Eccles et al. model of achievement-related choices. International Journal of Behavioral Development, 35(3), 195–201.
- Eccles, J. S. (2013). Gender and achievement choices. In E. Gershoff, R. S. Mistry, & D. Crosby (Eds.), Societal contexts of child development: Pathways of influences and implications for practice and policy (pp. 19–34). New York: Oxford University Press.
- Eccles, J. S., & Harold, R. D. (1991). Gender differences in sport involvement: Applying the Eccles’ expectancy-value model. Journal of Applied Sport Psychology, 3, 7–35.
- Eccles, J. S., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Age and gender differences in children’s self- and task perceptions during elementary school. Child Development, 64, 830–847.
- Eccles, J. S., Wong, C. A., & Peck, S. C. (2006). Ethnicity as a social context for the development of African-American adolescents. Journal of School Psychology, 44(5), 407–426.
- Eccles-Parsons, J., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. M. (1983). Expectations, values and academic behaviors. In J. T. Spence (Ed.), Perspective on achievement and achievement motivation (pp. 75–146). San Francisco: Freeman.
- Eccles-Parsons, J. S., Adler, T., & Meece, J. (1984). Sex differences in achievement: A test of alternative theories. Journal of Personality and Social Psychology, 46, 26–43.
- Eccles-Parsons, J. E., Meece, J. L., Adler, T. F., & Kaczala, C. M. (1982). Sex differences in attributions and learned helplessness. Sex Roles, 8(4), 421–432.
- Fast, L. A., Lewis, J. L., Bryant, M. J., Bocian, K. A., Cardullo, R. A., Rettig, M., & Hammond, K. A. (2010). Does math self-efficacy mediate the effect of the perceived classroom environment on standardized math test performance? Journal of Educational Psychology, 102(3), 729–740.
- Farmer, H. S., & Vispoel, W. P. (1990). Attributions of female and male adolescents for real-life failure experiences. Journal of Experimental Education, 58(2), 127–140.
- Feather, N. T. (1988). From values to actions: Recent applications of the expectancy-value model. Australian Journal of Psychology, 40(2), 105–124.
- Fredericks, J. A., & Eccles, J. S. (2002). Children’s competence and value beliefs from childhood through adolescence: Growth trajectories in two male-sex-typed domains. Developmental Psychology, 38(4), 519–533.
- Frieze, I. H. (1975). Women’s expectations for and causal attributions of success and failure. In T. Mednick, S. Tangi, & L. W. Hoffman (Eds.), Women and achievement: Social and motivational analysis (pp. 158–171). New York: John Wiley.
- Frieze, I. H., Parsons, J. E., Johnson, D., Ruble, D., & Zellman, P. (1978). Women and sex roles: A social psychological perspective. New York: Norton.
- Frieze, I. H., Whiteley, B. E., Hanusa, B. H., & McHugh, M. C. (1982). Assessing the theoretical models for sex differences in causal attributions for success and failure. Sex Roles, 8, 333–343.
- Good, C., Rattan, A., & Dweck, C. S. (2007). Adults’ theories of intelligence affects feedback to males and females in math. Unpublished data, Columbia University.
- Graham, S., Taylor, A. Z., & Hudley, C. (1998). Exploring achievement values among ethnic minority early adolescents. Journal of Educational Psychology, 90, 606–620.
- Horner, M. S. (1972). Toward an understanding of achievement-related conflicts in women. Journal of Social Issues, 28(2), 157–175.
- Horner, M. S. (1975). Toward an understanding of achievement-related conflicts in women. In M. Ednick, S. Tangi, & L. W. Hoffman (Eds.), Women and achievement: Social and motivational analyses (pp. 206–220). New York: John Wiley.
- Huang, C. (2013). Gender differences in academic self-efficacy: A meta-analysis. European Journal of Psychology of Education, 28(1), 1–35.
- Hyde, J. S. (2014). Gender similarities and differences. Annual Review of Psychology, 65, 373–398.
- Jacobs, J. E., Lanza, S., Osgood, D. W., Eccles, J. S., & Wigfield, A. (2002). Changes in children’s self-competence and values: Gender and domain differences across grades one though twelve. Child Development, 73(2), 509–527.
- Jerrim, J., & Schoon, I. (2014). Do teenagers want to become scientists? A comparison of gender differences in attitudes toward science, career expectations, and academic skill across 29 countries. In I. Schoon & J. Eccles (Eds.), Gender differences in aspirations and attainment, a life course perspective (pp. 203–223). Cambridge, UK: Cambridge University Press.
- Kloosterman, P. (1990). Attributions, performance following failure, and motivation in mathematics. In E. Fennema & G. C. Leder (Eds.), Mathematics and gender (pp. 96–127). New York: Teachers College Press.
- Licht, B. G., & Dweck, C. S. (1984). Determinants of academic achievement: The interaction of children’s achievement orientations with skill area. Developmental Psychology, 20(4), 628–636.
- Luo, W., Paris, S. G., Hogan, D., & Luo, Z. (2011). Do performance goals promote learning? A pattern analysis of Singapore students’ achievement goals. Contemporary Educational Psychology, 36, 165–176.
- McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). The achievement motive. New York: Appleton-Century-Crofts.
- McMahan, I. D. (1973). Relationships between causal attributions and expectancy of success. Journal of Personality and Social Psychology, 28(1), 108–114.
- Meece, J., Anderman, E. M., & Anderman, L. H. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 505–528.
- Meece, J., & Askew, K. (2012). Gender, motivation, and educational attainment. In K. Harris, S. Graham, T. Urban, S. Graham, J. M. Royer, & M. Zeider (Eds.), APA educational psychology handbook, Vol. 2: Individual differences and cultural and contextual factors (pp. 139–162). Washington, DC: American Psychological Association.
- Meece, J. L., Askew, K. J. S., Agger, C. A., Hutchins, B. C., & Byun, S. (2014). Familial and economic influences on the gender-related educational and occupational aspirations of rural adolescents. Journal of Educational and Developmental Psychology, 4(1), 238–257.
- Meece, J. L., Glienke, B. B., & Burg, S. (2006). Gender and motivation. Journal of School Psychology, 44(5), 351–373.
- Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of math anxiety and its influence on young adolescents’ course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82(1), 60–70.
- National Center for Educational Statistics. (2012). The nation’s report card: Writing 2011 (NCES 2012-470). Washington, DC: US Department of Education,
- National Science Foundation. (2013). Women, minorities, and persons with disabilities in science and engineering: 2013. Retrieved from http://www.nsf.gov/statistics/wmpd/2013/digest/theme2_1.cfm.
- Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91(3), 328–346.
- Nolen, S. B., Horn, I. S., & Ward, C. J. (2015). Situating motivation. Educational Psychologist, 50, 234–247.
- Organisation for Economic Co-operation and Development (OECD). (2011). Report on gender initiative: gender equality in education, employment, and entrepreneurship. Retrieved from http://www.oecd.org/education/48111145.pdf.
- Otsuka, S., & Smith, I. D. (2005). Educational applications of the expectancy-value model of achievement motivation in diverse cultural contexts of West and East. Change: Transformations in Education, 8(1), 91–109.
- Pajares, F. (1996a). Self-efficacy beliefs and mathematical problem-solving of gifted students. Contemporary Educational Psychology, 21(4), 325–344.
- Pajares, F. (1996b). Self-efficacy beliefs in academic settings. Review of Educational Research, 66(4), 543–578.
- Pajares, F., & Valiante, G. (2001a). Gender differences in writing motivation and achievement of middle school students: A function of gender orientation? Contemporary Educational Psychology, 26(3), 366–381.
- Pajares, F., & Valiante, G. (2001b). Influence of self-efficacy on elementary students’ writing. Journal of Educational Research, 90(6), 353–360.
- Parsons [Eccles], J., Adler, T. F., & Kaczala, C. M. (1984). Socialization of achievement attitudes and beliefs: Parental influences. Child Development, 53, 322–339.
- Parsons [Eccles], J. E., Adler, T., & Meece, J. L. (1982). Sex differences in achievement: A test of alternate theories. Journal of Personality and Social Psychology, 46(1), 26–43.
- Parsons [Eccles], J. E., Meece, J. L., Adler, T. F., & Kaczala, C. M. (1982). Sex differences in attributions and learned helplessness. Sex Roles, 8(4), 421–432.
- Parsons [Eccles], J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., & Meece, J. L. (1983). Expectancies, values and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motives (pp. 75–146). San Francisco: Freeman.
- Perry, N. E., Turner, J. C., & Meyer, D. K. (2006). Classroom contexts for motivating learners. In P. Alexander & P. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 327–348). Mahwah, NJ: Lawrence Erlbaum.
- Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33–40.
- Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.
- Schunk, D. H. (1984). Self-efficacy perspective on achievement behavior. Educational Psychologist, 19, 45–58.
- Schunk, D. H., & Pajares, F. (2002). The development of academic self-efficacy. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp. 16–31). San Diego, CA: Academic Press.
- Schunk, D. H., Meece, J. R., & Pintrich, P. R. (2014). Motivation in education: Theory, research, and applications (4th ed.). Upper Saddle River, NJ: Pearson Education.
- Taylor, D., & Lorimer, M. (2003). Helping boys succeed. Educational Leadership, 60(4), 68–70.
- Turner, J. C., & Nolen, S. B. (2015). Introduction: The relevance of the situative perspective in educational psychology. Educational Psychologist, 50(3), 167–172.
- United Nations Educational, Scientific and Cultural Organization (UNESCO). (2015). Gender and education. UNESCO Institute for Statistics. Retrieved from http://www.uis.unesco.org/Education/Pages/gender-education.aspx.
- Usher, E. L., & Pajares, F. (2006). Sources of academic and self-regulatory efficacy beliefs of entering middle school students. Contemporary Educational Psychology, 31(2), 125–141.
- Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751–796.
- Wang, M. T. (2012). Educational and career interests in math: A longitudinal examination of the links between classroom environment, motivational beliefs, and interests. Developmental Psychology, 48(6), 1643–1657.
- Wang, M. T., Eccles, J. S., & Kenny, S. (2013). Not lack of ability but more choice: Individual and gender difference in choice of careers in sciences, technology, engineering, and mathematics. Psychological Sciences, 24(5), 770–775.
- Wang, M. T., & Peck, S. C. (2013). Adolescent educational success and mental health vary across school engagement profiles. Developmental Psychology, 49(7), 1266–1276.
- Watt, H. M., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. (2012). Gendered motivational processes affecting high school mathematics participation, educational aspirations, and career plans: A comparison of samples from Australia, Canada, and the United States. Developmental Psychology, 48(6), 1594–1611.
- Watt, H. M. G. (2008). What motivates females and males to pursue sex-stereotyped careers? In H. Watt & J. Eccles. (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social and cultural influences (pp. 87–113). Washington, DC: APA Books.
- Weiner, B. (1979). A theory of motivation for some classroom experiences. Journal of Educational Psychology, 71(1), 3–25.
- Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–573.
- Weiner, B. (1986). An attributional theory of motivation and emotion. New York: Springer-Verlag.
- Wigfield, A., & Eccles, J. S. (1992). The development of achievement task values: A theoretical analysis. Developmental Review, 12(3), 265–310.
- Wigfield, A., & Eccles, J. S. (1995). Middle grades schooling and early adolescent development: Part II: Interventions, practices, beliefs, and contexts. Journal of Early Adolescence, 15(1), 5–8.
- Wigfield, A., & Eccles, J. S. (2000). Expectancy-value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81.
- Wigfield, A., Eccles, J. S., Fredricks, J. A., Simpkins, S., Roeser, R. W., & Schiefele, U. (2015). Development of achievement motivation and engagement. In M. Lamb & R. Lerner (Eds.), Handbook of child psychology and developmental science (7th ed., Vol. 3, pp. 657–700). Hoboken, NJ: John Wiley.
- Wigfield, A., Eccles, J. S., Mac Iver, D., & Reuman, D. A. (1991). Transitions during early adolescence: Changes in children’s domain-specific self-perceptions and general self-esteem across the transition to junior high school. Developmental Psychology, 27(4), 552–565.
- Wigfield, A., Eccles, J. S., & Pintrich, P. R. (1996). Development between the ages of 11 and 25. In R. C. Calfee & D. C. Berliner (Eds.), Handbook of educational psychology (pp. 148–185). New York: Prentice Hall International.
- Wigfield, A., Eccles, J. S., Yoon, K. S., & Harold, R. D. (1997). Change in children’s competence beliefs and subjective task values across the elementary school years: A 3-year study. Journal of Educational Psychology, 89(3), 451–469.
- Williams, J. D., & Takaku, S. (2011). Gender, writing self-efficacy, and help seeking. International Journal of Business, Humanities and Technology, 1(3), 46–54.
- Wolleat, P. L., Pedro, J. D., Becker, A. D., & Fennema, E. (1980). Sex differences in cognitive functioning: Developmental issue. New York: Academic Press.
- Wood, D., Kurtz-Costes, B., & Copping, K. E. (2011). Gender differences in motivational pathways to college for middle class African American youths. Developmental Psychology, 47(4), 961–968.
- Zimmerman, B. J., & Martinez-Pons, M. (1990). Student differences in self-regulated learning: Relating grade, sex, and giftedness to self-efficacy and strategy use. Journal of Educational Psychology, 82(1), 51–59.