Effect of Student Motivation on Academic Achievement

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In the past several decades, extensive research has been conducted on student motivation. There are different types of influence on a student’s motivation drive to perform well in school (Al‐Dhamit & Kreishan, 2016; Buzdar, Mohsin, Akbar, & Mohammad, 2017; Cleary & Kitsantas, 2017; Corpus, Wormington, & Haimovitz, 2016; Korpershoek, Kuyper, & van der Werf, 2015; Lunnan Hjort, 2015; Vecchione, Alessandri, & Marsicano, 2017). Studies have found, however, that as students enter adolescence, there is a significant decline of academic motivation (Cleary & Kitsantas, 2017; Gnambs & Hanfstingl, 2017; Weidinger, Steinmayr, & Spinath, 2017). Studying this relationship between student motivation and academic achievement seemed very important so that educators and administrators may find a way of increasing academic achievement by focusing on strategies to improve motivation in their students. This research review will explore the question, “How does student motivation affect academic achievement?”

This question is explored by organizing the review of research into two main topics. The studies presented will outline the research conducted and its relevance to the focus question. The first domain concerns motivation types and their effect on academic achievement. The second area of focus is related to possible interventions that may affect student motivation. Finally, at the end of this review of research, the findings will be summarized and the strengths and limitations of the research will be discussed as well as implications for future research.

Review of Literature

Motivation Types and Their Effect on Academic Achievement

Student motivation can play a significant role on academic achievement. Often, intrinsic motivational attributes can be strong predictors of academic outcomes. Cleary and Kitsantas (2017) conducted a study exploring the relations amongst background, motivation, self-regulated learning behaviors, and achievement in middle school math classes. In the study, 331 middle school students and 11 math teachers were given a questionnaire which used four instruments

  • Self-Efficacy for Self-Regulated Learning Scale
  • Task Interest Inventory
  • School Connectedness Scale
  • Self-Regulation Strategy Inventory-Teacher Rating Scale (SRSI-TRS)

Cleary and Kitsantas (2017) found that cognitive and behavioral factors were key mediators in the model, each exhibiting different effects on mathematics performance after controlling for prior achievement. Specifically, they found there were strong correlations between “Task Interest” and “Self-Efficacy” (0.61); “Final Math Grade and Task Interest” (0.45); and “Final Math Grade” and “Self-Efficacy” (0.41). The results of Cleary and Kitsantas’ study supports the claim that student motivation has a significant role on academic achievement. It is important to note, however, that this research study explored several variables together. It might make for a stronger case if just one or two variables were compared. In addition, this study examined one given point in time and it might be worth investigating, via a longitudinal study, how the performance and attitudes of the students change over time.

Buzdar et al. (2017) also completed a study that explored the relationship of academic performance with intrinsic and extrinsic motivation. In the study, 600 masters-level students enrolled at Government College University in Faisalabad, Pakistan were selected from six faculties and twenty departments through a multiphase random-sampling approach. Buzdar et al. (2017) found that the data collected showed a positive and significant relationship between the students’ academic performance and their intrinsic and extrinsic motivation. Strong correlations include “Intrinsic Motivation” and “Assignment and Class Tasks” (0.497) and “Independent Mastery” and “Assignment and Class Tasks” (0.467). Surprisingly, there was a weak correlation between “Curiosity and Comprehension” (0.112). While these findings have the potential to further support the statement that student motivation is significantly related to academic achievement, it must be taken into consideration that all students used in the sample were completing their masters, but no other demographic information was provided which may indicate sample bias. It would be difficult to generalize the results due to this factor.

Corpus et al. (2016) also conducted a study to characterize the intrinsic and extrinsic motivation patterns of students with a focus on motivational orientations, learning strategies, ability validation goals, well-being, and achievement. Two K-8 Catholic schools, located in a middle to upper-middle class neighborhood, were used. All students from grades 3 – 8 were invited to participate. The primarily intrinsic profile showed the most adaptive pattern of responses whereas the primarily extrinsic and low quantity profiles, displayed maladaptive patterns. Using a mixed methods approach allowed the researchers to gain a deeper insight into participant responses, however, just like in the study conducted by Buzdar et al. (2017), there are limits on the external validity since participants came from religiously affiliated schools in a middle to upper middle- class neighborhood. Also, this study has low reliability and validity since it does not thoroughly explain the instruments used.

However, Vecchione et al. (2014) examined a broader sample using the self-determination theory, with a focus on academic motivation of male and female students, to see how it is related to school success. A self-report measure of academic motivation and a measure of general intelligence (Italian version of the Culture-Fair Intelligence Test) was given. Academic achievement was assessed in July (at the end of the school year). Vecchione et al. (2014) also took into account absences from school, SES (parental self-reporting), engagement in learning activities, quality of relationships, and appropriateness of student behavior (rated by the teacher on a scale of 1 to 10). The researchers found that academic motivation was related to a variety of academic outcomes including final grades, attendance, and classroom behavior. These outcomes complement the findings of Cleary and Kitsantas (2017) as well as Buzdar et al. (2017) with respect to strong correlations between motivation and achievement. It is important to note, however, that the predictive value of intrinsic motivation was stronger among female students while the effect of external motivation was found to be stronger for male students. Further research into the differences between male and female motivation and achievement factors may yield information that could be practically applied to the school setting.

In a separate study conducted to address the same research question, Korpershoek et al. (2015) aimed to identify distinct motivation profiles within a sample of 7,257 9th grade students, using the four motivation dimensions in a latent class analysis. Also, this study investigated the relationships between students’ school motivation profiles and several educational outcomes (school commitment, academic self-efficacy, and academic achievement). Using data from a large-scale longitudinal study (COOL5-18 project) a self-report questionnaire was used to obtain the information. Korpershoek et al. (2015) found that on average, the students scored the highest on mastery motivation (3.3 on a 5-point scale), followed by social motivation (3.1), and extrinsic motivation (2.7). The lowest score was found for performance motivation (2.0). This pattern was consistent across all educational tracks. There was a moderate correlation between mastery and performance motivation. There was also a moderate to high correlation between all other combinations of motivation subscales, except for that between performance and social motivation, which was low.  The highest correlation within the four motivation subscales was between performance and extrinsic motivation. The large sample used is from an ongoing longitudinal study (COOL5-18 project) which gives cause for generalizing the results to an even larger population (Korpershoek et al., 2015). This, however, is a cross-sectional study and causal relationships between motivation levels and student achievement cannot be deduced.

In addition to understanding the correlation of student motivation to academic achievement, it is worth noting which age cohorts may experience a decline in motivation. Gnambs and Hanfstingl (2016) investigated the role of the three basic psychological needs for the decline of academic intrinsic motivation in an accelerated longitudinal cohort design among teenaged students. There were two measurement occasions and four motivational styles assessed with four items each of the German Self-Regulation Questionnaire (modified version of the Academic Self-Regulation Questionnaire). Changes in motivational styles were analyzed using latent growth modeling. Gnambs and Hanfstingl (2016) found that intrinsic motivation gradually declined between the ages of 11 and 16 years. The observed decline within one year replicated across all age cohorts. It seemed strongest for the transition from 13 to 14 years. The sharpest decline in intrinsic motivation was between grades 7 and 8. The data collected from this study is consistent and based on the wide variety of school types and locations, it may be plausible to generalize these findings.

In all, there are multiple studies that conclude academic motivation is positively correlated to academic achievement. Cleary and Kitsantas (2017) found the strongest correlation in their research to be between task interest and self-efficacy. This yielded similar results to the study conducted by Buzdar et al. (2017) which found a strong correlation between intrinsic motivation and assignment/class tasks. Interestingly, Vecchione et al. (2014) found there was a difference in student motivation when comparing female and male students. According to their results, female students were more motivated intrinsically, while their male counterparts were motivated by extrinsic factors. Additionally, Korpershoek et al. (2015) found that the students in their sample scored the highest on mastery motivation and the results showed a strong correlation between performance and extrinsic motivation which is in slight contrast to the other studies presented. Finally, Gnambs and Hanfstingl (2016) gathered data documenting a gradual decline in intrinsic motivation in adolescence. This could mean a shift toward student preference for extrinsic motivation, but further research would need to be gathered and analyzed.

Interventions Affecting Student Motivation

While it is understood that student motivation plays a significant role on student achievement (Buzdar et al., 2017; Cleary & Kitsantas, 2017; Corpus et al., 2016; Gnambs & Hanfstingl, 2016; Korpershoek et al., 2015; Vecchione et al., 2017), the next step is in understanding what may affect student motivation. By learning this, educators and administrators may implement practices to positively affect student motivation and thereby increasing student achievement.

Weidinger et al. (2017) investigated whether, and how, changes in students’ intrinsic motivation are related to their grades in math right after grades are implemented in elementary school. There were seven measurement occasions occurring at four-month intervals. The first occurred when students were at the end of second grade and the last measurement occurred approximately two years later. By the end of the study, there were 264 complete data sets. Weidinger et al. (2017) found there were substantial differences in trajectories between students, instead of a uniform decline in intrinsic motivation. Additionally, a change in math grades was only weakly associated with a change in intrinsic motivation. Researchers also discovered the effects of grades on the change in intrinsic motivation were insignificant. Based on this information, grades do not play a significant role in affecting a student’s motivation. It is important to note, however, that the students studied were only from a centralized location in Germany and it may be difficult to generalize the results to students in other countries. In addition, there is no mention as to why, or how, the schools in this region were selected or how the class and children were selected. Also, the instruments used were not clearly stated which leads to low reliability and validity.

Focusing on a different area related to the topic, Trolian, Jach, Hanson, and Pascarella (2016) conducted a longitudinal, multi-institutional study which explored whether or not there was a relationship with academic motivation and student-faculty interactions. Using data collected from the Wabash National Study (WNS) of Liberal Arts Education, students were surveyed at three different data points. Trolian et al. (2016) measured students’ critical thinking, need for cognition, academic motivation, and positive attitude toward literacy, among other factors. Trolian et al. (2016) found that all student-faculty interaction variables had a positive and statistically significant influence on academic motivation. It is worth noting, however, that the sample from WNS does not represent all four-year colleges and universities. In addition, there was significant participant attrition because of the longitudinal nature of the study. This may indicate biased results due to the self-report nature of the study.

In a similar study based on student and teacher interaction, Ruzek, Domina, Conley, Duncan, and Karabenick (2015) examined teacher-associated changes in seventh grade students’ academic achievement and achievement goals. The study drew upon on teacher effectiveness and motivation research in viewing student achievement. Students were surveyed about their achievement goals in math at four data collection points. Seven middle schools from three urban districts were selected. From those schools, 35 teachers who taught in 2004-05 and/or 2005-06 were used, along with all of their enrolled students, amounting to 2,026 student participants. At the conclusion of the study, Ruzek et al. (2015) found that by eighth grade, the mean performance-approach and performance avoidance goal levels fall below the overall sample average, when it was above average the year prior. Ruzek et al. (2015) also found that seventh grade students experienced the largest decreases within the school year across all goal types. Most surprisingly, a student assigned to a teacher who is 1.0 SD above the mean on the achievement value added distribution scale, learns 0.12 SD more during seventh grade than they would with a teacher who was at the mean (Ruzek et al., 2015). In addition, there was a 0.66 correlation between teacher contribution to performance approach and teacher contribution to performance-avoidance goals which indicated that variation in teacher influence on one performance goal can explain 44% of variance in teacher influence on the other (Ruzek et al., 2015). This study, however, did not explicitly say what approaches the teachers took (or did not take) that may have impacted student outcomes. The outcome of this study corroborates the findings of Trolian et al. (2016) in that student-teacher interaction may play a significant role in promoting student motivation, thereby improving academic achievement.

In another study, Hawlitschek and Joeckel (2017) investigated the effects of learning instruction on various student outcomes including intrinsic motivation, cognitive load, and learning with a digital educational game. This was an experimental design study with a digital survey. The experimental group was told they were going to play an educational game, answer questions about it afterwards, and to learn as much as they can. The control group was told they were going to play a game and to have fun. Students played the game in their schools’ computer labs. Both groups filled out a survey afterwards measuring intrinsic motivation, mental effort, extraneous cognitive load, and learning performance (based on recall and transfer knowledge). Hawlitschek and Joeckel (2017) found there was a significant effect on transfer knowledge in favor of the experimental group, but no significant effect on recall. It was also discovered that there was no significant difference between either group and their intrinsic motivation. The experimental group reported a significantly higher extraneous cognitive load. There are several factors which affect the reliability of this study. For example, only one type of game educational game was used, and the results may vary based on the subject or genre of the game. Also, there is no mention as to how the schools were selected or the students within those schools. Finally, student demographic information, other than gender, is not stated, making it difficult to generalize the findings.

In another study, Im, Hughes, Cao, and Kwok (2016) conducted a year-long longitudinal inquiry which investigated the role of activity context, duration of participation, and the youth’s gender and ethnicity on effects of participation in extracurricular activities during the middle school grades on academic motivation and achievement. Students were recruited at the end of first grade and interviewed in seventh and eighth grade based on assessed outcomes such as academic competence beliefs; subjective valuing of academic achievement; academic effort and attainment; students’ course grades; and teacher related behavioral engagement. There were 1,374 children eligible for the study and by the end of the study, 569 of those children were still included based on the response rate. Students were selected to participate based on if they scored below the median on a district-administered test of literacy given in the spring of Kindergarten or the fall of first grade. Im et al. (2016) found that continuous participation in sports had a significant positive effect on ninth grade academic confidence beliefs and valuing of education. The association between education belief and academic competence belief, and between teacher-rated engagement and letter grade, were also strong. It is worth noting, that the results may not generalize for samples of students entering school with above average literacy skills. The sample population was also predominantly low SES. In addition, the categorization of sports and performing arts/clubs does not specify the variation within each. Finally, similar to the study conducted by Trolian et al. (2016), there was a significant subject attrition rate, which again, may signify bias in the results.

According to the studies presented there are some ways in which a student’s motivation can be directly influenced in order to improve academic achievement. In particular, there is a strong correlation between student and teacher interaction (Ruzek et al., 2015; Trolian et al., 2016). While the study conducted by Trolian et al. (2016) showed a statistically significant correlation of student and teacher interaction to academic motivation, the study did not mention the specific ways in which the interactions took place. The same can be said for Ruzek et al. (2015), who did not explicitly mention the strategies used to improve student outcomes. Interestingly, student motivation can be influenced by factors outside of the school setting. In the study conducted by Im et al. (2016), it was found that students who participated in ongoing extracurricular activities had a significant effect on academic confidence belief. Finally, the introduction of letter grades was found not to have any influence on student motivation, whether positively or negatively (Weidinger et al., 2017). Based upon the studies collected, the most impactful way a school organization can influence student motivation and academic achievement would be through improving student and teacher interactions. More research would need to be conducted in order to ascertain explicit strategies, as these were not presented in the studies gathered.

Conclusion

The research presented in this review generally answers the question, “How does student motivation affect academic achievement?”. This was an important question to answer because educators and administrators are constantly searching for ways to increase academic achievement, but it is necessary to understand how student motivation may affect academic outcomes first. In this review, multiple studies confirmed that there is a significant and positive relationship of student motivation to academic achievement (Buzdar et al., 2017; Cleary & Kitsantas, 2017; Corpus et al., 2016; Gnambs & Hanfstingl, 2016; Korpershoek et al., 2015; Vecchione et al., 2017). In all of these studies, a strong correlation was found to support the claim that academic achievement is influenced by student intrinsic and extrinsic motivational factors and the results gathered were consistent with one another. In addition, this review highlights direct interventions that impact student motivation. The strongest intervention, based upon the validity of the studies to support it, would be that student and teacher interaction has a significant impact on student motivation and academic achievement (Ruzek et al., 2015; Trolian et al., 2016).

There are limitations to some of the studies presented in this review. Many of the research designs used were longitudinal studies. While this can be an effective way of studying a variable over time, such as a students’ change in intrinsic motivation over time, there was also significant subject attrition in some of the studies presented (Im et al., 2016; Trolian et al., 2016; Weidinger et al., 2017). Based on the response rate and self-reporting nature of the studies, this may signify bias in the sample remaining. In addition, some studies presented in this review did not explicitly report the measures of validity used as is the case in the study conducted by Buzdar et al. (2017) which did not present details on how the survey used was administered.  Another limitation would be the sampling size of some of the studies. While the research design was promising, the limited number of participants makes it difficult to generalize the results to a larger population.

There are many implications for future research that have surfaced after conducting this review. First, a better understanding of the causes of student motivation would benefit school officials and educators, alike when planning for and implementing newer strategies. In addition, some of the research presented made note of the fact that intrinsic motivation declines when students enter adolescence (Cleary & Kitsantas, 2017; Gnambs & Hanfstingl, 2017; Weidinger et al., 2017). It would be worth investigating the cause for this decline so that educators and administrators can try to counteract the effects. In addition, Vecchione et al. (2014) found that female students are more intrinsically motivated than their male counterparts. While male students are more driven by extrinsic motivational factors. Further research into the difference in gendered motivational factors would be suggested for a future study.

References

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