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 LiteratureMotivation Types and Their Effect on Academic AchievementStudent 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 instrumentsSelf-Efficacyfor Self-Regulated Learning ScaleTaskInterest InventorySchoolConnectedness ScaleSelf-RegulationStrategy Inventory-Teacher Rating Scale (SRSI-TRS)Cleary and Kitsantas (2017) found that cognitive and behavioral factors were key mediators inthe model, each exhibiting different effects on mathematics performance aftercontrolling for prior achievement. Specifically, they found there were strongcorrelations between “Task Interest” and “Self-Efficacy” (0.61); “FinalMath Grade and Task Interest” (0.45); and “Final Math Grade” and“Self-Efficacy” (0.41). The results of Cleary and Kitsantas’ study supports theclaim that student motivation has a significant role on academic achievement.It is important to note, however, that this research study explored severalvariables together. It might make for a stronger case if just one or twovariables were compared. In addition, this study examined one given point intime and it might be worth investigating, via a longitudinal study, how theperformance 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 tocharacterizethe intrinsic and extrinsic motivation patterns of students with a focus on motivational orientations, learningstrategies, ability validation goals, well-being, and achievement. Two K-8Catholic schools, located in a middle to upper-middle class neighborhood, wereused. All students from grades 3 – 8 were invited to participate. The primarily intrinsicprofile showed the most adaptive pattern of responses whereas the primarilyextrinsic and low quantity profiles, displayed maladaptive patterns. Using a mixed methods approach allowed theresearchers to gain a deeper insight into participant responses, however, justlike in the study conducted by Buzdar et al. (2017), there are limits on theexternal validity since participants came from religiously affiliated schoolsin a middle to upper middle- class neighborhood. Also, this study has lowreliability and validity since it does not thoroughly explain the instrumentsused.However, Vecchioneet 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 itis related to school success. A self-report measure of academic motivation anda measure of general intelligence (Italian version of the Culture-FairIntelligence Test) was given. Academic achievement was assessed in July (at theend of the school year). Vecchione et al. (2014) also took into accountabsences from school, SES (parental self-reporting), engagement in learningactivities, quality of relationships, and appropriateness of student behavior(rated by the teacher on a scale of 1 to 10). The researchers found thatacademic motivation was related to a variety of academic outcomes includingfinal grades, attendance, and classroom behavior. These outcomes complement thefindings of Cleary andKitsantas (2017) as well as Buzdar et al. (2017)with respect to strong correlations between motivation and achievement. It isimportant to note, however, that the predictive value of intrinsic motivationwas stronger among female students while the effect of external motivation wasfound to be stronger for male students. Further research into thedifferences between male and female motivation and achievement factors mayyield information that could be practically applied to the school setting.In a separatestudy conducted to address the same research question, Korpershoek et al.(2015) aimed to identify distinct motivation profiles within asample of 7,257 9th grade students, using the four motivation dimensions in alatent class analysis. Also, this study investigated the relationships betweenstudents’ school motivation profiles and several educational outcomes (schoolcommitment, academic self-efficacy, and academic achievement). Using data froma large-scale longitudinal study (COOL5-18 project) a self-report questionnairewas used to obtain the information. Korpershoek et al. (2015) found that on average, thestudents 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 lowestscore was found for performance motivation (2.0). This pattern was consistentacross all educational tracks. There was a moderate correlation between masteryand performance motivation. There was also a moderate to high correlationbetween all other combinations of motivation subscales, except for that betweenperformance and social motivation, which was low.  The highest correlation within the fourmotivation subscales was between performance and extrinsic motivation. The large sample usedis from an ongoing longitudinal study (COOL5-18 project) which gives causefor generalizing the results to an even larger population (Korpershoek et al.,2015). This, however, is a cross-sectional study and causal relationshipsbetween motivation levels and student achievement cannot be deduced.In addition to understanding the correlationof student motivation to academic achievement, it is worth noting which agecohorts may experience a decline in motivation. Gnambs and Hanfstingl (2016) investigatedthe role of the three basic psychological needs for the decline of academicintrinsic motivation in an accelerated longitudinal cohort design amongteenaged students. There were two measurement occasions and fourmotivational styles assessed with four items each of the German Self-RegulationQuestionnaire (modified version of the Academic Self-Regulation Questionnaire).Changes in motivational styles were analyzed using latent growth modeling. Gnambsand Hanfstingl (2016) found that intrinsic motivation gradually declinedbetween the ages of 11 and 16 years. The observed decline within one yearreplicated across all age cohorts. It seemed strongest for the transition from13 to 14 years. The sharpest decline in intrinsic motivation wasbetween grades 7 and 8. The data collected from this study is consistentand based on the wide variety of school types and locations, it may beplausible to generalize these findings. In all, there are multiple studies thatconclude academic motivation is positively correlated to academic achievement. Clearyand Kitsantas (2017) found the strongest correlation in their research to bebetween task interest and self-efficacy. This yielded similar results to thestudy conducted by Buzdar et al. (2017) whichfound a strong correlation between intrinsic motivation and assignment/classtasks. Interestingly, Vecchione et al. (2014) found there was adifference 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 samplescored the highest on mastery motivation and the results showed a strongcorrelation between performance and extrinsic motivation which is in slightcontrast to the other studies presented. Finally, Gnambs and Hanfstingl (2016) gathered datadocumenting a gradual decline in intrinsic motivation in adolescence. Thiscould mean a shift toward student preference for extrinsic motivation, butfurther research would need to be gathered and analyzed.Interventions Affecting Student MotivationWhile 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 thetopic, Trolian, Jach, Hanson, and Pascarella (2016) conducted a longitudinal,multi-institutional study which explored whether or not there was arelationship with academic motivation and student-faculty interactions. Usingdata collected from the Wabash National Study (WNS) of Liberal Arts Education,students were surveyed at three different data points. Trolian et al. (2016) measuredstudents’ critical thinking, need for cognition, academic motivation, andpositive attitude toward literacy, among other factors. Trolian et al. (2016) foundthat all student-faculty interaction variables had a positive and statisticallysignificant influence on academic motivation. It is worth noting, however, thatthe sample from WNS does not represent all four-year colleges and universities.In addition, there was significant participant attrition because of thelongitudinal nature of the study. This may indicate biased results due to theself-report nature of the study. In a similar study based on student andteacher interaction, Ruzek, Domina, Conley, Duncan, and Karabenick (2015) examinedteacher-associated changes in seventh grade students’ academic achievement andachievement goals. The study drew upon on teacher effectiveness and motivationresearch in viewing student achievement. Students were surveyed about theirachievement goals in math at four data collection points. Seven middle schoolsfrom three urban districts were selected. From those schools, 35 teachers whotaught in 2004-05 and/or 2005-06 were used, along with all of their enrolledstudents, amounting to 2,026 student participants. At the conclusion of thestudy, Ruzek et al. (2015) found that by eighth grade, the meanperformance-approach and performance avoidance goal levels fall below theoverall sample average, when it was above average the year prior. Ruzek et al.(2015) also found that seventh grade students experienced the largest decreaseswithin the school year across all goal types. Most surprisingly, a studentassigned to a teacher who is 1.0 SD above the mean on the achievement value addeddistribution scale, learns 0.12 SD more during seventh grade than they wouldwith a teacher who was at the mean (Ruzek et al., 2015). In addition, there wasa 0.66 correlation between teacher contribution to performance approach andteacher contribution to performance-avoidance goals which indicated thatvariation in teacher influence on one performance goal can explain 44% ofvariance in teacher influence on the other (Ruzek et al., 2015). This study,however, did not explicitly say what approaches the teachers took (or did nottake) that may have impacted student outcomes. The outcome of this studycorroborates the findings of Trolian et al. (2016) in that student-teacherinteraction may play a significant role in promoting student motivation, therebyimproving academic achievement.In another study, Hawlitschek and Joeckel(2017) investigated the effects of learning instruction on various studentoutcomes including intrinsic motivation, cognitive load, and learning with adigital educational game. This was an experimental design study with a digitalsurvey. The experimental group was told they were going to play an educationalgame, 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 filledout a survey afterwards measuring intrinsic motivation, mental effort,extraneous cognitive load, and learning performance (based on recall and transferknowledge). Hawlitschek and Joeckel (2017) found there was a significant effecton transfer knowledge in favor of the experimental group, but no significanteffect on recall. It was also discovered that there was no significantdifference between either group and their intrinsic motivation. Theexperimental group reported a significantly higher extraneous cognitive load. Thereare several factors which affect the reliability of this study. For example, onlyone type of game educational game was used, and the results may vary based onthe subject or genre of the game. Also, there is no mention as to how theschools were selected or the students within those schools. Finally, studentdemographic information, other than gender, is not stated, making it difficultto generalize the findings.In another study, Im, Hughes, Cao, and Kwok(2016) conducted a year-long longitudinal inquiry which investigated the roleof activity context, duration of participation, and the youth’s gender andethnicity on effects of participation in extracurricular activities during themiddle school grades on academic motivation and achievement. Students wererecruited at the end of first grade and interviewed in seventh and eighth gradebased on assessed outcomes such as academic competence beliefs; subjectivevaluing of academic achievement; academic effort and attainment; students’course grades; and teacher related behavioral engagement. There were 1,374children eligible for the study and by the end of the study, 569 of thosechildren were still included based on the response rate. Students were selectedto participate based on if they scored below the median on adistrict-administered test of literacy given in the spring of Kindergarten orthe fall of first grade. Im et al. (2016) found that continuous participationin sports had a significant positive effect on ninth grade academic confidencebeliefs and valuing of education. The association between education belief andacademic competence belief, and between teacher-rated engagement and lettergrade, were also strong. It is worth noting, that the results may notgeneralize for samples of students entering school with above average literacyskills. The sample population was also predominantly low SES. In addition, thecategorization of sports and performing arts/clubs does not specify thevariation within each. Finally, similar to the study conducted by Trolian etal. (2016), there was a significant subject attrition rate, which again, maysignify bias in the results.According to the studies presented there aresome ways in which a student’s motivation can be directly influenced in orderto improve academic achievement. In particular, there is a strong correlationbetween student and teacher interaction (Ruzek et al., 2015; Trolian et al., 2016).While the study conducted by Trolian et al. (2016) showed a statisticallysignificant correlation of student and teacher interaction to academicmotivation, the study did not mention the specific ways in which theinteractions took place. The same can be said for Ruzek et al. (2015), who didnot 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 whoparticipated in ongoing extracurricular activities had a significant effect onacademic confidence belief. Finally, the introduction of letter grades wasfound not to have any influence on student motivation, whether positively ornegatively (Weidinger et al., 2017). Based upon the studies collected, the mostimpactful way a school organization can influence student motivation andacademic achievement would be through improving student and teacherinteractions. More research would need to be conducted in order to ascertainexplicit strategies, as these were not presented in the studies gathered.ConclusionThe 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.ReferencesAl?Dhamit, Y., & Kreishan, L. (2016). Gifted students’ intrinsic and extrinsic motivations and         parental influence on their motivation: From the self?determination theory perspective. Journal of Research in Special Educational Needs, 16(1), 13-23. doi:10.1111/1471-3802.12048Buzdar, M. A., Mohsin, M. N., Akbar, R., & Mohammad, N. (2017). Students’ academic     performance and its relationship with their intrinsic and extrinsic motivation. Journal of            Educational Research, 20(1), 74-82.Cleary, T. J., & Kitsantas, A. (2017). Motivation and self-regulated learning influences on middle school mathematics achievement. School Psychology Review, 46(1), 88-107.Corpus, J. H., Wormington, S. 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Academic motivation predicts educational attainment: Does gender make a difference? Learning and Individual Differences, 32, 124-131. doi:10.1016/j.lindif. 2014.01.003Weidinger, A. F., Steinmayr, R. and Spinath, B. (2017), Math grades and intrinsic motivation in    elementary school: A longitudinal investigation of their association. Br J Educ Psychol, 87: 187–204. doi:10.1111/ bjep.12143Get Help With Your AssignmentIf you need assistance with writing your assignment, our professional assignment writing service is here to help!Find out more