Potential reciprocal relationship between motivation and achievement: A longitudinal study

Abstract

Among the non-cognitive factors that influence academic achievement, intrinsic motivation has been found to be a potential reciprocal factor. The present study aims to determine the causal relationship between other types of motivation and academic achievement. For this purpose, a large-scale data survey, the National Education Longitudinal Study of 1988 (NELS88), was used. The results revealed that test-taking motivation and achievement were bi-directional influences in that grade 10 mathematics scores greatly predicted grade 12 test-taking motivation and that test-taking motivation predicted subsequent mathematics scores with a smaller effect. Moreover, although intrinsic motivation was found to predict subsequent mathematics scores, no bi-directional influence was captured. The results indicate that intrinsic motivation greatly promotes academic achievement and that there is a potential reciprocal relationship between the extrinsic motivations and academic performance of students.

Keywords

academic performance causal relationship intrinsic motivation longitudinal study test-taking motivation

Extensive research has found that learning motivation and academic achievement may have a bi-directional influence. That is, the motivational factors, particularly intrinsic motivation, directly enhance academic achievement (for a review, see Hattie, 2009), whereas individual motivation may be enhanced by the obtained achievements in late school years (Köller, Baumert, & Schnabel, 2001; Marsh, Trautwein, Lüdtke, Köller, & Baumert, 2005). However, the discussion of extrinsic motivation and achievement is mostly restricted to the correlated debate, that is, extrinsic motivation is either positively or negatively related to performance (Amabile, Hill, Hennessey, & Tighe, 1994). The aim of the present study is to determine the potential causal relationship between motivational factors (i.e., intrinsic and test-taking motivation), which are considered simultaneously, and academic achievement. Data from a large scale longitudinal study, the National Education Longitudinal Study of 1988 (NELS88), were used in the present study, and a cross-lag model was used to estimate the relationship.

Intrinsic and extrinsic motivation

In any discussion regarding intrinsic motivation, self-determination theory (SDT) (Deci & Ryan, 1985, 2000; Ryan & Deci, 2000a) should be cited. The origin of SDT is an autotelic orientated perspective on individual agency (e.g., Csikszentmihalyi, 1975; De Charms, 1968). SDT theorists assert that human beings have inherent propensities to be intrinsically motivated, to assimilate their environment, and to integrate external regulations into self-regulations (for a review, see Deci & Ryan, 2012; Reeve, 2012; Vansteenkiste, Niemiec, & Soenens, 2010). SDT theorists also believe that intrinsic motivations are those motives that arise when an activity satisfies basic human needs (Deci, 1971).

As defined by Ryan and Deci (2000b), intrinsic motivation refers to ‘the primary propensity of organisms to engage in activities that interest them and, in doing so, to learn, develop, and expand their own capacities’ (p.16). From this definition, it is evident that there are two important components of intrinsic motivation. First, intrinsic motivation is situated within the individual rather than in external pressures, and furthermore, it is driven by interests in the task itself. Second, intrinsic motivation is to ‘seek out novelty and challenges, to extend and exercise one’s capacities, to explore, and to learn’ (Ryan & Deci, 2000a, p. 70).

Conversely, extrinsic motivation results from influences outside of the activity. In accordance with Ryan and Deci (2000a)’s definition, extrinsic motivation refers to ‘the performance of an activity in order to attain some separable outcome’ (p.71). Similar perspectives raised by other researchers indicate that extrinsic motivation is characterized by an instrumental purpose that is desired by separate consequences (Eccles & Wigfield, 2002; Simons, Vansteenkiste, Lens, & Lacante, 2004). Accordingly, monetary rewards and grades are commonly used extrinsic motivators to promote a desired behaviour.

However, the more sophisticated consideration is that the external factors may play significantly different roles (e.g., Deci & Ryan, 1985). Even if the drive is from outside the activity, individuals may perceive the activity quite differently. For example, when a reward is given to a student, the student can either interpret the reward as informational (i.e., the reward reveals one’s competence) or as controlling (i.e., the reward compels one to achieve). Accordingly, the key question goes to the interpretation/perception of the individual as the external events have both controlling and informational value. In other words, when students perceive that external events are controlling, their intrinsic motivation may be diminished. However, when they feel that the external events are informational, their intrinsic motivation is heightened (see Deci & Ryan, 1985, 2012). This leads to a broader definition of autonomy motivation (Deci & Ryan, 1985). This broader definition states that if a person associates the reward of the satisfaction with the activity itself, he/she can treat the event as an autonomous motivator, even if the reward is an extrinsic motivator (Vansteenkiste, Lens, & Deci, 2006).

In educational settings, extrinsic motivation differs from that in experimental studies. Monetary rewards are seldom provided in schools. In this case, the pursuit of grades, scores, or academic performance becomes a common indicator of extrinsic motivation. Specifically, test-taking motivation is an important motivational factor that has been widely considered by previous researchers (e.g., Arvey, Strickland, Drauden, & Martin, 1990; Eklöf, 2010; Sanchez, Truxillo, & Bauer, 2000). Test-taking motivation can be regarded as a specific form of achievement motivation, which refers to the motivation to perform well on a given test (Arvey et al., 1990; Eklöf, 2010). It also shows the willingness of working on test items and investing persistence in testing situations (Baumert & Demmrich, 2001). The measurement of test-taking motivation mainly involves the measure of external motivation (e.g., aims to be the top scorer; pushes oneself to work on the test) and that of identified motivation (e.g., doing well on the test is important; this is a very important test to me, see Arvey et al., 1990; Wolf & Smith, 1995 for item details). Particularly, external motivation has been found to be significantly associated with test takers’ desire for a good score (Sanchez et al., 2000). Since the pursuit of scores or grades is regarded as one’s extrinsic motivation, test-taking motivation is thus an aspect reflecting one’s extrinsic value in the subject.

In summary, SDT regards intrinsic motivation as a type of motive that originates from an individual. As such, SDT includes individual’s interest and his/her seeking of challenges, which culminates in feelings of autonomy and competence. For extrinsic motivation, SDT includes the motive internalized into one’s own value (e.g., the importance of doing something), as well as external motivation that was caused by the external incentives (Deci & Ryan, 1985, 2000). In the present study, we mainly focus on test-taking motivation, which reflects one’s internalized value and external pursuit at the same time (Arvey et al., 1990).

Motivation and academic achievement

Correlation between motivation and academic achievement

Based on previous research using a cross-sectional approach to examine correlational relationships, motivation is a non-cognitive component that correlates with performance (see Hattie, 2009 for a review) as evidenced by the positive relationship between intrinsic motivation and academic achievement, a finding that has long been documented by many studies (e.g., Froiland & Oros, 2014; Vansteenkiste, Simons, Lens, Soenens, & Matos, 2005). The SDT perspective states that outward pressures may undermine autonomous motivation and thereby be counterproductive to students’ learning and academic growth. Furthermore, SDT theorists stress the importance of intrinsic autonomy, arguing that it may satisfy students’ needs for competence and well-being and facilitate their adjustment to school and their engagement in deep learning, etc. (e.g., Reeve, Jang, Hardre, & Omura, 2002; Ryan & Brown, 2005; Vansteenkiste, Simons, Lens, Sheldon, & Deci, 2004).

However, the SDT perspective somehow contrasts with education’s tendency to focus on incentives, accountability, and high-stake tests (Deci & Ryan, 2012). Success in academic achievement involves performing deliberate, effortful, and challenging exercises, such as studying and doing homework (Burton, Lydon, D’Alessandro, & Koestner, 2006). Particularly, in terms of test performance as the outcome, test-taking motivation has a strong association with the obtained scores (Sanchez et al., 2000; Sundre & Kitsantas, 2004). Accordingly, it is probable that the intrinsically motivated status should be accompanied by some long-term regulations. Csikszentmihalyi and Wong (2014) distinguished intrinsic motivation and work orientation, arguing that, unlike intrinsic motivation based on on-going self-experience, work orientation reflects long-term goals, such as fulfilling one’s life-long expectations, which cannot be satisfied immediately. Individuals must invest a substantial amount of time in learning, which is significantly related to work orientation rather than related to their immediate experiences. Lepper, Master, and Yow (2008), in laboratory and educational settings, distinguished between the roles of both types of motivation in terms of different outcomes. Generally, their laboratory studies revealed the negative effects of extrinsic motivation, whereas in educational surveys when considering academic outcomes, both types of motivation facilitate. Individuals with limited options performed better in the area of essay writing and reported greater subsequent satisfaction with their selections.A recent meta-analysis (Cerasoli, Nicklin, & Ford, 2014) also revealed that under conditions that provide no compensation, intrinsic motivation exhibited a lower correlation rate (r = 0.27) with performance than when directly salient compensation (external rewards highly linked to the task or performance, r = 0.30) or indirectly salient compensation (r = 0.45) was provided. The results indicate that there is no reason why educators should not provide both types of motivation. Further, they posit that the two types of motivation should not necessarily by positively or negatively correlated.

To support the positive prediction regarding both types of motivation, Hidi (2015) revisited the studies on the psychological perspective and compared the results from psychological research with the findings from neuroscience. She found that from the neuroscience perspective, rewards do enhance learning behaviour and that whether the reward is intrinsically or extrinsically given, neural activities are recorded. The difference is that in extrinsic reward situations, despite the activity in certain regions of the brain, which differ from that for intrinsic reward situations, the evaluation systems are activated (Lee & Reeve, 2012). As more evidence indicates that the response time is greater for the extrinsic condition (Kable & Glimcher, 2007), it is surmised that there might be an enacting effect of extrinsic motivation.

A similar finding was obtained by De Brabander and Martens (2014), whose review borrowed from the neuroscience perspective when redefining the relevant theories. The authors considered that according to SDT, intrinsic motivation is a type of inner drive of the affective domain. When intrinsically motivated, people are likely to be aroused by a series of positive feelings, such as enjoyment and interest. The affect is associated with motivation systems that rely on subcortical regions of the brain such as the amygdala, insular cortex and ventromedial prefrontal cortex (Reeve & Lee, 2012). On the contrary, extrinsic motivation, such as a reward, occurs in areas of cognitive control, as it requires recognition and evaluation. Accordingly, these cognitive controls appear to enact the cortical region, such as the prefrontal and parietal cortexes. Based on such evidence, De Brabander and Martens classified intrinsic motivation as an affective concept, whereas extrinsic motivation is considered to be a cognitive concept. According to the new definition, the affective process refers to the positive feelings experienced while engaging in the activity thus producing autonomic feelings. Conversely, cognitive process indicates the articulation and valuation of expected consequences of the activities, which is reflected as the individual engaged in the activities. Though affective and cognitive valences are independent, their responses may be simultaneous.

Causal relationship between motivation and achievement

With respect to the studies exploring the causal relationship between motivation and achievement, it has been well documented that specific methods should be employed to detect the causal relationship. In educational settings, the longitudinal method is often used to detect such a relationship. Recent studies have considered school achievement to be an outcome variable where motivational status includes interest, self-efficacy, task value, and self-concept, all of which can predict achievement and achievement growth (Alivernini & Lucidi, 2011; Hornstra, van der Veen, Peetsma, & Volman, 2013; Wang &Eccles, 2013). Longitudinal studies also have revealed that motivation could be an effective factor influencing subsequent ability, academic achievement, and performance (e.g., Gottfried, Fleming, & Gottfried, 2001; Harackiewicz, Barron, Tauer, & Elliot, 2002; Oliver & Simpson, 1988).

It is unique that SDT emphasizes that the instructional task of promoting student intrinsic motivation is the key point in facilitating school engagement (Reeve & Halusic, 2009). In this sense, intrinsic motivation influences school achievement through the change of the behaviour engaged in school. When students are highly intrinsically motivated, they are more willing to solve the relevant task, love the subject, and thus choose to do the school work; the increase of the school behaviour and engagement promotes the final outcomes. For example, Froiland and Worrell, (2016) showed that intrinsic motivation predicts high school engagement, thus predicting school achievement for the 9th graders. This was replicated for older students from different samples, where intrinsic motivation increased the mathematic course-taking behaviour, which in turn yielded higher achievement outcomes (Froiland & Davison, 2016). An intervention study with a group of grade 7 students showed that the increase of intrinsic motivation promoted school engagement, goals, and thus grades (Grolnick, Farkas, Sohmer, Michaels, & Valsiner, 2007).Teachers can promote these resources during the flow of instruction to facilitate high-quality student study behaviours (Niemiec & Ryan, 2009).

However, there are very few studies that have detected a possible bi-directional relationship between motivation and achievement, and furthermore, the findings have been mixed. For example, Morgan and Fuchs (2007) reviewed studies in educational settings and showed that reading ability and reading motivation (e.g., competence, interest, goal orientations) should have a bidirectional relationship. Köller et al. (2001), who argued that student interest was an important factor in enhancing mathematics, revealed that a high interest level (grade 10) had a direct influence on future mathematics achievement (grade 12). Such an influence was not found to be related to a low degree of interest (grade 7). Furthermore, there was no direct influence of grade 10 achievement on grade 12 interest. On the contrary, such influence was captured from grade 7 achievement to grade 10 interest. Cross-lagged analyses by Skaalvik and Valås (1999) showed that mathematics and verbal achievement predicted the subsequent intrinsic motivation (interest and investment) in grade 6 and grade 8 cohorts. For grade 3 students, the influence from achievement to motivation was not observed. Marsh et al. (2005), using the same approach with a sample of students who were approximately 13-years-old, illustrated that the paths from initial interests at the beginning of grade 7 to grades and achievement test scores at the mid-term of grade 7 were statistically significant, albeit relatively small, whereas the opposite path, i.e., from initial grades to later interests, was not significant. As for the college students, previous academic achievements (e.g., SAT performance) did not predict the course motivation (Harackiewicz et al., 2002).

Although with some exceptions, these findings suggest that the achievement may influence motivation in late school years (from grade 6 to grade 9). It might be a distal route from achievement to motivation where some mediators could exist. Achievement may indirectly affect interest through the mediation of self-concept (Bouffard, Marcoux, Vezeau, &Bordeleau, 2003; Denissen, Zarrett, &Eccles, 2007; Marsh et al., 2005). So the influence from achievement to motivation may be small and trivial compared to the influence from motivation to achievement. For students in junior high school, it is of great possibility that their declining self-concept contributes to the predictive effect of achievement to motivation (Guay, Marsh, & Boivin, 2003; Marsh, 1989).

The present study

There are two important issues to be explored. The first question is whether motivation causes change in achievement, or vice versa. As discussed previously, with respect to a group of high school students, intrinsic motivation may be a cause of achievement, whereas there is less evidence to support the reverse causal relationship, thus indicating that this latter relation requires further exploration. The second question is concerned with the causal relationship from types of motivation other than the intrinsic ones, as these other types are not the subject of current literature. As increasingly more studies value identified motivation, test-taking motivation, and performance goals, causal relationships between other types of motivation and academic performance should also be explored. Therefore, the focus of the present study is on both intrinsic and test-taking motivation, and accordingly, the potential causal relationship between both motivation and achievement is examined.

Based on these questions, a longitudinal survey was selected. The National Education Longitudinal Study of 1988 (NELS88, available at http://nces.ed.gov/surveys/nels88/index.asp) measures the various variables that influence teenagers’ academic results and participation in school activities. Among the datasets, the self-reported items that reflect intrinsic motivation and items on plans to take tests (test-taking motivation) were selected.

Method

Participants

The NELS88 was administered in three waves, namely, one baseline survey for grade 8 (1988) and two follow-up surveys, one in 1990 (10th grade) and one in 1992 (12th grade). It included students from 1,052 high schools across the United States. In the data, 53.2% of the sample were girls. Individuals who provided valid answers with respect to the target concepts, namely, intrinsic motivation and extrinsic motivation, in the first and second follow-up questionnaires were selected for the study. There were 3,411 missing responses for all target (independent) variables (i.e., intrinsic and test-taking motivation), 17 missing for all achievement scores, and 30 missing for both, all of which were excluded from the present analyses. The sample size for the present study was 8,674. The missing data were imputed using Mplus 7.11 using maximum likelihood (ML) method (see Muthén & Muthén, 2013 for details) and finally, 8,674 cases were retained.

Measures

Mathematics achievement

We used the mathematical IRT (item respond theory) theta scores as the achievement indicators in all three waves of the NELS88 (BY2XMTH, F12XMTH, and F22XMTH). The IRT theta represented the ability of the individuals on the same scale of the achievement tests anchored from grade 8 to the two follow-up surveys. The use of the IRT scores was based on the comparability and normalization transformation of the scores. The mathematics theta scores ranged from 23.98 to 80.67 for all individuals, with means of 45.48, 50.73, and 54.30, respectively, for each wave (see Table 1).

Table 1.

Correlation between motivation factors, covariates and mathematics achievement.

	Math 0	Math 1	Math 2	SES	SEX	InMot1	InMot2	TTMot1	TTMot2
Math0	1.000
Math1	0.880**	1.000
Math2	0.838**	0.919**	1.000
SES	0.440**	0.459**	0.470**	1.000
SEX	–0.048**	–0.053**	–0.087**	–0.041**	1.000
InMot1	0.348**	0.389**	0.426**	0.111**	–0.126**	1.000
InMot2	0.128**	0.146**	0.187**	–0.028*	–0.015*	0.414**	1.000
TTMot1	0.333**	0.361**	0.372**	0.298**	0.026**	0.186**	0.064**	1.000
TTMot2	0.418**	0.457**	0.491**	0.354**	0.050*	0.187**	0.061**	0.448**	1.000
M	46.43	51.88	55.23	0.04	0.53	0.01	–0.06	0.03	0.02
SD	8.48	9.59	10.25	0.79	0.50	0.96	0.89	0.64	0.52

Note: *p < 0.05; **p < 0.01.

InMot = Intrinsic Motivation; Math = Mathematics Achievement; TTMot = Test-Taking Motivation; For SEX, 0 = Male and 1 = Female; For SES, the variable ‘BYSES’ was used in the dataset.

Intrinsic motivation

On the NELS88, the self-description questionnaire (SDQ, see Marsh, 1992; Marsh & O’Nell, 1984) was adopted to measure the non-cognitive factors. According to SDT, interest and competence are two important factors that influence intrinsic motivation. Thus, as there is a high correlation among different types of intrinsic motivation (Amabile et al., 1994; Loo, 2001), the related items were treated as reports of intrinsic motivation. The items in Wave 1 asked about intrinsic motivation with respect to mathematics competence (F1S63D, F1S63J, F1S63Q, F1S63S in the data set, e.g., ‘Mathematics is one of my best subjects’). The responses ranged from 1 = False (not at all) to 6 = True (absolutely true). The factor analysis indicated that the items were highly representative of competence in mathematics with loadings ranging from 0.75 to 0.92 and a reliability of 0.71. In Wave 2, the items directly asked students to rate their reason for learning mathematics, which included interest and competence (F2S22CA, F2S22CB in the dataset, e.g., ‘I am interested in math’). The responses ranged from 1 = not at all important to 4 = very important. The factor loadings ranged from 0.92 to 0.94 with a reliability score of 0.98. The factor scores for the two sets of variables were recorded as the indicators of intrinsic motivation (InMot 1 and InMot 2, Table 2), where a higher score indicated a stronger intrinsic motivation for mathematics.

Table 2.

Parameter estimates of the cross-lag model between motivation and mathematics achievement.

	Std Est.	Post SD	p	95% Interval
Math 1 on
Math 0	0.840	0.004	<0.001	[0.833 0.847]
SES	0.089	0.006	<0.001	[0.076 0.101]
SEX	−0.008	0.005	0.067	[−0.018 0.002]
Math 2 on
Math 1	0.856	0.004	<0.001	[0.848 0.864]
SES	0.053	0.005	<0.001	[0.043 0.064]
SEX	−0.037	0.005	<0.001	[−0.046 −0.027]
InMot1	0.079	0.005	<0.001	[0.070 0.088]
TTMot1	0.037	0.005	<0.001	[0.028 0.046]
InMot2 on
Mat 1	−0.009	0.018	0.323	[−0.040 0.025]
InMot1	0.572	0.016	<0.001	[0.537 0.598]
TTMot1	0.000	0.017	0.483	[−0.027 0.037]
TTMot2 on
Math 1	0.345	0.010	<0.001	[0.328 0.365]
InMot1	−0.007	0.010	0.260	[−0.026 0.012]
TTMot 1	0.327	0.010	<0.001	[0.306 0.346]
Mat 2 with InMot2	0.124	0.019	<0.001	[0.085 0.155]
TTMot2 with InMot2	0.027	0.024	0.153	[−0.020 0.071]
TTMot2 with Math 2	0.171	0.012	<0.001	[0.149 0.194]

Note. Math = Mathematics Achievement; InMot = Intrinsic Motivation; TTMot = Test-Taking Motivation; Est. = Standardized Estimation.

Test-taking motivation

In the NELS88 datasets, there were a series of items that asked about the student’s intention to take various tests. Test-taking motivation was represented by using the items on whether a student was planning to take a certain test in relevant time. For example, statements included the tests such as the ‘College Board Scholastic Aptitude Test (SAT)’, the ‘American College Testing (ACT)’, the ‘Advanced Placement test (AP)’, etc. The responses were originally recorded as 1 = have not thought about it, 2 = do not plan to take, 3 = plan to take this year, 4 = plan to take next year, and 5 = plan to take in 12th grade for Wave 1; and 1 = have not thought about it, 2 = do not plan to take, 3 = have already taken, and 4 = plan to take for Wave 2. We recoded 1 and 2 to 0, indicating the student had no intention of taking the tests and recoded 3 through 5 as 1, indicating the student intended to take the tests. The count (sum) of the scores for the six items for each individual was computed and was then logged due to its non-normal distribution. The items were included in both waves (F1S50A – F1S50AF and F2S44A – F2S44F, TTMot1 and TTMot2 in Table 1). A higher score indicated a stronger test-taking motivation.

Controlling covariates

While numerous studies have selected gender, socioeconomic status (SES), poverty level, minority status and previous achievement as the available variables to control the salient background information (e.g., Marsh et al. 2005), we controlled gender, SES, and the initial achievement in the subsequent analyses.

Analyses

The analytical model is shown in Figure 1. We controlled the influence of gender and SES on the achievement measures in the same model. Initial achievement (Math 0) was also included influencing the first follow-up ability. We used Mplus 7.11 (Muthén & Muthén, 2013) to conduct the cross-lag analysis with a Bayesian estimator to achieve the results.

Figure 1.

Path graph between motivation and mathematics achievement.

Results

Bivariate correlations are presented in Table 1. The model fit indices are obtained using a model where χ²= 843, df = 9, p < 0.001, CFI = 0.971, TLI = 0.916, RMSEA = 0.107, and the parameter estimates are presented in Table 2. For the controlled covariates, boys achieved higher scores in mathematics in Wave 2 than girls, and higher SES level students exhibited slightly higher mathematics scores in both Wave 1 and Wave 2.

To clearly illustrate the relationship between motivation and achievement, the model path graph without covariates is used (Figure 1). The model indicated that after controlling for the covariates, motivational factors influenced the follow-up status and, accordingly, greater intrinsic motivation in Wave 1 led to greater intrinsic motivation in Wave 2. It was also determined that a higher test-taking intention in Wave 1 led to a greater intention in Wave 2. Furthermore, both motivation factors facilitated achievement growth after controlling the covariates. Intrinsic motivation also had a greater influence on follow-up mathematics achievement (est. = 0.079, p < 0.001) than did test-taking motivation (est. = 0.037, p < 0.001). Most importantly, it was determined that mathematics achievement predicted test-taking intention (Est. = 0.345, p < 0.001) but could not predict intrinsic motivation.

Discussion

Although general developmental and educational psychologists declare that non-cognitive factors are primary determinants of achievement and performance (e.g., Hattie, 2009), a more detailed picture should be explored. With a causal ordering study of relations among motivation factors and academic achievement, the present study highlights the potential reciprocal relationship between motivational factors and mathematics achievement.

Due to a limited number of past studies, the various roles of motivation should be differentiated in educational settings. In concert with the literature, interest, acting as a factor of intrinsic motivation, influences, to a limited degree, achievement. However, achievement does not lead to a change in intrinsic motivation, at least in the present sample and age group, as intrinsic motivation was only influenced by former intrinsic status. This indicates that the relationship between intrinsic motivation and academic achievement may be uni-directional. This is consistent with past studies (Köller et al., 2001; Marsh et al., 2005), which used a similar age group of participants, that is, students in their later school years, namely, junior to senior in high school, may exhibit such a pattern. As explained by Marsh et al. (2005), the non-significant relationship may be due to some shared variance in subsequent measures of academic achievement that could not be uniquely explained by either intrinsic or test-taking motivation. Marsh and colleges (2005) also indicated that there might be a remote relation between achievement and interest, since mediators such as self-concept and perceived competence may exist.

The most important finding indicates that test-taking motivation promotes subsequent achievement, as suggested by previous studies, and at the same time, achievement level will, in turn, largely promote subsequent test-taking motivational level, and students with higher achievement levels will more strongly pursue external certification. This is likely because students with higher academic achievement may require additional opportunities to present their competence by taking tests. School achievement may possess naturally inherent test-taking aspects and that achievement tests reflect student competence as an outcome of their study efforts.

Though controlled in the study, there are gender and social economic differences in ability. Boys exhibited higher abilities in later school years, and students from higher SES families demonstrated higher ability levels. However, Table 2 indicates that these background effects are rather small. It is also important that, though girls may demonstrate lower achievement in later school years and that lower SES students exhibit slightly inferior scores than higher SES students, the non-cognitive factors that contribute to ability growth are still significant after controlling the background information. Educators should not emphasize the demographic information, but rather, they should emphasize learning motivation. For example, even though girls demonstrated lower mathematics achievement than boys, the positive effects of motivation on subsequent mathematics achievement tests were similar for both boys and girls. Possible motivational factors include intrinsic life goals, informational feedback, teacher autonomy support, etc.

Limitations and future directions

Several limitations of this study are worth mentioning. The intrinsic motivation indicators used in the two waves of the present study are not identical. Although there is high correlation, the two factors, interest and competence, reflect different aspects of intrinsic motivation. However, due to the limit of the instruments, the present study could only represent the change in intrinsic motivation change. Further exploration should use identical items in both waves to represent the same construct.

Another limitation is that we only used the test-taking plan as an indicator of test-taking motivation. Since we used the direct measure of students’ plans to take test, we could not know where the motives are indeed coming from (either external or identified). As previously discussed, although test-taking motivation involves external and identified orientations which should be at the same time extrinsically orientated, individuals may still have different motives towards taking tests. In the present study, we took the ‘test-taking motivation’ as a whole (cf. Arvey et al., 1990), and did not differentiate its detailed components. As suggested by SDT theorists, because the perception of the individual is important, future studies may consider these detailed factors. For example, the value placed on the test, the pursuit of the scores, and even the perseverance reflecting intrinsic value may be explored. Meanwhile, extrinsic motivation may not be restricted to test-taking intentions. Others, such as the pursuit of grades, the focus on study for teachers and parents, and the motivation to compete with peers are also branches of extrinsic motivation, even though their roles in influencing academic achievement may vary. Thus, future studies could incorporate these various extrinsic motivation factors into the model and explore more detailed causal relationships.

Finally, we did not consider other relevant factors which might be important mediators. For example, school engagement may be the mediator between the path from motivation to achievement (e.g., Froiland & Davison,2016; Froiland & Worrell, 2016). The lack of the mediator measures may decrease the explanation power of the causal effects. Future research may include an indicator of school engagement as a mediator. This might explain why the path from motivation to achievement is manifested whereas the opposite path could not be consistently and robustly obtained. In future studies, relevant variables, such as engagement and self-concept, could be considered in a mediating model.

Implications

The direction of causality between motivation and achievement has important practical implications for educators and educational psychologists. If the direction is from motivation to achievement, as much of the literature insists, teachers should concentrate on student motivation, including intrinsic motivation to learn and extrinsic motivation focusing on academic performance. Conversely, if the causality is from achievement to motivation, for example, with respect to the extrinsic motivation in the present study, teachers should focus on improving academic skills to strengthen external drive. By contrast, the reciprocal effect indicates that achievement and test-taking intention are mutually reinforcing. It also suggests that the effects of the emphasis on only one aspect (e.g., test-taking intention) may be short-lived and will not have a long-term influence on academic achievement (Marsh et al., 2005). Emphases on test-taking intentions and on the improving of academic skills will interact as an effective, long-term way to facilitate academic achievement.

The present study shows that intrinsic and test-taking motivations may positively influence academic performance. More importantly, achievement also influences subsequent test-taking motivation; this reciprocal relationship may enhance the final academic achievement for the long-term. As demonstrated in educational settings, the choice for students to learn what they are really interested in is not always a panacea (Iyengar & Lepper, 2002). As a result, teachers and educators should pay attention to all kinds of motivation which may facilitate, regardless of the demographics. Particularly, the external motivators (e.g., scores, grades) may be more useful and necessary for students with high academic achievement than those with low academic achievement.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been fully supported by the Fundamental Research Funds for the Central Universities (Project No. SWU1709379) to the first author Yuan Liu, and the grant of Educational Scientific Plan for 13th Five-Year of Shenzhen (Project No. YBFZ16002) to the corresponding author Shumeng Hou.

Author biographies

Yuan Liu, PhD in Education, is an Associate Professor in the Faculty of Psychology at the Southwest University. His research interests include statistics and measurement in education and psychology, growth modeling, longitudinal study method, and learning motivation.

Shumeng Hou, PhD in Educational Psychology, is an Assistant Professor in Harbin Institute of Technology Shenzhen Graduate School. Her research interests mainly lie in learning and cognitive development of children and adolescents.

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