Decades of research have suggested strong associations between motivation and academic achievement (e.g. Hattie, 2008), but limited studies have taken students’  characteristics such as intelligence and personality into account. Given that intelligence (Roth et al., 2015) and personality (Poropat, 2009) have been found to predict school performance, it is important to examine if motivation plays a unique role in academic success after controlling for intelligence and personality traits. If so, which motivational factors contribute more to academic achievement? To address these questions, Lavrijsen et al. (2022) conducted a study under a large research project involving 3409 Grade 7 students from Flanders, Belgium. 

Lavrijsen et. al (2022) focused on a list of motivational factors: academic self-concept (students’ perception of how well they were doing in most school subjects), motivation quality (autonomous motivation from an inherent interest in learning and controlled motivation from the pressure to succeed, achievement goals (students’ goal to master the subject material/to avoid not mastering the material/to perform better than other students/to avoid performing worse than others), achievement motives (achievement motivation and fear of failure), intelligence beliefs, and effort beliefs. The researchers also measured students’ personalities (neuroticism, agreeableness, extraversion, conscientiousness, and openness) and their need for cognition (preferences for thinking about things). Both standardized math test results and school grades were collected.The results showed that intelligence and students’ preference for cognition as a personality trait were strong predictors of academic achievement. However, when controlling for intelligence and personality, all motivational constructs played an important role in predicting school grades. It is worth noting that the effect of motivation was less pronounced in predicting standardized test results, suggesting that motivation may play a more important role in students’ daily schoolwork than in objective measures of achievement such as standardized tests. Within all of the motivational factors, academic self-concept was the strongest predictor of academic achievement. A possible explanation for this relation is that students with high academic self-concept strive to engage in behaviors consistent with their self-image and invest more in their academic studies. 

Lavrijsen et al.’s study (2022) conveys an important message to students, parents, and teachers: despite the fact that intelligence and personality are strong predictors of achievement, motivation also has a unique contribution to academic performance. Teachers can engage their students through appealing instruction and foster high academic self-concept. In relation to EPIC’s research studies, Lavrijsen et al.’s study points to potential future research study on examining whether the relation between motivation and academic achievement is mediated by students’ resilience to setbacks in academic studies. This line of research may help decipher the underlying mechanism of obtaining academic success. 

If you are interested in reading further about Lavrijsen’s study, check out the link to retrieve

the journal article: https://psycnet.apa.org/record/2021-28255-001

This article was written by Emma Hong.

Reference:

Hattie, J. (2008). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge. https://doi.org/10.4324/9780203 887332

Lavrijsen, J., Vansteenkiste, M., Boncquet, M., & Verschueren, K. (2022). Does motivation predict changes in academic achievement beyond intelligence and personality? A multitheoretical perspective. Journal of Educational Psychology, 114(4), 772.

Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135(2), 322–338. https://doi.org/10.1037/a0014996

Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118–137. https://doi.org/10.1016/j.intell.2015.09.002