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The role of study strategy in motivation and academic performance of ethnic minority and majority students: a structural equation model.

Ulviye IsikJanneke WilschutGerda CroisetRashmi A Kusurkar
Published in: Advances in health sciences education : theory and practice (2018)
Underperformance among ethnic minority students has been reported in several studies. Autonomous motivation (acting out of true interest or personal endorsement) is associated with better learning and academic performance. This study examined whether study strategy (surface, achieving, and deep) was a mediator between the type of motivation (autonomous and controlled motivation) and academic performance (GPA and clerkship performance), and whether these relations are different for students from different ethnic groups to gain a better understanding about the needed intervention/support in the curriculum. Data was gathered from 947 students at VUmc School of Medical Sciences, Amsterdam. Structural Equation Modelling was performed to test the hypothesized model: a higher autonomous motivation has a positive association with academic performance through deep and achieving strategy, and has a negative association with performance through surface strategy. The model with the outcome variables GPA and clerkship performance had a good fit (n = 618; df = 1, RMSEA = 0.000, p = 0.43). The model for the ethnic majority and minority groups was significantly different (p < 0.025). In this study, autonomous motivation had a positive association with GPA through achieving strategy for the ethnic majority students only. It might be that the size of the minority groups was too small to detect differences or that other factors mediate these relations in ethnic minority students. Qualitative research is needed to identify other factors influencing the academic performance of ethnic minority students and what they experience during their education, in order to support their learning in the right manner.
Keyphrases
  • high school
  • medical students
  • healthcare
  • randomized controlled trial
  • physical activity
  • machine learning
  • mental health