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Gamified Modules for an Introductory Statistics Course and Their Impact on Attitudes and Learning

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  • Tamarah Smith

Abstract

Background. The theory of gamified learning (Landers, 2014) posits that gamified approaches positively impact students’ attitudes, and in turn this change in attitudes impacts learning; however, research is needed to examine the role of attitude change in gamified approaches (Seaborn & Fels, 2014). A strong negative relationship between students’ attitudes towards statistics and their performance in statistics has been well documented. The need to help students have positive attitudes towards statistics , and therefore be more likely to achieve in the course, makes using gamified learning , which targets attitudes, an ideal domain to test the effects of gamification on attitudes. Methods. The aim in this quasi-experimental study was to examine the ability of gamified modules in a statistics course to have positive impacts on learning and attitudes towards statistics. Students in the experimental group were compared to previous cohorts completing the same course, but without the gamified exercises as well as published results from a large cohort of comparable students. Results. The attitudes of cognitive competence , affect, value and perceived difficulty were all positively impacted after completing the gamified exercises. The experimental group also had large effects of test performance one semester after completing the course. Conclusion. In line with the theory of gamified learning, these findings suggested that the gamified modules were successful in shifting students’ attitudes in a positive direction and subsequently increasing performance. Future studies should introduce randomization between students and examine the specific pathways between attitudes and performance.

Suggested Citation

  • Tamarah Smith, 2017. "Gamified Modules for an Introductory Statistics Course and Their Impact on Attitudes and Learning," Simulation & Gaming, , vol. 48(6), pages 832-854, December.
  • Handle: RePEc:sae:simgam:v:48:y:2017:i:6:p:832-854
    DOI: 10.1177/1046878117731888
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