Adapting Statistics Education to a Cognitively Heterogeneous Student Population

Abstract

Historically, the introductory course in statistics at the Norwegian University of Life Sciences (NMBU), has taken a traditional, lecture-based form. A previous study at the NMBU concluded that the course structure appeared to disfavor certain cognitive or personality types, extraverts in particular. Therefore, in 2016, as an experiment, the course was restructured into a student active learning course following a flipped classroom approach. At the same time, students were encouraged to do an online screening test for cognitive preferences, personality, work interest, and preferred learning style. The main outcome in the present study was exam scores. Despite the new course structure, we still found significant differences in exam scores between students with a contextual preference, compared with a digital preference, and those with a feeling-based rather than a thinking-based personality characteristic. However, in contrast to the previous study, no significant difference in exam scores was found between the extraverts and the introverts, also after adjusting for other covariates. In the present article, we outline these results and other findings that indicate that additional adaptations should be made in the course, in order to reach an even wider group of the heterogeneous student mass, helping individuals to better reach their learning potential.

Keywords

• cooperative learning
• flipped classroom
• introductory statistics
• personalized learning
• stem-education