Educating Nonmajors: Real Life Experiences of Students Learning Quantitative Methods
Conference
64th ISI World Statistics Congress - Ottawa, Canada
Format: IPS Abstract
Keywords: data science education
Thursday 20 July 2 p.m. - 3:40 p.m. (Canada/Eastern)
Abstract
For most undergraduate students in fields that do not focus on statistics or data science (i.e., nonmajors), the only real opportunity to acquire data analysis skills is through mandatory quantitative methods (QM) courses. Although these skills are very in-demand in the workplace, QM courses generally have a bad reputation among students, who find them difficult and do not see their usefulness. While scientific literature shows that educators have worked on improving the way QM are taught, negative perceptions persist overall among students. The objective of this research was thus to take a novel approach by providing a more in-depth examination of the real life experiences of nonmajors during their QM course, with the goal of understanding exactly how these courses are being experienced as well as providing further insight on continued improvement. A narrative-based approach was used to document students’ experiences; nonmajor undergraduate students participated in semi-structured interviews where they documented their detailed experiences while learning QM. A thematic analysis was conducted to identify six main themes (student profiles, emotional experiences, challenges, coping strategies, helpful learning experiences, and suggestions). The results are presented using 4 turning-points (before the class, before the midterm, before the final, and after the class). The findings are discussed in terms of potential opportunities for improvement in these courses moving forward.