Statistically significant learning experiences: towards building self-efficacy of undergraduate statistics learners through team-based learning

ABSTRACT

Competence in statistics is a fundamental component of a biological scientist’s toolbox. However, anxiety often affects undergraduate students’ development of this competence and research has shown that perceived self-efficacy for statistics is correlated to academic performance. Self-efficacy may be promoted by reducing anxiety , and also allowing students to practice their skills in groups to model approaches used and obtain peer feedback. We undertook action research to investigate how a change in teaching method to team-based learning (TBL) affected our students. The first iteration of the teaching with Year 2 students led us to change our delivery to allow more time for teamworking for the next iteration with Year 1 students. We found that some measures of self-efficacy were correlated with a post-TBL summative test performance of Year 1 and Year 2 students. However, Year 1 students were less positive about TBL. This corroborated quantitative findings revealing that they had lower collective efficacy than Year 2 students, despite teams performing as well during formatively assessed TBL. We draw on self-efficacy theory to better understand why students perceive and report differing learning experiences, and to make recommendations for designing teaching and learning that helps build their self-efficacy.

KEYWORDS:

• Team-based learning
• statistics
• programming
• undergraduate
• biological sciences

Acknowledgments

We would like to express our gratitude to: Dr. Samraat Pawar who co-taught Year 2 sessions; Moira Sarsfield for data management and technological support; Heidi Mennenga for permission to use the TBL-SAI; and Georgina Dagley for research assistance.

Disclosure statement

No potential conflict of interest was reported by the authors.