Evaluating Attitudes, Skill, and Performance in a Learning-Enhanced Quantitative Methods Course: A Structural Modeling Approach

Abstract

Whereas statistics teachers approach their topic with enthusiasm, students often feel trepidation (e.g., Dauphinee, Schau, & Stevens, 1997). Engaging pedagogy is needed to improve attitudes and performance, thereby increasing interest in quantitative methods. We evaluated relations among attitudes, initial skill, and performance in a Quantitative Methods course that involved students in active learning using a structural modeling approach. Results from data on 129 New England undergraduates largely confirmed hypotheses. First, the means for 2 of 3 quantitative attitudes showed significant improvement over the semester, with reduced quantitative anxiety and increased quantitative self-efficacy. Second, previous math ability and positive quantitative attitudes significantly predicted 38% of the variance in course performance. Third, 75% of the variance in postcourse quantitative attitudes was significantly associated with precourse quantitative attitudes, whereas precourse quantitative skill was not a significant predictor. Fourth, 18% of the variance in course experience ratings was significantly predicted by initial quantitative attitudes such that those with low confidence, high anxiety, or perceived hindrances rated learning activities more favorably. Limitations are discussed and follow-up research is suggested.