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College professors in the social sciences and professional studies have adopted numerous strategies for teaching undergraduate statistics, yet few researchers provide empirical evidence students’ learning actually increased because of the instructional innovation. Assessment of pedagogy is frequently subjective and based on comments from students or faculty. Consequently, evaluating the effectiveness of teaching activities on student learning in statistical analysis courses is warranted. This study employed a pretest-posttest design to measure student learning and then examined the relationship between student demographics, prior knowledge, and course characteristics on knowledge gained in undergraduate statistics. Data derived from 185 students enrolled in six different sections of a statistical analysis course taught over a seven-year period by the same instructor. Multiple regression analyses revealed age, age X gender (interaction effect), major, prior knowledge, examinations, and group projects all had statistically significant effects on how much students learned in the course. The results suggest faculty assess students’ prior knowledge at the beginning of the semester and use such data to inform both the content and delivery of statistical analysis. Moreover, before embracing a new pedagogy, faculty should establish empirically that learning is linked to the teaching innovation.
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How to Cite
Delucchi, M. (2018). Using a Quasi-Experimental Design in Combination with Multivariate Analysis to Assess Student Learning. Journal of the Scholarship of Teaching and Learning, 19(2). https://doi.org/10.14434/josotl.v19i1.24474