Voluntary E-Learning Exercises Support Students in Mastering Statistics

Abstract

University students often learn statistics in large classes, and in such learning environments, students face an exceptionally high risk of failure. One reason for this is students’ frequent statistics anxiety. This study shows how students can be supported using e-learning exercises with automated knowledge of correct response feedback, supplementing a face-to-face lecture. To this end, we surveyed 67 undergraduate social science students at a German university and observed their weekly e-learning exercises. We aggregated students’ exercise behavior throughout the semester to explain their exam performance. To control for participation bias, we included essential predictors of educational success, such as prior achievement, motivation, personality traits, time preferences, and goals. We applied a double selection procedure based on the machine learning method Elastic Net to include an optimal but sparse set of control variables. The e-learning exercises indirectly promoted the self-regulated learning techniques of retrieval practice and spacing and provided corrective feedback. Working on the e-learning exercises increased students’ performance on the final exam, even after controlling for the rich set of control variables. Two-thirds of students used our designed e-learning exercises; however, only a fraction of students spaced out the exercises, although students who completed the exercises during the semester and were not cramming at the end benefited additionally. Finally, we discuss how the results of our study inform the literature on retrieval practice, spacing, feedback, and e-learning in higher education.

Assessing Numerical Analysis Performance with the Practi Mobile App

“…Overall, the results are in concordance with studies showing that spaced retrieval of learned information through assessments improves information retention in many domains of postsecondary education, including mathematics [59,60], science [32], biology [61], and physiology [62]. Similar to the present study, Schwerter and Brahm [31] found that voluntarily working on e-learning statistics exercises that promoted retrieval practice improved students' learning performance and that students who also spaced out their practice throughout the semester gained additional benefits.…”

“…Considering the current findings and those of other researchers [31], we recommend spacing out self-quizzes over an entire semester to reap and maximize the benefits of deliberate practice and retrieval practice. The post-lecture Practi quizzes were positively and significantly associated with the course measures of achievement: the two midterms and the final exam.…”

“…For example, a math game was used to support middle-school students' deliberate practice [30]. Also, voluntary e-learning exercises were designed to support university students' retrieval practice to learn statistics [31]. These behaviors leverage the retrieval practice (or testing) effect, which is a phenomenon studied in cognitive psychology, whereby taking a memory test has a dual role: it assesses what the learner knows, and it also enhances later retention [32,33].…”

“…They found that students in the treatment condition spontaneously used more methods, which also resembled expert solutions more often, to complete the task than the students in the control condition, showing that expert skills and strategies could be taught. A different study provided 67 German social science university students with weekly e-learning exercises to supplement the face-to-face lectures in a statistics class [31]. The e-learning exercises promoted retrieval practice and spacing, providing corrective feedback.…”