Improving Students’ Deep Learning through Optimizing Testing Schedules in Waterloo’s Online Learning Environment

Grant Recipients: Evan Risko, Jonathan Fugelsang, Jennifer Stolz, and Paul Wehr, Department of Psychology

(Project timeline: January 2016 - December 2017)

Word cloud consisting of words related to the project (e.g., distributed testing, online learning)

Description

Research in psychology has demonstrated that interpolated testing (testing within lectures) and distributed practice (temporally spacing out study episodes) enhance student learning. We recently demonstrated that implementing these innovative techniques into an online course can lead to benefits in student learning. The project will significantly expand the investigation of these innovative approaches to enhancing teaching by implementing and comparing different schedules of interpolated testing and distributed practice across multiple semesters in a large online course. This will allow us to further test the hypothesis that these techniques will improve student learning. This project will foster deep student learning by providing concrete guidance regarding best practices for the use of these techniques in the University of Waterloo’s growing number of online courses. To this end, we will develop material that provides course developers with the requisite information to use, optimally, interpolated testing and distributed practice within an online course.

This project is an extension of a Seed grant project

References

Project Reference List (PDF)

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