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Abstract Title: Online Learning Modules: A Better Lens to Observe Learning at Higher Resolution
Abstract: Online learning platforms provide rich data on students' learning behavior. However, analysis of online learning data often suffer from widespread ambiguities in the data, caused in part by the structures of many online courses being similar to their offline counterparts. To improve the resolution of learning measurements, we designed a series of online learning modules (OLMs) based on the ideas of deliberate practice and modularized instructional design. In two case studies in introductory mechanics, we demonstrate that the OLMs allow instructors to collect effective pre and post-test data on the time scale of every 20-30 minutes, capable of measuring student learning of a single knowledge component. In addition, the design of OLMs directly connects learning behavior with learning outcome, thereby providing a rich variety of information on the effectiveness of instructional materials, on students' learning habits and learning difficulties, as well as on students' learning motivation.
Abstract Type: Contributed Poster Presentation

Author/Organizer Information

Primary Contact: Zhongzhou Chen
University of Central Florida Physics Department
4111 Libra Drive
Room 153
Orlando, FL 32828
Phone: 2177218411

Contributed Poster

Contributed Poster: Download the Contributed Poster