Abstract

The use of online learning resources as core components of university science courses is increasing. Learning resources range from summaries, videos, and simulations, to question banks. Our study set out to develop, implement, and evaluate research-based online learning resources in the form of pre-lecture online learning modules (OLMs). The aim of this paper is to share our experiences with those using, or considering implementing, online learning resources. Our first task was to identify student learning issues in physics to base the learning resources on. One issue with substantial research is conceptual understanding, the other with comparatively less research is scientific representations (graphs, words, equations, and diagrams). We developed learning resources on both these issues and measured their impact. We created weekly OLMs which were delivered to first year physics students at The University of Sydney prior to their first lecture of the week. Students were randomly allocated to either a concepts stream or a representations stream of online modules. The programme was first implemented in 2013 to trial module content, gain experience and process logistical matters and repeated in 2014 with approximately 400 students. Two validated surveys, the Force and Motion Concept Evaluation (FMCE) and the Representational Fluency Survey (RFS) were used as pre-tests and post-tests to measure learning gains while surveys and interviews provided further insights. While both streams of OLMs produced similar positive learning gains on the FMCE, the representations-focussed OLMs produced higher gains on the RFS. Conclusions were triangulated with student responses which indicated that they have recognized the benefit of the OLMs for their learning of physics. Our study shows that carefully designed online resources used as pre-instruction can make a difference in students’ conceptual understanding and representational fluency in physics, as well as make them more aware of their learning processes. In particular, the representations-focussed modules offer more advantages.

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