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Moving large classes online: Principles for teaching, learning and assessment

Authors: Hornsby, D.J.;

Moving large classes online: Principles for teaching, learning and assessment

Abstract

When approaching the issue of large class teaching it is important to acknowledge that under normal conditions these types of learning spaces often pose significant challenges for lecturers in delivery and for students in learning. The present pandemic, COVID-19, is anything but normal and adds a complicating factor in approaching large class teaching. This is largely due to the fact that most institutions of higher education have ceased face-to-face instruction and are rapidly pivoting courses online, at least until the end of 2020. Under normal conditions, large classes are often synonymous with a lack of student engagement, bad performance, and few opportunities to develop important skills like critical thinking (Ehrenberg et al., 2001; McKeachie, 1980; Cooper and Robinson, 2000; Mulryan-Kyne, 2010). Under conditions of online learning, the possibilities for these challenges to be compounded is real if pedagogical strategies that reinforce passive learning are adopted, or opportunities for direct contact with students are avoided, and the use of summative types of assessments are privileged. Therefore, the purpose of this short essay is to frame and offer some principles to adopt in moving large classes online and developing assessments

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Keywords

Large Classes; Online; COVID-19; Teaching; Learning; Assessment

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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