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Fostering Active Learning with Video Using Teacher-Set Analysis Categories

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Abstract

Despite widespread use of video in higher education, there is still much to be learnt about what constitutes optimal teaching practices in leveraging digital resources for learning. Research on student interactions with online video suggests that practices can range from as minimal as setting passive-receptive viewing requirements through to teacher-structured purposeful engagement. Some approaches focus on either technological or pedagogical solutions, or both, to guide learning with video. This chapter examines several published cases of teaching practice with video in undergraduate education. It draws from these examples a focus on teacher-set analysis categories to guide student exploration of digital video content to help novices to scaffold their thinking. Various explicit and implicit uses of analysis categories within Australian, Taiwan, and US universities are reviewed from the literature. Some cases demonstrate transferability and/or scalability to apply to other disciplines. Overall, the literature reviewed indicates that the use of categories to inform the design of digital video analysis needs to ensure that an active learning challenge is retained. Analysis guided by teacher-set categories tends to be beneficial for student performance evaluation and development in particular, as well as knowledge acquisition/consolidation.

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Colasante, M., Lang, J. (2019). Fostering Active Learning with Video Using Teacher-Set Analysis Categories. In: Sampson, D., Spector, J.M., Ifenthaler, D., Isaías, P., Sergis, S. (eds) Learning Technologies for Transforming Large-Scale Teaching, Learning, and Assessment. Springer, Cham. https://doi.org/10.1007/978-3-030-15130-0_10

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