INSTRUCTIONAL EXPLANATIONS OF VIDEO LECTURES IN HIGHLY RATED MOOCs
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Date
2021-08
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[Bloomington, Ind.] : Indiana University
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Abstract
Instructional explanations (IEs) are a teacher’s deliberate contribution to learning. They are designed and communicated to convey, structure, and convince learning content as well as to respond to an actual or anticipated questions or perceived puzzlement. The purpose of this study is to explore the characteristics of IEs in highly rated MOOC video lectures. Based on the user review scores of the MOOC portals and MOOC providers, 12 MOOCs were selected for this study. A study rubric with 2 layers (i.e., purpose and instance of IEs) was developed by integrating previous studies and then revised after a pilot study. An observation method with momentary time sampling (MTS) was used to capture lecturers’ IE instances at every 10 seconds. Over 37 hours of MOOC videos were coded resulting in 13,524 total codes. The results show that the most frequent IE category was Justification, followed by Familiarizing and Scaffolding. The frequencies were significantly different by subject area and video production type. Five themes of 3-code IE patterns were generated based on the sequential analysis. In unit lectures, IEs at the beginning and ending rely heavily on Scaffolding and Motivating explanations compared to the remaining lecture portions.
Three main findings of this study are: (1) evidence to validate the observation rubric of this study, (2) five themes of IE patterns, and (3) detailed information on opening and closing IE patterns of unit lectures. In addition, various examples of IE patterns are presented and discussed in detail.
Description
Thesis (Ph.D.) - Indiana University, Department of Instructional Systems Technology/School of Education, 2021
Keywords
instructional explanation, sequential analysis, learner impasse, mental model, Massive Open Online Course (MOOC), momentary time sampling (MTS)
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This work is under a CC-BY license. You are free to copy and redistribute the material in any format, as well as remix, transform, and build upon the material as long as you give appropriate credit to the original creator, provide a link to the license, and indicate any changes made.
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/licenses/by/4.0/
Type
Doctoral Dissertation