Investigating the effectiveness of visual learning analytics in Active Video Watching

Type of content
Conference Contributions - Published
Thesis discipline
Degree name
Publisher
Springer
Journal Title
Journal ISSN
Volume Title
Language
Date
2022
Authors
Mohammadhassan N
Mitrovic, Antonija
Abstract

Video-based Learning (VBL) is a popular form of online learning, which may lead to passive video watching and low learning outcomes. Besides potential low engagement, VBL often provides very limited feedback on student’s progress. As a way to overcome these challenges, we present student-facing visual learning analytics (VLA) designed for the AVW-Space VBL platform. Using a quasi-experimental design, we compared data collected in the same firstyear university course in 2020 (control group, 294 participants using the original version of AVW-Space) to the 2021 data when 351 participants used the enhanced version of AVW-Space (experimental group). We analysed various measures of engagement (number of watched videos, comments, etc.) and learning (pre/post-study knowledge scores). The findings show that VLA encourage constructive behaviour and increase learning. This research contributes to using student-facing VLA in VBL platforms to boost engagement and learning.

Description
Citation
Mohammadhassan N, Mitrovic A (2022). Investigating the effectiveness of visual learning analytics in Active Video Watching. Durham, UK: Artificial Intelligence in Education. 27/07/2022-31/07/2022. I. 127-139.
Keywords
Video-based Learning, Visual Learning Analytics, Student Model
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::39 - Education::3904 - Specialist studies in education::390405 - Educational technology and computing
Fields of Research::39 - Education::3904 - Specialist studies in education::390408 - Learning analytics
Fields of Research::46 - Information and computing sciences::4608 - Human-centred computing
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All rights reserved unless otherwise stated