Understanding the Effects of Structured Note-taking Systems for Video-based Learners in Individual and Social Learning Contexts

Autor: Jingchao Fang, Yanhao Wang, Chi-Lan Yang, Ching Liu, Hao-Chuan Wang
Rok vydání: 2022
Předmět:
Zdroj: Proceedings of the ACM on Human-Computer Interaction. 6:1-21
ISSN: 2573-0142
DOI: 10.1145/3492840
Popis: Video-based learning is widely adopted by online learners, yet, learning experience and quality may be negatively affected by asynchronous and remote natures of video-based learning. As note-taking is a common practice employed by video-based learners and is known to be an effective way to trigger active construction and processing of knowledge, yet as a meta-skill, it is challenging to most learners. In this study, we aim to approach the goal of providing cognitive and social scaffolds to video-based learners by structuring their note-taking process. We presented and evaluated structured note-taking systems designed for learners in two contexts, namely, individual learning context and social learning context. With an online controlled study involving 43 participants, we compared the structured note-taking systems with two baseline systems (for individual learning and social learning contexts respectively) and found that structured note-taking significantly improved certain aspects of video-based learning such as and higher cognitive engagement and lower distraction. We discussed our results to inform the design, iteration, and adoption of note-taking tools in video-based learning.
Databáze: OpenAIRE