1392. The impact of AI video summaries on video platform learning and teaching mode
Invited abstract in session TC-61: Behaviour in information systems, stream Behavioural OR.
Tuesday, 12:30-14:00Room: Maurice Keyworth G.31
Authors (first author is the speaker)
| 1. | Yan Peng
|
| Tianjin University | |
| 2. | Dan Ke
|
| Wuhan University |
Abstract
This study investigates the impact of the AI-generated summaries of video content on users' cognitive load and learning productivity, and therefore, how to improve the teaching design of online video platforms. Grounded in Cognitive Load Theory (CLT), this study hypothesizes that AI video summaries increase learning productivity, and cognitive load (intrinsic, extraneous, germane cognitive load) mediates this relationship. The video complexity moderates the effectiveness of AI summaries on learning productivity. We conduct three between-subject experiments to validate the main hypothesis and the mediating and moderating effects, using several online videos with varying complexity levels. Participants are randomly assigned to groups with or without AI-generated summaries and complete post-video learning assessments by measure cognitive load using established self-report scales.Preliminary findings suggest that AI-generated summaries reduce extraneous cognitive load, allowing users to focus on intrinsic knowledge acquisition, thereby increasing learning efficiency. This research provides empirical evidence on how AI tools optimize cognitive resources, improve content comprehension, and shape digital knowledge acquisition. AI content summaries grasp the core content of online videos, thus improve users' learning process and productivity. Online knowledge sharing platforms can adopt such AI tools to enhance the teaching design and performance.
Keywords
- Behavioural OR
- Artificial Intelligence
Status: accepted
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