VideoDL: Video-Based Digital Learning Framework Using AI Question Generation and Answer Assessment
DOI:
https://doi.org/10.3991/ijac.v16i1.35207Keywords:
Video-based Learning, Question Generation, Learning Assessment, Online LearningAbstract
Assessing learners’ understanding and competency in video-based digital learning is time-consuming and very difficult for educators, as it requires the generation of accurate and valid questions from pre-recorded learning videos. This paper demonstrates VideoDL, a video-based learning framework powered by Artificial Intelligence (AI) that supports automatic question generation and answer assessment from videos. VideoDL comprises of various AI algorithms, and an interactive web-based user interface (UI) developed using the principles of human-centred design. Our empirical evaluation using real-world videos from multiple domains demonstrates the effectiveness of VideoDL.
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Copyright (c) 2023 Abdur Rahim Mohammad Forkan, Yong-Bin Kang, Prem Prakash Jayaraman, Hung Du, Steven Thomson, Elizabeth Kollias, Natalie Wieland
This work is licensed under a Creative Commons Attribution 4.0 International License.