VideoDL: Video-Based Digital Learning Framework Using AI Question Generation and Answer Assessment (2023)
Published in International Journal of Advanced Corporate Learning , 2023
Recommended citation: Forkan, Abdur Rahim Mohammad; Kang, Yong-Bin; Jayaraman, Prem Prakash; Du, Hung; Thomson, Steven; Kollias, Elizabeth; Wieland, Natalie (2023). VideoDL: Video-Based Digital Learning Framework Using AI Question Generation and Answer Assessment. International Journal of Advanced Corporate Learning (iJAC), vol 16, pp. 19-27. /files/research/videoDL_2023.pdf
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.