Title: Visualisation of learners' level of understanding of lectures using digital textbook data

Authors: Hiroto Morita; Kousuke Mouri; Masaru Okamoto; Yukihiro Matsubara

Addresses: Department of Intelligent Systems, Hiroshima City University, Hiroshima, Japan ' Department of Intelligent Systems, Hiroshima City University, Hiroshima, Japan ' Department of Intelligent Systems, Hiroshima City University, Hiroshima, Japan ' Department of Intelligent Systems, Hiroshima City University, Hiroshima, Japan

Abstract: In this paper, we propose a system that defines and visualises learners' understanding of lecture content based on learning data obtained from the digital textbook system, Smart E-textbook Application (SEA), and a quiz function. By feedbacking the visualised results to the learner, the system allows the learner to know which units of the lecture need a review. This enables the learner to improve their understanding of lectures efficiently and effectively. To evaluate whether the proposed system can improve learning effectiveness and learners' understanding of lectures, we conducted an evaluation experiment and found that the proposed system does both. Additionally, a clear difference in the number of logs in the digital textbook and the time to answer the quiz was confirmed. From these, it is possible to decide whether the learner is actively engaged in learning or not.

Keywords: learning analytics; digital textbook system; adaptive learning; personalisation; visualisation.

DOI: 10.1504/IJMLO.2025.145321

International Journal of Mobile Learning and Organisation, 2025 Vol.19 No.2, pp.177 - 198

Received: 15 Jun 2023
Accepted: 04 Oct 2023
Published online: 31 Mar 2025 *

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