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http://dx.doi.org/10.14352/jkaie.2021.25.5.813

Development and evaluation of AI-based algorithm models for analysis of learning trends in adult learners  

Jeong, Youngsik (Department of Computer Education, Jeonju National University of Education)
Lee, Eunjoo (Korean Educational Development Institute)
Do, Jaewoo (Korean Educational Development Institute)
Publication Information
Journal of The Korean Association of Information Education / v.25, no.5, 2021 , pp. 813-824 More about this Journal
Abstract
To improve educational performance by analyzing the learning trends of adult learners of Open High Schools, various algorithm models using artificial intelligence were designed and performance was evaluated by applying them to real data. We analyzed Log data of 115 adult learners in the cyber education system of Open High Schools. Most adult learners of Open High Schools learned more than recommended learning time, but at the end of the semester, the actual learning time was significantly reduced compared to the recommended learning time. In the second half of learning, the participation rate of VODs, formation assessments, and learning activities also decreased. Therefore, in order to improve educational performance, learning time should be supported to continue in the second half. In the latter half, we developed an artificial intelligence algorithm models using Tensorflow to predict learning time by data they started taking the course. As a result, when using CNN(Convolutional Neural Network) model to predict single or multiple outputs, the mean-absolute-error is lowest compared to other models.
Keywords
Adult learners; artificial intelligence model; learning trend analysis; Tensorflow;
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