Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151947
Title: Towards AI-powered personalization in MOOC learning
Authors: Yu, Han 
Miao, Chunyan
Leung, Cyril
White, Timothy John
Keywords: Engineering::Computer science and engineering
Issue Date: 2017
Source: Yu, H., Miao, C., Leung, C. & White, T. J. (2017). Towards AI-powered personalization in MOOC learning. Npj Science of Learning, 2(1), 15-. https://dx.doi.org/10.1038/s41539-017-0016-3
Journal: npj Science of Learning
Abstract: Massive Open Online Courses (MOOCs) represent a form of large-scale learning that is changing the landscape of higher education. In this paper, we offer a perspective on how advances in artificial intelligence (AI) may enhance learning and research on MOOCs. We focus on emerging AI techniques including how knowledge representation tools can enable students to adjust the sequence of learning to fit their own needs; how optimization techniques can efficiently match community teaching assistants to MOOC mediation tasks to offer personal attention to learners; and how virtual learning companions with human traits such as curiosity and emotions can enhance learning experience on a large scale. These new capabilities will also bring opportunities for educational researchers to analyse students’ learning skills and uncover points along learning paths where students with different backgrounds may require different help. Ethical considerations related to the application of AI in MOOC education research are also discussed.
URI: https://hdl.handle.net/10356/151947
ISSN: 2056-7936
DOI: 10.1038/s41539-017-0016-3
Rights: © 2017 The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MSE Journal Articles
SCSE Journal Articles

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