Towards AI-powered personalization in MOOC learning

被引：68

作者：

Yu, Han ^{[1
]}

Miao, Chunyan ^{[1
,2
]}

Leung, Cyril ^{[1
,3
]}

White, Timothy John ^{[4
]}

机构：

[1] Nanyang Technol Univ, Joint NTU UBC Res Ctr Excellence Act Living Elder, Singapore 639798, Singapore

[2] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore

[3] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada

[4] Nanyang Technol Univ, Sch Mat Sci & Engn, Singapore 639798, Singapore

来源：

NPJ SCIENCE OF LEARNING | 2017年 / 2卷 / 01期

基金：

新加坡国家研究基金会;

关键词：

FRAMEWORK; LESSONS; DESIGN;

D O I：

10.1038/s41539-017-0016-3

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

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.

引用

页数：5

共 50 条

[21] Massive Open Online Course Completion Rates Revisited: Assessment, Length and Attrition [J].

Jordan, Katy .

INTERNATIONAL REVIEW OF RESEARCH IN OPEN AND DISTRIBUTED LEARNING, 2015, 16 (03) :341-358

[22]

Knox J., 2012, ASS LEARNING TECHNOL

[23] Bots as Virtual Confederates: Design and Ethics [J].

Krafft, Peter M. ;

Macy, Michael ;

Pentland, Alex Sandy .

CSCW'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, 2017, :183-190

[24] Peer and Self Assessment in Massive Online Classes [J].

Kulkarni, Chinmay ;

Wei, Koh Pang ;

Le, Huy ;

Chia, Daniel ;

Papadopoulos, Kathryn ;

Cheng, Justin ;

Koller, Daphne ;

Klemmer, Scott R. .

ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, 2013, 20 (06)

[25] Building a practically useful theory of goal setting and task motivation - A 35-year odyssey [J].

Locke, EA ;

Latham, GP .

AMERICAN PSYCHOLOGIST, 2002, 57 (09) :705-717

[26] Open Learning at a Distance: Lessons for Struggling MOOCs [J].

McAndrew, Patrick ;

Scanlon, Eileen .

SCIENCE, 2013, 342 (6165) :1450-1451

[27]

McLoughlin C., 2008, International Journal of Teaching and Learning in Higher Education, V20, P10, DOI DOI 10.1017/S1537592709991423

[28] A Survey on Transfer Learning [J].

Pan, Sinno Jialin ;

Yang, Qiang .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2010, 22 (10) :1345-1359

[29]

Papadopoulos K., 2014, Proceedings of the first ACM conference on Learning@ scale conference, P163

[30]

Pellegrino J.W., 2012, Education for life and work: Developing transferable knowledge and skills in the 21st century

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