An e-learning recommender that helps learners find the right materials.

Mbipo, Blessing; Massie, Stewart; Craw, Susan

Abstract

Learning materials are increasingly available on the Web making them an excellent source of information for building e-Learning recommendation systems. However, learners often have difficulty finding the right materials to support their learning goals because they lack sufficient domain knowledge to craft effective queries that convey what they wish to learn. The unfamiliar vocabulary often used by domain experts creates a semantic gap between learners and experts, and also makes it difficult to map a learner's query to relevant learning materials. We build an e-Learning recommender system that uses background knowledge extracted from a collection of teaching materials and encyclopedia sources to support the refinement of learners' queries. Our approach allows us to bridge the gap between learners and teaching experts. We evaluate our method using a collection of realistic learner queries and a dataset of Machine Learning and Data Mining documents. Evaluation results show our method to outperform benchmark approaches and demonstrates its effectiveness in assisting learners to find the right materials.

Citation

MBIPO, B., MASSIE, S. and CRAW, S. 2018. An e-learning recommender that helps learners find the right materials. In Zilberstein, S., McIlraith, S., Weinberger, K., Youngblood, G.M., Myers, K., Eaton, E. and Wollowski, M. (eds.) Proceedings of the 32nd Association for the Advancement of Artificial Intelligence (AAAI) Artificial intelligence conference (AAAI18), co-located with the 30th Innovative applications of artificial intelligence conference (IAAI18) and the 8th AAAI Educational advances in artificial intelligence (EAAI-18), 2-7 February 2018, New Orleans, Louisiana, USA. Palo Alto: AAAI Press [online], pages 7928-7933. Available from: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16253

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 8th Symposium on educational advances in artificial intelligence (EAAI-18)
• Start Date: Feb 3, 2018
• End Date: Feb 4, 2018
• Acceptance Date: Nov 9, 2017
• Online Publication Date: Feb 3, 2018
• Publication Date: Apr 27, 2018
• Deposit Date: Dec 7, 2017
• Publicly Available Date: Dec 7, 2017
• Print ISSN: 2159-5399
• Publisher: Association for the Advancement of Artificial Intelligence
• Peer Reviewed: Peer Reviewed
• Pages: 7928-7933
• Series ISSN: 2159-5399
• ISBN: 9781577358008
• Keywords: Learning materials; eLearning; Teaching experts; Knowledge searching
• Public URL: http://hdl.handle.net/10059/2617
• Publisher URL: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16253
• Contract Date: Dec 7, 2017