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What's in it for me?: Augmenting recommended learning resources with navigable annotations

Bulathwela, S; Kreitmayer, S; Pérez-Ortiz, M; (2020) What's in it for me?: Augmenting recommended learning resources with navigable annotations. In: IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces Companion. (pp. pp. 114-115). Association for Computing Machinery: New York, NY, USA. Green open access

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Abstract

This paper introduces an interface that enables the user to quickly identify relevant fragments within multiple long documents. The proposed method relies on a machine-generated layer of annotations that reveals the coverage of topics per fragment and document. To illustrate how the annotations double as a tool for preview as well as navigation, an example application is presented in the form of a personalised learning system that recommends relevant fragments of video lectures according to user's history. Potential implications of this approach for lifelong learning are discussed. We argue that this approach is generally applicable to recommender and information retrieval systems, across multiple knowledge domains and document types.

Type: Proceedings paper
Title: What's in it for me?: Augmenting recommended learning resources with navigable annotations
Event: IUI '20: 25th International Conference on Intelligent User Interfaces
ISBN-13: 9781450371186
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3379336.3381457
Publisher version: https://doi.org/10.1145/3379336.3381457
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Recommender Systems, Information Retrieval, User Modeling, Intelligent Tutoring Systems, Open Education Resources, OER, Future User Interfaces
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10095671
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