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Fine-Grained Open Learner Models: Complexity Versus Support

Guerra-Hollstein, Julio and Barria-Pineda, Jordan and Schunn, Christian D. and Bull, Susan and Brusilovsky, Peter (2017) Fine-Grained Open Learner Models: Complexity Versus Support. In: UMAP 2017, July 09 - 12, 2017, Bratislava, Slovakia.

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Open Learner Models (OLM) show the learner model to users to assist their self-regulated learning by, for example, helping prompt reflection, facilitating planning and supporting navigation. OLMs can show different levels of detail of the underlying learner model, and can also structure the information differently. As a result, a trade-off may exist between the potential for better support for learning and the complexity of the information shown. This paper investigates students' perceptions about whether offering more and richer information in an OLM will result in more effective support for their self-regulated learning. In a first study, questionnaire responses relating to designs for six visualisations of varying complexity led to the implementation of three variations on one of the designs. A second controlled study involved students interacting with these variations. The study revealed that the most useful variation for searching for suitable learning material was a visualisation combining a basic coloured grid, an extended bar chart-like visualisation indicating related concepts, and a learning gauge.


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Item Type: Conference or Workshop Item (Paper)
Status: Published
CreatorsEmailPitt UsernameORCID
Guerra-Hollstein, Julio
Barria-Pineda, JordanJAB464@pitt.eduJAB464
Schunn, Christian D.schunn@pitt.eduschunn
Bull, Susan
Brusilovsky, Peterpeterb0000-0002-1902-1464
Date: 9 July 2017
Date Type: Publication
Publisher: ACM Press
Page Range: pp. 41-49
Event Title: UMAP 2017
Event Dates: July 09 - 12, 2017
Event Type: Conference
DOI or Unique Handle: 10.1145/3079628.3079682
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
Title of Book: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization - UMAP '17
Official URL:
Date Deposited: 12 Dec 2018 19:01
Last Modified: 12 Dec 2018 19:01


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