Piotrkowicz, A, Dimitrova, V orcid.org/0000-0002-7001-0891, Hallam, J orcid.org/0000-0002-1044-0515 et al. (1 more author) (2020) Towards Personalisation for Learner Motivation in Healthcare: A Study on Using Learner Characteristics to Personalise Nudges in an e-Learning Context. In: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 2020 Proceeding. UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization, 14-17 Jul 2020, Genoa Italy. ACM , pp. 287-292. ISBN 9781450379502
Abstract
Lifelong learning is a key requirement for anyone working in healthcare, but many healthcare professionals find it challenging to undertake learning activities during their daily tasks. Digital solutions such as e-learning have been proposed to encourage and support the self-management of learning activities. In order to enhance the effectiveness of e-learning provision, personalised interventions in the form of prompts or nudges can be used, but first we need to ascertain (i) what kind of nudges are effective in an e-learning scenario, and (ii) which learner characteristics will be useful for personalisation of such nudges. In this paper we report the results of a study among medical and healthcare students which looks at the relationships between users' interests, demographics and psychological traits, and the perceived effectiveness of five choice architecture techniques implemented as textual nudges on an e-learning platform in the healthcare domain. We found that even without personalisation different nudges vary in effectiveness in this context, and that interest (and to lesser extent other user characteristics) influence the perceived effectiveness of nudges. We finish with a set of recommendations for nudge design in this domain.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Personalization, Learner Models, Nudges, e-Learning, Medical Education |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Education > Medical Education Unit (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Sep 2021 14:22 |
Last Modified: | 30 Sep 2021 14:22 |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/3386392.3399290 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:178636 |