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BrainHood: towards an explainable recommendation system for self-regulated cognitive training in children

Published: 30 June 2020 Publication History

Abstract

There is evidence that cognitive and executive functions are mental capabilities that children need in order to successfully learn in school. Serious Games (SG) and Games for Health (G4H) have been extensively used as tools to promote health and well-being in children. Cognitive games are a type of educational games which focus on enhancing cognitive functioning in children with different profiles of executive functions and cognitive development. We propose a system for self-regulated cognitive training for children, which enables the child to reflect on their own progress, weaknesses and strengths, and self-arrange their training materials, promoting self-regulated learning skills. We provide a narrative review of research in cognitive training for children and in explainable recommendation systems for children in educational settings. Based on the review, an experimental testbed is proposed to explore how transparency, explainability and persuasive strategies can be used to promote self-regulated learning skills in children, considering individual differences on abilities, preferences, and needs.

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      cover image ACM Other conferences
      PETRA '20: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments
      June 2020
      574 pages
      ISBN:9781450377737
      DOI:10.1145/3389189
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • CSE@UTA: Department of Computer Science and Engineering, The University of Texas at Arlington
      • NCRS: Demokritos National Center for Scientific Research

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      Published: 30 June 2020

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      1. cognitive training for children
      2. explainable recommendations
      3. personalization
      4. self-regulation

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      • (2024)Identifying Children Metacognitive Monitoring Performance Through Facial ExpressionsCompanion Proceedings of the 2024 Annual Symposium on Computer-Human Interaction in Play10.1145/3665463.3678790(242-248)Online publication date: 14-Oct-2024
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      • (2024)Not Just Algorithms: Strategically Addressing Consumer Impacts in Information RetrievalAdvances in Information Retrieval10.1007/978-3-031-56066-8_25(314-335)Online publication date: 24-Mar-2024
      • (2023)Personality-based tailored explainable recommendation for trustworthy smart learning system in the age of artificial intelligenceSmart Learning Environments10.1186/s40561-023-00282-610:1Online publication date: 11-Dec-2023
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      • (2022)Self-Regulated Learning and Scientific Research Using Artificial Intelligence for Higher Education SystemsInternational Journal of Technology and Human Interaction10.4018/IJTHI.30622618:7(1-15)Online publication date: 9-Sep-2022
      • (2022)Educational Explainable Recommender Usage and its Effectiveness in High School Summer Vacation AssignmentLAK22: 12th International Learning Analytics and Knowledge Conference10.1145/3506860.3506882(458-464)Online publication date: 21-Mar-2022
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