Khan-Galaria, M;
Cukurova, M;
Luckin, R;
(2020)
A Framework for Exploring the Impact of Tutor Practices on Learner Self-regulation in Online Environments.
In:
Artificial Intelligence in Education.
(pp. pp. 135-139).
Springer Nature
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Abstract
There is increasing interest in the conceptualization of Self-Regulated learning (SRL) as a dynamic process which unfolds over the course of a learning activity. This is partly because this conceptualization could potentially be operationalized and used as the basis for AI and analytics tools which monitor and scaffold SRL in real-time. However, while there is an abundance of research on theories of SRL, little research explicitly reviews and operationalizes such theoretical considerations. Work is needed to develop frameworks for the practical applications of fundamental SRL theories, helping researchers move from conceptual considerations to operationalization in real world settings. In this paper, we propose a theoretically grounded framework for investigating SRL in the context of online tutoring for upper primary school learners. SRL is interpreted as a social learning construct, and the framework proposed is designed to investigate the influence of tutor practices on the development of learners’ SRL. We present the results of a pilot study that explored the applicability of the framework.
Type: | Proceedings paper |
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Title: | A Framework for Exploring the Impact of Tutor Practices on Learner Self-regulation in Online Environments |
Event: | 21st International Conference, AIED 2020 |
ISBN-13: | 978-3-030-52239-1 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-030-52240-7_25 |
Publisher version: | https://doi.org/10.1007/978-3-030-52240-7_25 |
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: | Self-regulated learning, online tutoring, Winne and Hadwin model, tutor practices, metacognition, virtual classroom environment, process mining |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
URI: | https://discovery.ucl.ac.uk/id/eprint/10106760 |




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