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Monitoring Tutor Practices to Support Self-regulated Learning in Online One-To-One Tutoring Sessions with Process Mining

Cukurova, Mutlu; Khan-Galaria, M; (2022) Monitoring Tutor Practices to Support Self-regulated Learning in Online One-To-One Tutoring Sessions with Process Mining. In: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. AIED 2022. (pp. pp. 405-409). Springer: Cham, Switzerland.

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Abstract

This paper reports on research that aims to examine what tutoring practices in an online environment can promote students’ self-regulated learning (SRL). First, we propose a theoretically grounded framework of signifiers that can be used to track tutor-student interactions with respect to SRL. Second, we operationalize the framework using log data from a virtual learning environment and process mining approaches. Our results demonstrate that there are structural differences in tutor-learner interactions between the high performing versus low performing tutors. High performing tutors show complex patterns of engagement, which emphasize open-ended questioning and reasoning. Whilst the low performing tutors use a more restricted range of teaching practices that focus on instruction and are more strictly led by the learning platf

Type: Proceedings paper
Title: Monitoring Tutor Practices to Support Self-regulated Learning in Online One-To-One Tutoring Sessions with Process Mining
Event: AIED 2022: The 23rd International Conference on Artificial Intelligence in Education,
Location: Durham, UK
Dates: 27 Jul 2022 - 31 Jul 2022
ISBN-13: 978-3-031-11647-6
DOI: 10.1007/978-3-031-11647-6_80
Publisher version: https://doi.org/10.1007/978-3-031-11647-6_80
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, Process mining, Virtual classroom environment framework of signifiers
UCL classification: 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
UCL > Provost and Vice Provost Offices > School of Education
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10156278
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