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ERIC Number: EJ1382886
Record Type: Journal
Publication Date: 2023
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0271-0633
EISSN: EISSN-1536-0768
Teachers as Self-Regulated Learners: The Role of Multimodal Data Analytics for Instructional Decision Making
Taub, Michelle; Azevedo, Roger
New Directions for Teaching and Learning, n174 p25-32 Sum 2023
The goal of this chapter is to propose a cyclical process of how teachers can use multimodal multichannel data of cognitive, affective, metacognitive, motivational, and social processes to assist with the understanding of their own and their students' self-regulated learning (SRL), and their subsequent instructional decision making. What differentiates our proposed framework from theories of self-regulated learning is that we propose this cycle occurs throughout all phases of self-regulated learning and in real time. In this chapter, we outline each component of the framework, followed by a discussion of future steps that discuss our future view of the classroom with teachers and how they can use multimodal multichannel data to help them with their instructional decision making. We aim to make it clear that: (1) our proposed stages are non-linear and interdependent, which represents the foundation of SRL theory and the structure of classroom learning, and (2) our proposed framework highlights that using any technological tool to help teachers, not replace them.
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://bibliotheek.ehb.be:2191/en-us
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A