Affective Support for Self-Regulation in Mobile-Assisted Language Learning

Viberg, Olga; Kukulska-Hulme, Agnes and Peeters, Ward (2023). Affective Support for Self-Regulation in Mobile-Assisted Language Learning. International Journal of Mobile and Blended Learning, 15(2), article no. 26.

DOI: https://doi.org/10.4018/IJMBL.318226

Abstract

Mobile-assisted language learning (MALL) research includes examination and development of second language learners' cognitive and metacognitive self-regulated learning skills, but the affective learning component of self-regulation in this context remains largely unexplored. Support for affective learning, which is defined by learners' beliefs, attitudes, and emotions, has been shown to influence learners' cognitive processes, performance, and engagement considerably, and is therefore critical to promote and foster throughout the learning process. This paper defines the importance of supporting affect in MALL, sets out a theoretical perspective on supporting affective self-regulation in MALL, and elaborates on what designers and teachers can do to facilitate affective development through the use of mobile technology, learning analytics, and artificial intelligence. It examines and further delineates the role of affective computing and the role of the teacher in fully harnessing the affective affordances of MALL.

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About

• Item ORO ID
• 87577
• Item Type
• Journal Item
• ISSN
• 1941-8655
• Keywords
• Affect; Artificial Intelligence; Learner Autonomy; Learning Analytics; L2 Learning; Mobile App Design; Mobile Assisted Language Learning; Self-regulated Learning; Learner support
• Academic Unit or School
• Institute of Educational Technology (IET)
• Research Group
• OpenTEL
• Copyright Holders
• © 2023 The Authors
• Depositing User
• Agnes Kukulska-Hulme