Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism

Penny J Standen
David J Brown
Gosia M Kwiatkowska
Matthew K Belmonte
Maria J Galvez Trigo
Helen Boulton
Andy Burton
Madeline J Hallewell
Nick Shopland
Maria A Blanco Gonzalez
Elena Milli
Stefano Cobello
Annaleda Mazzucato
Marco Traversi

Adaptive Instructional Systems. Design and Evaluation. HCII 2021. Lecture Notes in Computer Science 12792:436-452 (3 July 2021).


ABSTRACT


Adoption of e-learning for those with special needs lags that for mainstream learners. Not much is known about barriers and facilitators that drive this disparity. The present study used focus groups and interviews to collect the views of 21 teachers taking part in preliminary evaluations of an adaptive learning system based on multimodal affect recognition for students with learning disabilities and autism. The system uses multimodal detection of affective state and scoring of performance to drive its adaptive selection of learning material. Five themes captured the teachers’ views of the system’s potential impact, especially regarding learning and engagement but also on factors that might influence adoption. These were: the potential of the system to transform their teaching practice; the ability of the system to impact on learning outcomes; the potential impact on teacher-student/peer to peer relationships; usability issues; and organisational challenges. Despite being highly motivated as volunteer testers, teachers highlighted barriers to adoption, which will need addressing. This finding underscores the importance of involving teachers and students in the design and development process.


To receive a password that will enable you to download a reprint, enter your email address here:


DOWNLOAD REPRINT
(requires password)