Paper Info
Title
Towards Hybrid Human-System Regulation: Understanding Children' SRL Support Needs in Blended Classrooms
Abstract
This paper proposes a new approach to translate learner data into self-regulated learning support. Learning phases in blended classrooms place unique requirements on students' self-regulated learning (SRL). Learning path graphs merge moment-by-moment learning curves and learning phase data to understand student' SRL support needs. Results indicate 4 groups with different SRL support needs. Students in the self-regulated learning group are capable of learning without external regulation. In the teacher regulation group students need initial teacher regulation but rely on SRL thereafter. Students in the system regulation group require teacher and system regulation to learn. Finally, the advanced system support group is in need of support beyond the current level of system regulation. Based on these insights, the application of personalized dashboards and hybrid human-system regulation is further specified.
Year
DOI
Venue
2019
10.1145/3303772.3303780
Proceedings of the 9th International Conference on Learning Analytics & Knowledge
Keywords
Field
DocType
Adaptive Learning Technologies, Blended Classrooms, Hybrid Human-System Intelligence, Self-Regulated Learning
Graph,Self-regulated learning,Learning support,Support group,Computer science,Knowledge management,Merge (version control),Learning curve,Dashboard (business)
Conference
ISBN
Citations 
PageRank 
978-1-4503-6256-6
0
0.34
References 
Authors
12
3
Name
Order
Citations
PageRank
Inge Molenaar1367.81
Anne Horvers200.68
Ryan S. J. d. Baker31220111.60