View Proposal

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Proposer

Ralph Barthel

Title

Explainable Learning Analytics for Socially Shared Regulation of Learning (SSRL)

Goal

Develop a learning analytics system (e.g. a dashboard) that identifies patterns of regulation in collaborative dialogue and presents them to learners or educators in an interpretable way.

Description

Understanding and capturing small group learning processes in higher education can be challenging. There are multiple benefits of using group work as part of an assessment strategy. Frequently, self- or peer-assessment are being used in this context. However, these approaches are subjective and influenced by group dynamics. Using a learning analytics approach can turn recorded collaborative interactions into insights how groups regulate their work over time. It allows to identify regulatory patterns and to visualise the group collaboration process which can help to distinguish between effective and less effective collaboration. The developed artefact could be an proof of concept of an interactive learning analytics dashboard for example. The data could be collected in a user study or alternatively a suitable data set of recorded group collaboration could be used.

Resources

Background

[1] Villa-Torrano, C., Suraworachet, W., Gómez-Sánchez, E., Asensio-Pérez, J. I., Bote-Lorenzo, M. L., Martínez-Monés, A., Zhou, Q., Cukurova, M., & Dimitriadis, Y. (2025). Using learning design and learning analytics to promote, detect and support Socially-Shared Regulation of Learning: A systematic literature review. Computers & Education, 232, 1–19. [2] Järvelä, S., Järvenoja, H. & Malmberg, J. Capturing the dynamic and cyclical nature of regulation: Methodological Progress in understanding socially shared regulation in learning (2019). Intern. J. Comput.-Support. Collab. Learn 14, 425–441. [3] Malmberg, J; Järvelä, S; Järvenoja, H; Panadero, E (2015). Promoting socially shared regulation of learning in CSCL: Progress of socially shared regulation among high- and low-performing groups. Computers in Human Behavior, 52, 562-572.

Url

Difficulty Level

Variable

Ethical Approval

Full

Number Of Students

2

Supervisor

Ralph Barthel

Keywords

socially shared regulation of learning (ssrl), self-regulated learning (srl), learning analytics, collaborative learning, human-data interaction (hdi)

Degrees

Bachelor of Science in Computer Science
Master of Engineering in Software Engineering
Master of Science in Business Information Management
Master of Science in Data Science
Master of Science in Information Technology (Software Systems)
Bachelor of Science in Computing Science
BSc Data Sciences
BSc Information Systems with Data Analytics