Analytics of scaffold compliance for self-regulated learning
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The shift toward digitally-based education has emphasised the need for learners to have strong skills for self-regulated learning (SRL). The use of scaffolding prompts is seen as an effective way to stimulate SRL and enhance academic outcomes. A key aspect of SRL scaffolding prompts is the degree to which they are complied to by students. Compliance is a complex concept, one that is further complicated by the nature of scaffold design in the context of adaptability. These nuances notwithstanding, scaffold compliance demands specific exploration. To that end, we conducted a study in which we: 1) focused specifically on scaffolding interaction behaviour in a timed online assessment task, as opposed to the broader interaction with non-scaffolding artefacts; 2) identified distinct scaffold interaction patterns in the context of compliance and non-compliance to scaffold design; 3) analysed how groups of learners traverse compliant and non-compliant interaction behaviours and engage in SRL processes in response to a sequence of timed and personalised SRL-informed scaffold prompts. We found that scaffold interactions fell into two categories of compliance and non-compliance, and whilst there was a healthy engagement with compliance, it does ebb and flow during an online timed assessment.
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A recurring challenge has been learners' suboptimal interactions with SRL support tools, such as when and how to use them to support learning.
“Yet, regardless of design, a recurring challenge has been learners' suboptimal interactions with these tools, such as when and how to use them to support learning.”
From How do students regulate their learning with a genAI chatbot? (2026) · cites this paper as Saint et al., 2024
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How do students regulate their learning with a genAI chatbot?
Lim, L., & Bannert, M. (2026) · Learning Letters · doi:10.20851/ll.v8.61
- Authors
- Saint, J., Fan, Y., & Gasevic, D.
- Affiliations
- Regent's University London (GB)
- Peking University (CN)
- Monash University, Australia
- Venue
- Proceedings of the 14th Learning Analytics and Knowledge Conference
- Publisher
- ACM
- Published
- 2024-03-18
- Pages
- 326-337
- OpenAlex
- W4392484148
- Cited by
- 4
- References
- 4
- Citations by year
- 2026: 1 · 2025: 3
- FWCI
- 6.16
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Learning Analytics and Knowledge (LAK) (publishedVersion)
- HAL (submittedVersion)
- Funders
- Australian Research Council (DP220101209, DP240100069)
- Economic and Social Research Council of the United Kingdom (ES/S015701/1)
- Jacobs Foundation (CELLA 2 CERES)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- student self-regulation, scaffold design, online assessment, adaptive learning
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