Our publication titled „Development and Evaluation of an AI-Supported Teacher Assistant Tool (AI-TAT) to Foster Self-Regulated Learning“ has been published.
Abstract:
Self-regulated learning (SRL) is increasingly recognised as a key competence for students, yet many teachers struggle to integrate SRL concepts into concrete classroom materials like worksheets. In this paper, SRLly is presented, an AI-supported teacher assistance tool (AI-TAT) that helps teachers revise existing worksheets to better scaffold SRL processes. Rather than submitting entire documents to a large language model (LLM), SRLly performs local preprocessing of uploaded PDFs to extract text with positional metadata, segments the worksheet into meaningful blocks, and sends only relevant blocks for analysis. Based on this structured representation, the system generates actionable recommendations aligned with four SRL dimensions (planning, strategy, monitoring, reflection). Recommendations are presented in an easy-to-use interface that supports teachers’ workflows by providing short rationales and concrete recommendations with ready-to-use text snippets that can be copied. We conducted an initial evaluation during a teacher professional development training with 30 teachers at an Austrian school (student age range 10–18). Overall perceptions were positive: 76% of participants rated SRLly as good or very good. Likert-scale results indicated high perceived usefulness and feasibility, while trustworthiness ratings were more mixed, highlighting reliability of AI output as a key area for improvement. Our findings suggest that structured, material-centred AI feedback can support teachers in integrating SRL into everyday worksheet design, while underscoring the need for stronger reliability and real-world validation.
[full article @ publisher’s homepage]
[draft @ ResearchGate]
Reference: Geier, G., Ebner, M., Burgsteiner, H. (2026). Development and Evaluation of an AI-Supported Teacher Assistant Tool (AI-TAT) to Foster Self-Regulated Learning. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2026. Lecture Notes in Computer Science, vol 16733. Springer, Cham. https://doi.org/10.1007/978-3-032-30784-2_12