SLA-LENS: From Classroom Transcripts to CSLA-Informed and Evidence-Linked L2 Interaction Analytics
We introduce SLA-LENS, an end-to-end LLM-assisted framework that connects classroom transcripts to structured pedagogical annotations and evidence-linked descriptive analytics.
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Key points
- What happens after a learner makes an error, and how does the instructor's response shape the next turn?
- Investigating these exchanges across classrooms requires context-sensitive annotation that is difficult to scale manually.
- Grounded in interactionist Second Language Acquisition (SLA) theory, its annotation schema captures second language learner errors, pedagogical functions, and uptake or repair while accounting for speaker roles, conversational context, and hierarchical labels.
- We apply the framework to 40 authentic online L2 Spanish classroom transcripts comprising over 21,000 sentence-level instances.
Sources (1)
- [1]SLA-LENS: From Classroom Transcripts to CSLA-Informed and Evidence-Linked L2 Interaction AnalyticsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 09:33 PM
We introduce SLA-LENS, an end-to-end LLM-assisted framework that connects classroom transcripts to structured pedagogical annotations and evidence-linked descriptive analytics.
What happens after a learner makes an error, and how does the instructor's response shape the next turn?
Extractive summary: sentences quoted from the sources.
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