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Automated Evaluation of Classroom Instructional Support with LLMs and BoWs: Connecting Global Predictions to Specific Feedback
Feb. 27, 2024, 5:50 a.m. | Jacob Whitehill, Jennifer LoCasale-Crouch
cs.CL updates on arXiv.org arxiv.org
Abstract: With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate ``Instructional Support'' domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning architecture that uses either zero-shot prompting of Meta's Llama2, and/or a classic Bag of Words (BoW) model, to classify individual utterances of teachers' speech (transcribed automatically …
abstract aim arxiv assessment automated class classroom cs.ai cs.cl domain evaluation explore feedback global language language models large language large language models llms predictions scoring support teachers teaching type
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