T2MM uses LLM-generated action sequences rather than full code generation to build and edit interactive ecological models in VERA, achieving 92.7% structural match versus 54.5% and 57.4% for 0-shot and N-shot baselines.
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Copa is a theory-guided multimodal LLM agent that supports high school computational modeling through adaptive feedback, shown in a 33-dyad study to increase student confidence and conceptual verbalization without fostering dependence.
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T2MM: An LLM Supported Architecture For Inquiry-Based Modeling
T2MM uses LLM-generated action sequences rather than full code generation to build and edit interactive ecological models in VERA, achieving 92.7% structural match versus 54.5% and 57.4% for 0-shot and N-shot baselines.
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A Theory-Guided LLM Pedagogical Agent for STEM+C Scaffolding Without Over-Reliance
Copa is a theory-guided multimodal LLM agent that supports high school computational modeling through adaptive feedback, shown in a 33-dyad study to increase student confidence and conceptual verbalization without fostering dependence.