OpineBot: Class Feedback Reimagined Using a Conversational LLM

Henansh Tanwar; Kunal Shrivastva; Rahul Singh; Dhruv Kumar

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arXiv · 2401.15589

OpineBot: Class Feedback Reimagined Using a Conversational LLM

Henansh Tanwar·Kunal Shrivastva·Rahul Singh·Dhruv Kumar

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Abstract

Conventional class feedback systems often fall short, relying on static, unengaging surveys offering little incentive for student participation. To address this, we present OpineBot, a novel system employing large language models (LLMs) to conduct personalized, conversational class feedback via chatbot interface. We assessed OpineBot's effectiveness in a user study with 20 students from an Indian university's Operating-Systems class, utilizing surveys and interviews to analyze their experiences. Findings revealed a resounding preference for OpineBot compared to conventional methods, highlighting its ability to engage students, produce deeper feedback, offering a dynamic survey experience. This research represents a work in progress, providing early results, marking a significant step towards revolutionizing class feedback through LLM-based technology, promoting student engagement, and leading to richer data for instructors. This ongoing research presents preliminary findings and marks a notable advancement in transforming classroom feedback using LLM-based technology to enhance student engagement and generate comprehensive data for educators.

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Henansh Tanwar, Kunal Shrivastva, Rahul Singh, Dhruv Kumar. 2024-01-28. OpineBot: Class Feedback Reimagined Using a Conversational LLM. https://arxiv.org/abs/2401.15589

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