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Automating conversational tutors from text

Published on:

26 September 2023

Primary Category:

Computation and Language

Paper Authors:

Robin Schmucker,

Meng Xia,

Amos Azaria,

Tom Mitchell


Key Details

Proposes a novel workflow to induce full conversational tutors from text via LLMs

Orchestrates tutoring via two agents in student and professor roles

Improved helpfulness/coherence ratings but not test scores in user study

Enables more scalable authoring of conversational tutors

Provides insights for future LLM-based educational systems

AI generated summary

Automating conversational tutors from text

This paper introduces a new type of conversational tutoring system that uses large language models to automatically generate tutoring scripts from lesson texts, and orchestrate them via two AI agents acting as a student and professor. In a user study, the system improved helpfulness and coherence ratings, though didn't significantly impact test scores.

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