3 papers
cs.LG2025
Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency
Daniel Weitekamp, Christopher MacLellan, Erik Harpstead +1
Human learning relies on specialization -- distinct cognitive mechanisms working together to enable rapid learning. In contrast, most modern neural networks rely on a single mechan…
cs.AI2025
TutorGym: A Testbed for Evaluating AI Agents as Tutors and Students
Daniel Weitekamp, Momin N. Siddiqui, Christopher J. MacLellan
Recent improvements in large language model (LLM) performance on academic benchmarks, such as MATH and GSM8K, have emboldened their use as standalone tutors and as simulations of h…
cs.HC2024
AI2T: Building Trustable AI Tutors by Interactively Teaching a Self-Aware Learning Agent
Daniel Weitekamp, Erik Harpstead, Kenneth Koedinger
AI2T is an interactively teachable AI for authoring intelligent tutoring systems (ITSs). Authors tutor AI2T by providing a few step-by-step solutions and then grading AI2T's own pr…