18 citations · 20 across the 6 of their papers we have counts for
10 papers
The Assistance Dilemma: Learning to Teach via Multi-Turn Reinforcement Learning
Jakub Macina, Manu Kapur, Mrinmaya Sachan
Large language models (LLMs) trained to answer questions are natively poor at teaching. Reinforcement Learning (RL) against a simulated student is a promising approach to improve t…
From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
David Dinucu-Jianu, Jakub Macina, Nico Daheim +3
Large language models (LLMs) can transform education, but their optimization for direct question-answering often undermines effective pedagogy which requires strategically withhold…
MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors
Jakub Macina, Nico Daheim, Ido Hakimi +3
Evaluating the pedagogical capabilities of AI-based tutoring models is critical for making guided progress in the field. Yet, we lack a reliable, easy-to-use, and simple-to-run eva…
Towards the Pedagogical Steering of Large Language Models for Tutoring: A Case Study with Modeling Productive Failure
Romain Puech, Jakub Macina, Julia Chatain +2
One-to-one tutoring is one of the most efficient methods of teaching. With the growing popularity of Large Language Models (LLMs), there have been efforts to create LLM based conve…
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
Nico Daheim, Jakub Macina, Manu Kapur +2
Large language models (LLMs) present an opportunity to scale high-quality personalized education to all. A promising approach towards this means is to build dialog tutoring models…
Book2Dial: Generating Teacher-Student Interactions from Textbooks for Cost-Effective Development of Educational Chatbots
Junling Wang, Jakub Macina, Nico Daheim +2
Educational chatbots are a promising tool for assisting student learning. However, the development of effective chatbots in education has been challenging, as high-quality data is…
MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems
Jakub Macina, Nico Daheim, Sankalan Pal Chowdhury +4
While automatic dialogue tutors hold great potential in making education personalized and more accessible, research on such systems has been hampered by a lack of sufficiently larg…
Opportunities and Challenges in Neural Dialog Tutoring
Jakub Macina, Nico Daheim, Lingzhi Wang +4
Designing dialog tutors has been challenging as it involves modeling the diverse and complex pedagogical strategies employed by human tutors. Although there have been significant r…
Automatic Generation of Socratic Subquestions for Teaching Math Word Problems
Kumar Shridhar, Jakub Macina, Mennatallah El-Assady +3
Socratic questioning is an educational method that allows students to discover answers to complex problems by asking them a series of thoughtful questions. Generation of didactical…
Exploring Customer Price Preference and Product Profit Role in Recommender Systems
Michal Kompan, Peter Gaspar, Jakub Macina +2
Most of the research in the recommender systems domain is focused on the optimization of the metrics based on historical data such as Mean Average Precision (MAP) or Recall. Howeve…