activity
20242026
collaborators

16 papers

cs.CL2026

Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization

Jaewook Lee, Alexander Scarlatos, Simon Woodhead +1

With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become increasingly prominent. Prior wo…

cs.CL2026

Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues

Zhangqi Duan, Shuyan Huang, Alexander Scarlatos +3

A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor m…

cs.CL2026

CodeGENCAT: Generative Computerized Adaptive Testing for Open-ended Coding Problems

Wanyong Feng, Alexander Scarlatos, Ruochen Sun +1

Existing Computerized Adaptive Testing (CAT) frameworks typically select questions based on the predicted likelihood that the student will answer correctly. This design ignores inf…

cs.AI2026

Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steering

Hunter McNichols, Alexander Scarlatos, Mihai Dascalu +2

An effective method of teaching across disciplines is to provide examples of high-quality work. However, an example may be significantly different from a student's current work, ma…

cs.CL2026

Simulated Students in Tutoring Dialogues: Substance or Illusion?

Alexander Scarlatos, Jaewook Lee, Simon Woodhead +1

Advances in large language models (LLMs) enable many new innovations in education. However, evaluating the effectiveness of new technology requires real students, which is time-con…

cs.CL2026

Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues

Shuyan Huang, Alexander Scarlatos, Jaewook Lee +1

Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue. To enable these tutoring s…