1 citations · 2 across the 8 of their papers we have counts for
9 papers
Domain-Adapted Retrieval for In-Context Annotation of Pedagogical Dialogue Acts
Jinsook Lee, Kirk Vanacore, Zhuqian Zhou +2
Automated annotation of pedagogical dialogue is a high-stakes task where LLMs often fail without sufficient domain grounding. We present a domain-adapted RAG pipeline for tutoring…
The Digital Divide in Generative AI: Evidence from Large Language Model Use in College Admissions Essays
Jinsook Lee, Conrad Borchers, AJ Alvero +2
Large language models (LLMs) have become popular writing tools among students and may expand access to high-quality feedback for students with less access to traditional writing su…
LLM Reasoning Predicts When Models Are Right: Evidence from Coding Classroom Discourse
Bakhtawar Ahtisham, Kirk Vanacore, Zhuqian Zhou +2
Large Language Models (LLMs) are increasingly deployed to automatically label and analyze educational dialogue at scale, yet current pipelines lack reliable ways to detect when mod…
Utility-Preserving De-Identification for Math Tutoring: Investigating Numeric Ambiguity in the MathEd-PII Benchmark Dataset
Zhuqian Zhou, Kirk Vanacore, Bakhtawar Ahtisham +7
Large-scale sharing of dialogue data is key to advancing the science of teaching and learning, yet rigorous de-identification remains a major barrier. In mathematics tutoring trans…
Codebook-Injected Dialogue Segmentation for Multi-Utterance Constructs Annotation: LLM-Assisted and Gold-Label-Free Evaluation
Jinsook Lee, Kirk Vanacore, Zhuqian Zhou +3
Dialogue Act (DA) annotation typically treats communicative or pedagogical intent as localized to individual utterances or turns. This leads annotators to agree on the underlying a…
AI Annotation Orchestration: Evaluating LLM verifiers to Improve the Quality of LLM Annotations in Learning Analytics
Bakhtawar Ahtisham, Kirk Vanacore, Jinsook Lee +3
Large Language Models (LLMs) are increasingly used to annotate learning interactions, yet concerns about reliability limit their utility. We test whether verification-oriented orch…
Poor Alignment and Steerability of Large Language Models: Evidence from College Admission Essays
Jinsook Lee, AJ Alvero, Thorsten Joachims +1
People are increasingly using technologies equipped with large language models (LLM) to write texts for formal communication, which raises two important questions at the intersecti…
Algorithms for College Admissions Decision Support: Impacts of Policy Change and Inherent Variability
Jinsook Lee, Emma Harvey, Joyce Zhou +3
Each year, selective American colleges sort through tens of thousands of applications to identify a first-year class that displays both academic merit and diversity. In the 2023-20…
The Life Cycle of Large Language Models: A Review of Biases in Education
Jinsook Lee, Yann Hicke, Renzhe Yu +2
Large Language Models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based appl…