6 papers
Leveraging LLMs to Assess Tutor Moves in Real-Life Dialogues: A Feasibility Study
Danielle R. Thomas, Conrad Borchers, Jionghao Lin +6
Tutoring improves student achievement, but identifying and studying what tutoring actions are most associated with student learning at scale based on audio transcriptions is an ope…
Detecting LLM-Generated Short Answers and Effects on Learner Performance
Shambhavi Bhushan, Danielle R Thomas, Conrad Borchers +5
The increasing availability of large language models (LLMs) has raised concerns about their potential misuse in online learning. While tools for detecting LLM-generated text exist…
LLM-Generated Feedback Supports Learning If Learners Choose to Use It
Danielle R. Thomas, Conrad Borchers, Shambhavi Bhushan +3
Large language models (LLMs) are increasingly used to generate feedback, yet their impact on learning remains underexplored, especially compared to existing feedback methods. This…
Comparing Few-Shot Prompting of GPT-4 LLMs with BERT Classifiers for Open-Response Assessment in Tutor Equity Training
Sanjit Kakarla, Conrad Borchers, Danielle Thomas +2
Assessing learners in ill-defined domains, such as scenario-based human tutoring training, is an area of limited research. Equity training requires a nuanced understanding of conte…
Do Tutors Learn from Equity Training and Can Generative AI Assess It?
Danielle R. Thomas, Conrad Borchers, Sanjit Kakarla +5
Equity is a core concern of learning analytics. However, applications that teach and assess equity skills, particularly at scale are lacking, often due to barriers in evaluating la…
Does Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT
Danielle R. Thomas, Conrad Borchers, Sanjit Kakarla +5
The role of multiple-choice questions (MCQs) as effective learning tools has been debated in past research. While MCQs are widely used due to their ease in grading, open response q…