59 citations · 116 across the 22 of their papers we have counts for
8 papers · 1 filter
Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions
Danielle R. Thomas, Marie Cynthia Abijuru Kamikazi, Ashish Gurung +5
Past research using log data has faced the "learning system wall," whereby few methods exist for generalizing models of student learning across platforms. Increasingly, online lear…
Does the TalkMoves Codebook Generalize to One-on-One Tutoring and Multimodal Interaction?
Corina Luca Focsan, Marie Cynthia Abijuru Kamikazi, Tamisha Thompson +5
Accountable Talk theory has been widely adopted to analyze classroom discourse and is increasingly used to annotate tutoring interactions. In particular, the TalkMoves codebook, gr…
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…
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…
Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors
Sanjit Kakarla, Danielle Thomas, Jionghao Lin +2
Research suggests that tutors should adopt a strategic approach when addressing math errors made by low-efficacy students. Rather than drawing direct attention to the error, tutors…
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation
Danielle R. Thomas, Jionghao Lin, Erin Gatz +8
Artificial intelligence (AI) applications to support human tutoring have potential to significantly improve learning outcomes, but engagement issues persist, especially among stude…