7 papers · 1 filter
Agreement Is Not Quality: Blind Expert Verification of Human and LLM Qualitative Coding When Human Consensus Is Not Ground Truth
Alex Liu, Lief Esbenshade, Michael Xiao +4
Evaluations of LLM-assisted qualitative coding almost universally measure model performance as agreement with human coders, a practice that presumes human coding is the standard to…
Human-LLM Collaborative Inductive Coding for Conceptualizing K-12 Educator AI Use
Alex Liu, Min Sun, Lief Esbenshade +4
Qualitative researchers increasingly encounter interaction corpora whose scale exceeds what manual coding alone can address, and large language models (LLMs) are frequently propose…
How K-12 Educators Use AI: LLM-Assisted Qualitative Analysis at Scale
Alex Liu, Lief Esbenshade, Shawon Sarkar +4
This study investigates how K-12 educators use generative AI tools in real-world instructional contexts and how large language models (LLMs) can support scalable qualitative analys…
AI as a Teaching Partner: Early Lessons from Classroom Codesign with Secondary Teachers
Alex Liu, Lief Esbenshade, Shawon Sarkar +6
This report presents a comprehensive account of the Colleague AI Classroom pilot, a collaborative design (co-design) study that brought generative AI technology directly into real…
Emerging Patterns of GenAI Use in K-12 Science and Mathematics Education
Lief Esbenshade, Shawon Sarkar, Drew Nucci +10
In this report, we share findings from a nationally representative survey of US public school math and science teachers, examining current generative AI (GenAI) use, perceptions, c…
Implementation Considerations for Automated AI Grading of Student Work
Zewei Tian, Alex Liu, Lief Esbenshade +4
This study explores the classroom implementation of an AI-powered grading platform in K-12 settings through a co-design pilot with 19 teachers. We combine platform usage logs, surv…