11 citations · 11 across the 8 of their papers we have counts for
4 papers · 1 filter
Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs
Ashish Gurung, Ge Gao, Jordan Gutterman +6
Hybrid human-AI tutoring, where technology and humans jointly facilitate student learning, can be more beneficial than AI-only tutoring. However, preliminary evidence suggests that…
Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study
Calvin Isley, Joshua Gilbert, Evangelos Kassos +9
While large language models (LLMs) challenge conventional methods of teaching and learning, they present an exciting opportunity to improve efficiency and scale high-quality instru…
The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances
Allen Nie, Yash Chandak, Miroslav Suzara +6
Large language models (LLMs) are quickly being adopted in a wide range of learning experiences, especially via ubiquitous and broadly accessible chat interfaces like ChatGPT and Co…
Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data
Ge Gao, Amelia Leon, Andrea Jetten +4
Educational stakeholders are often particularly interested in sparse, delayed student outcomes, like end-of-year statewide exams. The rare occurrence of such assessments makes it h…