2 papers
cs.CL2026
Using Learning Progressions to Guide AI Feedback for Science Learning
Xin Xia, Nejla Yuruk, Yun Wang +1
Generative artificial intelligence (AI) offers scalable support for formative feedback, yet most AI-generated feedback relies on task-specific rubrics authored by domain experts. W…
cs.CY2026
Simulating Validity: Modal Decoupling in MLLM Generated Feedback on Science Drawings
Arne Bewersdorff, Nejla Yuruk, Xiaoming Zhai
In science education, students frequently construct hand-drawn visual models of scientific phenomena. These drawings rely on a visual structure where information is encoded through…