1 citations · 4 across the 7 of their papers we have counts for
10 papers · 1 filter
Beyond One-Size-Fits-All Exercises: Personalizing Computer Science Worksheets with Large Language Models
Franco Ortiz, Runlong Ye, Michael Liut
Large Language Models (LLMs) have been widely applied to student-facing educational tools, this work explores their use in supporting instructors by presenting a practical adaptati…
Exploring Emerging Norms of AI Attribution and Disclosure in Programming Education
Runlong Ye, Oliver Huang, Jessica He +1
Generative AI blurs the lines of authorship in computing education, creating uncertainty around how students should attribute AI assistance. To examine these emerging norms, we con…
Reflexis: Supporting Reflexivity and Rigor in Collaborative Qualitative Analysis through Design for Deliberation
Runlong Ye, Oliver Huang, Patrick Yung Kang Lee +3
Reflexive Thematic Analysis (RTA) is a critical method for generating deep interpretive insights. Yet its core tenets, including researcher reflexivity, tangible analytical evoluti…
TreeWriter: AI-Assisted Hierarchical Planning and Writing for Long-Form Documents
Zijian Zhang, Fangshi Du, Xingjian Liu +5
Long documents pose many challenges to current intelligent writing systems. These include maintaining consistency across sections, sustaining efficient planning and writing as docu…
Exploring Student Choice and the Use of Multimodal Generative AI in Programming Learning
Xinying Hou, Ruiwei Xiao, Runlong Ye +2
The broad adoption of Generative AI (GenAI) is impacting Computer Science education, and recent studies found its benefits and potential concerns when students use it for programmi…
Automated Feedback on Student-Generated UML and ER Diagrams Using Large Language Models
Sebastian Gürtl, Gloria Schimetta, David Kerschbaumer +2
UML and ER diagrams are foundational in computer science education but come with challenges for learners due to the need for abstract thinking, contextual understanding, and master…