activity
20242026
most citedCodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs

235 citations · 245 across the 15 of their papers we have counts for

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Showing 2026Show all

9 papers · 1 filter

cs.CY2026

Correctness, Convergence, and AI-Generated Code Detection: A Longitudinal Study of Student and Large Language Model Code in Introductory Programming

Runlong Ye, Jing Fan, Angela Zavaleta Bernuy +4

Large language models can generate plausible solutions to programming assignments, making it tempting to detect their use by matching student code against a reference bank of gener…

cs.HC2026

Who Bears the Cost of Honesty? A FAccT Workshop Synthesis and Research Agenda for Equitable AI Disclosure

Runlong Ye, Jessica He, Finola Finn +4

AI disclosure is increasingly promoted and sometimes required as a route to transparency, accountability, provenance, and trust. Yet disclosure can also expose AI users to suspicio…

cs.HC2026★ 1 cited

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…

cs.HC2026

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…

cs.HC2026★ 1 cited

From Toil to Thought: Designing for Strategic Exploration and Responsible AI in Systematic Literature Reviews

Runlong Ye, Naaz Sibia, Angela Zavaleta Bernuy +4

Systematic Literature Reviews (SLRs) are fundamental to scientific progress, yet the process is hindered by a fragmented tool ecosystem that imposes a high cognitive load. This fri…

cs.HC2026

Transforming GenAI Policy to Prompting Instruction: An RCT of Scalable Prompting Interventions in a CS1 Course

Ruiwei Xiao, Runlong Ye, Xinying Hou +4

Despite universal GenAI adoption, students cannot distinguish task performance from actual learning and lack skills to leverage AI for learning, leading to worse exam performance w…

cs.HC2026★ 1 cited

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…

cs.HC2026

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…

cs.HC2026

A Comparative Study of Student Perspectives on Technical Writing Feedback Quality: Evaluating LLMs, SLMs, and Humans in Computer Science Topics

Suqing Liu, Runlong Ye, Christopher Eaton +2

To address the scalability of feedback in computer science while mitigating the privacy and cost limitations of commercial Large Language Models (LLMs), this study evaluates a loca…