Accepted Full Research Papers 

(in the order of the randomized paper ID)

CFlow: Supporting Semantic Flow Analysis of Students’ Code in Programming Problems at Scale
Ashley Zhang (University of Michigan), Xiaohang Tang (Virginia Tech), Steve Oney (University of Michigan) and Yan Chen (Virginia Tech)

Multimodal deep learning for classifying student-generated questions in computer-supported collaborative learning
Han Kyul Kim (University of Southern California), Aleyeh Roknaldin (University of Southern California), Shriniwas Nayak (University of Southern California), Aditya Chavan (University of Southern California) and Stephen C.-Y. Lu (University of Southern California)

Handwritten Code Digitalization Tools for Broadening Access to CS Education
Md Sazzad Islam (Stanford University), Moussa Koulako Bala Doumbouya (Stanford University), Christopher D. Manning (Stanford University) and Chris Piech (Stanford University)

Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning
Frederik Baucks (Ruhr-Universität Bochum), Robin Schmucker (Carnegie Mellon University), Conrad Borchers (Carnegie Mellon University), Zachary A. Pardos (University of California, Berkeley) and Laurenz Wiskott (Ruhr-Universität-Bochum)

Automated Quality Assessment of Multimodal Mathematical Stories Generated by Generative Artificial Intelligence: Text-Image Coherence and Grade Level Appropriateness
Hai Li (University of Florida), Rui Guo (University of Florida), Chenglu Li (University of Utah) and Wanli Xing (University of Florida)

Automated Generation and Tagging of Knowledge Components From Multiple-Choice Question
Steven Moore (Carnegie Mellon University), Robin Schmucker (Carnegie Mellon University), John Stamper (Carnegie Mellon University) and Tom Mitchell (Carnegie Mellon University)

Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation
Xinyi Lu (University of Michigan) and Xu Wang (University of Michigan)

CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming
Xinying Hou (University of Michigan), Zihan Wu (University of Michigan), Xu Wang (University of Michigan) and Barbara Ericson (University of Michigan)

Simulating Climate Change Discussion with Large Language Models: Considerations for Science Communication at Scale
Ha Nguyen (Utah State University), Victoria Nguyen (University of California, Irvine), Saríah López-Fierro (Utah State University), Sara Ludovise (Orange County Department of Education) and Rossella Santagata (University of California, Irvine)

Edgeworth: Efficient and Scalable Authoring of Visual Thinking Activities
Wode Ni (Carnegie Mellon University), Sam Estep (Carnegie Mellon University), Hwei-Shin Harriman (Carnegie Mellon University), Kenneth Koedinger (Carnegie Mellon University) and Joshua Sunshine (Carnegie Mellon University)

“I believe I did not preach into the desert”: Opportunities & Challenges in Scaling Teacher Mentorship through Mobile Technology in Rural Côte d’Ivoire
Tricia Ngoon (Carnegie Mellon University), Vikram Kamath Cannanure (Carnegie Mellon University), Kaja Jasinska (University of Toronto), Sharon Wolf (University of Pennsylvania) and Amy Ogan (Carnegie Mellon University)

Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study
Wenhan Lyu (William & Mary), Yimeng Wang (William & Mary), Tingting Rachel Chung (William & Mary), Yifan Sun (William & Mary) and Yixuan Zhang (William & Mary)

From One-Size-Fits-All to Individualisation: Redefining MOOCs through Flexible Learning Paths
Selina Reinhard (Hasso Plattner Institute), Sebastian Serth (Hasso Plattner Institute), Thomas Staubitz (German University of Digital Science) and Christoph Meinel (Hasso Plattner Institute)

Ten Years, Ten Trends: The First Decade of an Affordable At-Scale Degree
David Joyner (Georgia Institute of Technology) and Alex Duncan (Georgia Institute of Technology)

Prompting for Comprehension: Exploring the Intersection of Explain in Plain English Questions and Prompt Writing
David Smith (University of Illinois Urbana-Champaign), Paul Denny (University of Auckland) and Max Fowler (University of Illinois Urbana-Champaign)

Combining LLM-Generated and Test-Based Feedback in a MOOC for Programming
Hagit Gabbay (Tel Aviv University) and Anat Cohen (Tel Aviv University)

AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and Guardrails
Sankalan Pal Chowdhury (ETH Zurich), Vilém Zouhar (ETH Zurich) and Mrinmaya Sachan (ETH Zurich)

Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms
Harsh Kumar (University of Toronto), Ruiwei Xiao (Carnegie Mellon University), Benjamin Lawson (University of Toronto), Ilya Musabirov (University of Toronto), Jiakai Shi (University of Toronto), Xinyuan Wang (University of Toronto), Huayin Luo (University of Toronto), Joseph Williams (University of Toronto), Anna Rafferty (Carleton College), John Stamper (Carnegie Mellon University) and Michael Liut (University of Toronto Mississauga)

New Coding Assignments and the First Repository Effect on Inter-Semester Plagiarism
Keith Adkins (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)

Influence on Judgements of Learning Given Perceived AI Annotations
Warren Li (University of Michigan) and Christopher Brooks (University of Michigan)

STEM Pathways in a Global Context: Are Male and Female Learners Motivated the Same?
Yiwen Lin (University of California, Irvine) and Nia Nixon (University of California, Irvine)

Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS Course
Binglin Chen (University of Illinois at Urbana-Champaign), Colleen Lewis (University of Illinois at Urbana-Champaign), Matthew West (University of Illinois at Urbana-Champaign) and Craig Zilles (University of Illinois at Urbana-Champaign)