42 citations · 76 across the 6 of their papers we have counts for
6 papers
A Plan-Tracing Interface for AI-Supported Algorithm Planning
Yoshee Jain, Heejin Do, Zihan Wu +1
Planning an algorithm in natural language allows learners to get formative feedback on their approach before coding. But these descriptions can be ambiguous, making it challenging…
Duality-based Mode Operations and Pyramid Multilayer Mapping for Rhetorical Modes
Zi-Niu Wu
Rhetorical modes are useful in both academic and non-academic writing, and can be subjects to be studied within linguistic research and computational modeling. Establishing a conce…
Learner and Instructor Needs in AI-Supported Programming Learning Tools: Design Implications for Features and Adaptive Control
Zihan Wu, Yicheng Tang, Barbara Ericson
AI-supported tools can help learners overcome challenges in programming education by providing adaptive assistance. However, existing research often focuses on individual tools rat…
Personalized Parsons Puzzles as Scaffolding Enhance Practice Engagement Over Just Showing LLM-Powered Solutions
Xinying Hou, Zihan Wu, Xu Wang +1
As generative AI products could generate code and assist students with programming learning seamlessly, integrating AI into programming education contexts has driven much attention…
Insights from Social Shaping Theory: The Appropriation of Large Language Models in an Undergraduate Programming Course
Aadarsh Padiyath, Xinying Hou, Amy Pang +6
The capability of large language models (LLMs) to generate, debug, and explain code has sparked the interest of researchers and educators in undergraduate programming, with many an…
CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming
Xinying Hou, Zihan Wu, Xu Wang +1
Learning to program can be challenging, and providing high-quality and timely support at scale is hard. Generative AI and its products, like ChatGPT, can create a solution for most…