338 citations · 494 across the 10 of their papers we have counts for
10 papers
To Police or to Guide: How Higher Education Computer Science Instructors Design and Implement Generative AI Policies
Xingjian Gu, Wells Lucas Santo, James M. Zumel Dumlao +1
While generative AI tools are directly changing how undergraduate computer science is learned and taught, they are also reshaping the relationships between instructors and students…
AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Xingjian Gu, Barbara J. Ericson
Even though AI literacy has emerged as a prominent education topic in the wake of generative AI, its definition remains vague. There is little consensus among researchers and pract…
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…
Integrating Personalized Parsons Problems with Multi-Level Textual Explanations to Scaffold Code Writing
Xinying Hou, Barbara J. Ericson, Xu Wang
Novice programmers need to write basic code as part of the learning process, but they often face difficulties. To assist struggling students, we recently implemented personalized P…
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…
Critiquing Computing Artifacts through Programming Satirical Python Scripts
Aadarsh Padiyath, Tamara Nelson-Fromm, Barbara Ericson
Computing artifacts tend to exclude marginalized students, so we must create new methods to critique and change them. We studied the potential for "satirical programming" to critiq…
Understanding the Effects of Using Parsons Problems to Scaffold Code Writing for Students with Varying CS Self-Efficacy Levels
Xinying Hou, Barbara J. Ericson, Xu Wang
Introductory programming courses aim to teach students to write code independently. However, transitioning from studying worked examples to generating their own code is often diffi…
How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environment
Majeed Kazemitabaar, Xinying Hou, Austin Henley +3
As Large Language Models (LLMs) gain in popularity, it is important to understand how novice programmers use them. We present a thematic analysis of 33 learners, aged 10-17, indepe…
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma +3
AI code generators like OpenAI Codex have the potential to assist novice programmers by generating code from natural language descriptions, however, over-reliance might negatively…