activity
20232025
most citedInsights from Social Shaping Theory: The Appropriation of Large Language Models in an Undergraduate Programming Course

34 citations · 77 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC2025

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…

cs.HC2025

Bridging Cultural Distance Between Models Default and Local Classroom Demands: How Global Teachers Adopt GenAI to Support Everyday Teaching Practices

Ruiwei Xiao, Qing Xiao, Xinying Hou +4

Generative AI (GenAI) is rapidly entering K-12 classrooms, offering teachers new ways for teaching practices. Yet GenAI models are often trained on culturally uneven datasets, embe…

cs.HC202434 cited

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…

cs.HC202430 cited

Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint Novices

Ruiwei Xiao, Xinying Hou, John Stamper

Recent studies have integrated large language models (LLMs) into diverse educational contexts, including providing adaptive programming hints, a type of feedback focuses on helping…

cs.CY20244 cited

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…

cs.HC20239 cited

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…