338 citations · 590 across the 4 of their papers we have counts for
4 papers
CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
Majeed Kazemitabaar, Runlong Ye, Xiaoning Wang +4
Timely, personalized feedback is essential for students learning programming. LLM-powered tools like ChatGPT offer instant support, but reveal direct answers with code, which may h…
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…
Scaffolding Progress: How Structured Editors Shape Novice Errors When Transitioning from Blocks to Text
Majeed Kazemitabaar, Viktar Chyhir, David Weintrop +1
Transitioning from block-based programming to text-based programming environments can be challenging as it requires students to learn new programming language concepts. In this pap…