7 citations · 13 across the 12 of their papers we have counts for
5 papers · 1 filter
The Right Kind of Help: Evaluating the Effectiveness of Feedback Methods in Elementary-Level Visual Programming
Ahana Ghosh, Liina Malva, Alkis Gotovos +2
We present a large-scale study comparing the effectiveness of various feedback methods in elementary-level programming. While prior work has explored different feedback methods, th…
Inference-Time Personalized Alignment with a Few User Preference Queries
Victor-Alexandru Pădurean, Parameswaran Kamalaruban, Nachiket Kotalwar +2
We study the problem of aligning a generative model's response with a user's preferences. Recent works have proposed several different formulations for personalized alignment; howe…
Interleaving Natural Language Prompting with Code Editing for Solving Programming Tasks with Generative AI Models
Victor-Alexandru Pădurean, Alkis Gotovos, Ahana Ghosh +5
Modern computing students often rely on both natural-language prompting and manual code editing to solve programming tasks. Yet we still lack a clear understanding of how these two…
Synthesizing High-Quality Programming Tasks with LLM-based Expert and Student Agents
Manh Hung Nguyen, Victor-Alexandru Pădurean, Alkis Gotovos +2
Generative AI is transforming computing education by enabling the automatic generation of personalized content and feedback. We investigate its capabilities in providing high-quali…
Prompt Programming: A Platform for Dialogue-based Computational Problem Solving with Generative AI Models
Victor-Alexandru Pădurean, Paul Denny, Alkis Gotovos +1
Computing students increasingly rely on generative AI tools for programming assistance, often without formal instruction or guidance. This highlights a need to teach students how t…