Paper Detail
Matthew Frazier, Kostadin Damevski, Lori Pollock
Secondary school students enrolled in the AP Computer Science Principles (CSP) course commonly utilize web resources (e.g., tutorials, Q\&A sites) to better understand key concepts in the curriculum. The primary obstacle to using these resources is finding information appropriate for the learning task and student's background. In addition to web search, conversational agents are increasingly a viable alternative for CSP students. In this paper, we study the potential of conversational agents to aid secondary school students as they acquire knowledge on CSP concepts. We explore general purpose, generative conversational agents (e.g., ChatGPT) and custom, fixed-response conversational agents built specifically to aid CSP students. We present results from classroom use by 45 high school students in grades 9-11 (ages 14-17) across six CSP sections. Our main contributions are in better understanding how conversational agents can help CSP students and an evaluation of the effectiveness and engagement of different approaches for CSP exploratory search.
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@article{frazier2026investigating,
title = {Investigating Conversational Agents to Support Secondary School Students Learning CSP},
author = {Matthew Frazier and Kostadin Damevski and Lori Pollock},
year = {2026},
abstract = {Secondary school students enrolled in the AP Computer Science Principles (CSP) course commonly utilize web resources (e.g., tutorials, Q\textbackslash{}\&A sites) to better understand key concepts in the curriculum. The primary obstacle to using these resources is finding information appropriate for the learning task and student's background. In addition to web search, conversational agents are increasingly a viable alternative for CSP students. In this paper, we study the potential of conversational agents to },
url = {https://arxiv.org/abs/2604.16213},
keywords = {cs.HC, cs.SE},
eprint = {2604.16213},
archiveprefix = {arXiv},
}
{}