TY - GEN
T1 - Characterizing the Relationship Between Generative AI, Student Behavior, and Learning Outcomes in Upper-Level CS Education
T2 - 57th SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2026
AU - Khan, Anha
AU - Mahinpei, Romina
AU - Hedayati, Maryam
AU - Dean, Victoria Lee
AU - Fong, Ruth
N1 - Publisher Copyright:
© 2026 Copyright held by the owner/author(s).
PY - 2026/2/17
Y1 - 2026/2/17
N2 - As generative artificial intelligence (genAI) tools become embedded in computing education workflows, it is essential to understand how students use such systems to learn beyond introductory programming. This work investigates the relationship between the use of genAI by students and their conceptual understanding of mathematical and algorithmic principles in an undergraduate machine learning course with 134 students. We deploy a course-specific, custom-interfaced large language model (LLM), CubBot, to examine (1) how students interact with genAI in an upper-level CS course via an analysis of anonymized chat logs and (2) how genAI usage relates to students’ conceptual understanding and learning outcomes via a randomized, controlled assessment comparing performance with and without CubBot access. This research contributes to the growing body of work on genAI-supported education by providing one of the first empirical investigations into genAI’s relationship with conceptual learning in an upper-level CS course.
AB - As generative artificial intelligence (genAI) tools become embedded in computing education workflows, it is essential to understand how students use such systems to learn beyond introductory programming. This work investigates the relationship between the use of genAI by students and their conceptual understanding of mathematical and algorithmic principles in an undergraduate machine learning course with 134 students. We deploy a course-specific, custom-interfaced large language model (LLM), CubBot, to examine (1) how students interact with genAI in an upper-level CS course via an analysis of anonymized chat logs and (2) how genAI usage relates to students’ conceptual understanding and learning outcomes via a randomized, controlled assessment comparing performance with and without CubBot access. This research contributes to the growing body of work on genAI-supported education by providing one of the first empirical investigations into genAI’s relationship with conceptual learning in an upper-level CS course.
KW - Artificial Intelligence (AI)
KW - Education
KW - Human Computer Interaction (HCI)
KW - Machine Learning (ML)
UR - https://www.scopus.com/pages/publications/105033876893
UR - https://www.scopus.com/pages/publications/105033876893#tab=citedBy
U2 - 10.1145/3770761.3777156
DO - 10.1145/3770761.3777156
M3 - Conference contribution
AN - SCOPUS:105033876893
T3 - SIGCSE TS 2026 - Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.2
SP - 1673
EP - 1674
BT - SIGCSE TS 2026 - Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.2
PB - Association for Computing Machinery, Inc
Y2 - 18 February 2026 through 21 February 2026
ER -