Three Years with Classroom AI in Introductory Programming: Shifts in Student Awareness, Interaction, and Performance

TL;DR

This longitudinal study examines how students' awareness, interaction, and performance in an introductory Python course evolve over three years with increasing AI integration, highlighting shifts in AI literacy and learning practices.

Contribution

It provides rare longitudinal evidence on student-AI interaction patterns and course outcomes as AI becomes routine in programming education.

Findings

Students' familiarity with GenAI increased over time.

Help-seeking practices evolved with growing AI literacy.

Course outcomes showed positive trends with AI integration.

Abstract

Generative AI (GenAI) tools such as ChatGPT now provide novice programmers with instant, personalized support and are reshaping computing education. While a growing body of work examines AI's immediate impacts, longitudinal evidence remains limited on how students' awareness, student-AI interaction patterns, and course outcomes evolve as AI becomes routine in classrooms. To address this gap, we investigate an introductory Python course across three successive AI-supported cohorts (2023-2025). Using questionnaires, coded student-AI dialogue logs, and course assessment records, we examine cohort-to-cohort shifts in students' AI awareness, interaction practices, and learning outcomes. We find that students' relationships with GenAI change systematically over time: familiarity and uptake become increasingly normative, and help-seeking practices evolve alongside growing AI literacy and shifting expectations of what the assistant should provide. These changes suggest that, in the AI era, the central instructional challenge is less about whether students use AI and more about how courses redefine productive learning practices while maintaining student agency. Our study offers longitudinal evidence and practical implications for designing and integrating AI programming support in course settings.