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

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.

Figures (5)

• Figure 1: Shifts in students’ GenAI Perspectives and Awareness. (a) Familiarity with GenAI, (b) GenAI usage, and (c) perceived benefit for learning. (d) Perceived ways GenAI can support programming learning.
• Figure 2: Word clouds of students’ GenAI awareness (larger words indicate higher frequency in students’ responses).
• Figure 3: Weekly trends in average conversation depth.
• Figure 4: Distribution of student prompt types across years (100% stacked).
• Figure 5: Prompt-type transition networks across years.