🤖 AI Summary
This study addresses how pedagogical strategies for generative AI integration influence students’ self-efficacy and career interest in higher education. In a fall 2023 undergraduate creative media course, we introduced SPIRAL—a novel, three-stage instructional framework prioritizing “skills-first, AI-integration-second, ethics-pervasive.” Employing a mixed-methods design, we conducted longitudinal surveys (n = full cohort) to track self-efficacy trajectories and in-depth interviews (n = 9) with thematic analysis to examine cognitive and vocational identity shifts. Results indicate significant gains in creative media practice and generative AI tool-use self-efficacy; however, ethical AI use efficacy varied across individuals. Most students demystified AI, and career expectations shifted toward openness or remained neutral. The study contributes the first generative AI pedagogical framework explicitly centered on competency development and ethical internalization, empirically validating its dual supportive impact on psychological self-efficacy and vocational identity formation.
📝 Abstract
Computing education and computing students are rapidly integrating generative AI, but we know relatively little about how different pedagogical strategies for intentionally integrating generative AI affect students' self-efficacy and career interests. This study investigates a SPIRAL integration of generative AI (Skills Practiced Independently, Revisited with AI Later), implemented in an introductory undergraduate creative media and technology course in Fall 2023 (n=31). Students first developed domain skills for half the semester, then revisited earlier material integrating using generative AI, with explicit instruction on how to use it critically and ethically. We contribute a mixed methods quantitative and qualitative analysis of changes in self-efficacy and career interests over time, including longitudinal qualitative interviews (n=9) and thematic analysis. We found positive changes in both students' creative media self-efficacy and generative AI use self-efficacy, and mixed changes for ethical generative AI use self-efficacy. We also found students experienced demystification, transitioning from initial fear about generative AI taking over their fields and jobs, to doubting AI capability to do so and/or that society will push back against AI, through personal use of AI and observing others' use of AI vicariously. For career interests, our SPIRAL integration of generative AI use appeared to have either a neutral or positive influence on students, including widening their perceived career options, depending on their view of how AI would influence the career itself. These findings suggest that careful pedagogical sequencing can mitigate some potential negative impacts of AI, while promoting ethical and critical AI use that supports or has a neutral effect on students' career formation. To our knowledge our SPIRAL integration strategy applied to generative AI integration is novel.