SPIRAL integration of generative AI in an undergraduate creative media course: effects on self-efficacy and career outcome expectations
Troy Schotter, Saba Kawas, James Prather, Juho Leinonen, Jon Ippolito, Greg L Nelson
TL;DR
This study investigates a SPIRAL (Skills Practiced Independently, Revisited with AI Later) approach to integrating GenAI in an undergraduate creative media course (Fall 2023, $n=31$) to assess effects on self-efficacy and career outcome expectations using a mixed-methods design. The course first builds domain skills without AI, then revisits tasks with GenAI and explicit instruction on critical and ethical use, including weekly reflections and industry panels. Quantitative results show significant gains in creative media self-efficacy ($p<0.018$, $d=0.43$) and GenAI-use self-efficacy ($p<0.01$, $d=0.63$), with mixed or non-significant changes for other writing-related self-efficacy measures, while qualitative data reveal demystification of GenAI and variable effects on career outlooks (neutral to positive depending on perceived AI impact). The study suggests that careful, spiral sequencing can mitigate negative AI effects, promote responsible use, and influence career formation in nuanced ways, with the approach being novel for GenAI integration in education.
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.