Date
Publisher
arXiv
This research category full paper investigates how community college instructors evaluate interactive, no-code AI literacy resources designed for non-STEM learners. As artificial intelligence becomes increasingly integrated into everyday technologies, AI literacy - the ability to evaluate AI systems, communicate with them, and understand their broader impacts - has emerged as a critical skill across disciplines. Yet effective, scalable approaches for teaching these concepts in higher education remain limited, particularly for students outside STEM fields.
To address this gap, we developed AI User, an interactive online curriculum that introduces core AI concepts through scenario - based activities set in real - world contexts. This study presents findings from four focus groups with instructors who engaged with AI User materials and participated in structured feedback activities. Thematic analysis revealed that instructors valued exploratory tasks that simulated real - world AI use cases and fostered experimentation, while also identifying challenges related to scaffolding, accessibility, and multi-modal support. A ranking task for instructional support materials showed a strong preference for interactive demonstrations over traditional educational materials like conceptual guides or lecture slides.
These findings offer insights into instructor perspectives on making AI concepts more accessible and relevant for broad learner audiences. They also inform the design of AI literacy tools that align with diverse teaching contexts and support critical engagement with AI in higher education.
Study at a glance
- Question: How do community college instructors evaluate interactive, no-code AI literacy resources designed for non-STEM learners?
- Setting and data: Four online focus groups and surveys with 17 instructors from community colleges across the United States.
- Method: Reflexive thematic analysis of focus group reflections and descriptive ranking analysis.
Why it matters
AI literacy education in higher education remains sparse, particularly outside STEM fields. Scalable, non-technical tools that combine conceptual knowledge with hands-on learning remain rare, and few studies examine how instructors interpret and adapt these resources.
Key findings
- Instructors ranked interactive demonstrations highest among instructional support materials (mean rank 3.20 out of 4), followed by lecture slides, conceptual guides, and reflection prompts.
- Instructors valued realistic visual narratives, animated simulations, and role-playing tasks for making foundational AI concepts concrete and supporting learner engagement without programming.
- Instructors identified key challenges, including balancing conceptual scaffolding without overwhelming or oversimplifying, preventing trial-and-error answering through progressive hints, and adding multimodal accessibility like audio narration.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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