AI Literacy for Community Colleges: Instructors'Perspectives on Scenario-Based and Interactive Approaches to Teaching AI

2025-11-07

AI Summary

This study addresses the lack of AI literacy education for non-STEM community college students by developing and evaluating a no-code, contextually grounded, interactive AI literacy curriculum. Employing an interactive online platform, no-code tools, and authentic scenario-based simulations, the study collected qualitative feedback from instructor focus groups and conducted thematic analysis. Results indicate strong instructor preference for interactive demonstrations and experiential tasks, validating the efficacy of contextualized, inquiry-based design in enhancing conceptual understanding of AI and critical awareness of its societal implications. Iterative refinement of pedagogical scaffolds and multimodal supports improved the curriculum’s accessibility and adaptability across diverse instructional settings. The study contributes a scalable, low-barrier, interdisciplinary AI literacy instructional framework, offering empirical evidence and actionable implementation pathways for institutionalizing AI general education in higher education. (149 words)

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Artificial General Intelligence
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

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.

Problem

• Investigating community college instructors' evaluations of interactive AI literacy resources
• Addressing limited scalable approaches for teaching AI to non-STEM learners
• Developing accessible curriculum through scenario-based activities in real-world contexts

Innovation

• Scenario-based activities for real-world AI learning
• Interactive online curriculum for non-STEM learners
• No-code AI literacy resources with demonstrations