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

TL;DR

This study explores community college instructors' perspectives on interactive, scenario-based AI literacy resources, highlighting their preferences, challenges, and insights for designing effective AI education tools for non-STEM students.

Contribution

It introduces AI User, an interactive curriculum for AI literacy, and provides empirical insights into instructor preferences and challenges in teaching AI concepts to diverse learners.

Findings

Instructors favor exploratory, real-world AI activities.

Interactive demonstrations are preferred over traditional materials.

Challenges include scaffolding, accessibility, and multi-modal support.

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.