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The research aims to derive instructional design principles for a new general education course focused on AI literacy.

January 14, 2026Open Access

A Study on the Derivation of Design Principles and Development of a Required General Education Course Based on AI Literacy

Key Points

The research aims to derive instructional design principles for a new general education course focused on AI literacy.
Utilized the ADDIE model to analyze current digital literacy education and assess students' GenAI usage.
Developed a curriculum organized into three phases focusing on AI technologies and ethical applications.
Evaluated content validity with six experts, achieving an Item-level Content Validity Index of 1.00.
Derived four key instructional principles: problem-based inquiry, ethical use of GenAI, accessibility and inclusivity, and sustainability.
Organized course activities into a cyclical inquiry process for deeper student engagement with AI.

Abstract

This study aims to develop a new required general education course, “Inquiry and Problem-Solving in the Age of Generative AI,” to strengthen the AI literacy competencies of undergraduate students at University A located in Busan, reflecting the emerging demands of the generative AI era. Following the analysis, design, development phases of the ADDIE model, the study examined the current state of digital literacy education, students’ GenAI usage patterns and learning needs at university A, and relevant theoretical foundations and practices. Based on these analyses, four instructional design principles were derived: problem-based inquiry, critical and ethical GenAI use, accessibility and inclusivity for diverse learners, and sustainability that accommodates rapid technological advances. Grounded in these principles, the course was systematically organized into three sequential phases: ① Understanding GenAI Technologies(1st~4th week), ② Multimodal AI and Ethical Application(5th~7th week), and ③ GenAI-supported Inquiry, Planning, and Creative Expression(9th~14th week). All weekly learning activities were intentionally designed to follow a cyclical inquiry process of “self-thinking → AI-generated output → comparison → reconstruction → reflection,” enabling students to critically engage with AI as a cognitive partner rather than a mere generative tool.Content validity was evaluated by six external experts, and all items demonstrated an Item-level Content Validity Index (I-CVI) of 1.00, confirming the appropriateness of the course design. This study contributes to the field by translating key components of AI literacy identified in prior research into a coherent, practice-oriented curriculum model that integrates learning objectives, content, pedagogy, and assessment. Future research will implement a pilot offering of the course to empirically evaluate learning outcomes and operational feasibility, and to further refine the curriculum.

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