🏷️ Concept
Curriculum Design
Curriculum Design — the process of planning and structuring what is taught across courses, programs, and institutions, including learning objectives, content sequencing, assessment strategies, and skill progression. In the AI era, curriculum design must balance foundational knowledge with emerging AI competencies, determining not just what students learn but how they learn to work with and critically evaluate AI tools.
Curriculum design addresses the what of education at the program level, complementing Instructional Design which addresses the how at the course level. The articles in this wiki explore how AI is reshaping curricula across disciplines — from software engineering to architecture to green education — and how educators are designing curricula that embed AI literacy without sacrificing disciplinary fundamentals.
Key research themes
Redesigning curricula for the AI era is the central challenge. Lee et al. synthesized findings from international workshops on reshaping undergraduate CS education, arguing that as GenAI automates implementation-level programming, curricula must shift toward system design, abstraction, and critical evaluation — while de-emphasizing low-level implementation details. Gorsky formalized Agentic Software Engineering as a distinct discipline with a 21-module curriculum focused on the "evolution of intent" and practitioner discipline required to manage AI agents. Both connect to AI Literacy and Scaffolding.
Curriculum mapping and analysis uses AI to understand existing curricula. Geng et al. analyzed 23 syllabi from AI-assisted software engineering courses, identifying common themes — prompt engineering, code review with AI, ethical considerations — and deriving design guidance that emphasizes balancing tool fluency with foundational knowledge. CourseGraph applies computational methods to compare CS course structures across institutions.
AI literacy integration embeds AI competencies across disciplines. SAIL provides a scaffolded AI literacy framework applicable across all ages and educational stages, addressing second- and third-level digital divides. Tracing GenAI Literacy Interaction Patterns examines how AI literacy develops through interaction patterns. Hingle Collaborative AI Literacy 2025 explores collaborative approaches to AI literacy curriculum development, connecting to Collaborative Learning.
Domain-specific curriculum innovation applies curriculum design to specific fields. GenAI Architecture Education explores how generative AI reshapes architectural design pedagogy. Talebzadeh AI Green Education 2026 examines AI integration in green education curricula. Connected AI Lesson Planning Vietnam and LLM Cultural Relevance K12 address culturally responsive curriculum design.
Institutional frameworks address curriculum change at scale. Finkelstein Principled AI Education 2025 and Principled AI Education provide principles for integrating AI across educational programs. AI Adoption Training Public Sector examines barriers to AI curriculum adoption in public sector education.
Connections to related concepts
Curriculum design connects directly to Instructional Design — curriculum defines what, instruction defines how. It connects to AI Literacy because embedding AI competencies is a primary curriculum challenge, to Teacher Role and Faculty Development because curriculum change requires educator preparation, and to Scaffolding because well-designed curricula scaffold skill development across courses and years. The Higher Ed and K 12 connections reflect curriculum design's relevance across educational levels.