Reimagining teacher-AI co-design in learning task design: trends and perspectives

Synthesis: Teacher-AI co-design in learning task design. A systematic review by Zongran Wang, Liu Mingzhuo & A.Y.M. Atiquil Islam (2026) synthesizing 28 empirical studies (2015–2025) on how teachers collaborate with AI — including generative AI — to design learning tasks. GenAI is predominantly used to support lesson planning, prompt generation, and creative ideation, while traditional AI is used for learning analytics and Feedback design. The dominant collaboration mode is AI as assistant/content generator, with AI as a fuller co-designer or dialogic partner much rarer. Four pedagogical affordances recur — efficiency, responsiveness, Creativity, and equity — and the review argues these form a functional-affordance framework for guiding teacher design work with AI.

Overview

Teachers increasingly act as instructional designers working with AI rather than merely using it for delivery. This review maps the theoretical frameworks, AI features, teacher–AI collaboration modes, and design objectives across empirical studies of teacher–AI co-design of learning tasks, in both K-12 and higher education.

Method

• Search: EBSCOhost and Web of Science, 2015–2025; Boolean term combinations ("Teacher Design Practices" AND "AI", "Learning Task Design" AND "AI", "Teacher-AI" AND "design", "Teacher AI co-design") plus snowballing.
• Screening: 672 records → 28 empirical studies after eligibility checks (population = K-12 and higher-ed teachers co-designing tasks; interventions = task creation/application).
• Appraisal: Mixed Methods Appraisal Tool (MMAT); 19 studies rated high quality (5/5), with common limitations reported across designs.

Key findings

• GenAI vs. traditional AI roles differ. GenAI tools are predominantly used for lesson planning, prompt generation, and creative ideation; traditional AI tools are more commonly used for learning analytics and feedback design.
• AI is mostly an assistant, rarely a co-designer. Teacher–AI collaboration manifests in multiple forms, but AI most often serves as an assistant or content generator, and less frequently as a co-designer or dialogic partner.
• Four pedagogical affordances. AI features map onto efficiency (workload reduction), responsiveness (just-in-time instructional adaptation), creativity (idea generation and design space expansion), and equity (differentiated, culturally responsive pathways). Creativity and equity are associated with a broader range of GenAI features; efficiency and responsiveness rely on a narrower set of traditional functions.
• Uneven contexts. Teacher education (36.7%) and higher education dominate the literature; K-12 is underrepresented, attributed to curricular rigidity and limited teacher autonomy.
• Fragmented theory. Theoretical grounding is uneven; many studies use traditional linear instructional-design models that may not fit the distributed, iterative nature of AI co-design.

Practical implications

• A functional-affordance framework. Teachers can use the four affordances (efficiency, responsiveness, creativity, equity) as a lens for evaluating which AI tool to use for which design problem.
• Reframe AI as a co-agent, not just a tool. The review argues AI reorganizes the temporal, cognitive, and relational structures of teaching — a shift from treating AI as a task-output device to a co-designer.
• Research gap: more real-world K-12 classroom studies of teacher–AI co-design are needed, with context-sensitive theoretical models that make teacher agency and AI's pedagogical role visible.

Connected Concepts

• Teacher AI Competency — the knowledge/skills teachers need to co-design with AI
• Learning Design — learning-task design as the collaborative object
• Human AI Collaboration — collaboration modes from assistant to co-designer
• Teaching — the teacher as instructional designer with AI

Connected Articles

• Analyzing teacher-AI interaction patterns across teacher experience and AI proficiency in student-centered lesson design — empirical teacher–AI interaction patterns in lesson design
• Pre-service teachers' agency during their interactions with generative AI while designing for learning - a process view — pre-service teacher agency during GenAI design interactions
• ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning — AI-assisted lesson planning in K-12
• The Intersection of Artificial Intelligence and Instructional Design Practice: A Systematic Review — AI and instructional design practice systematic review

Citation

Wang, Z., Liu, M., & Islam, A. Y. M. A. (2026). Reimagining teacher-AI co-design in learning task design: trends and perspectives. Humanities and Social Sciences Communications, 13, 757.