Design AI-related teacher professional development as practice-oriented, case-based and connected to teachers' real pedagogical decisions¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Drawing on recent AI-focused literature, the review recommends orienting AI professional development toward teachers' actual practice. It reports that studies by Ding et al. (2024) and Tan et al. (2025) "suggest that AI-related professional development needs to be practice-oriented, case-based and connected to teachers' real pedagogical decisions". This aligns with the AI subset's finding that superficial integration and insufficient AI-related preparation are the dominant barriers.

Design Implications¶

Context¶

Requirements¶

• Connection to teachers' real pedagogical decisions and case-based practice rather than tool-focused training

Constraints¶

• The review attributes this recommendation to the cited AI-focused literature and its own synthesis; the recommendation exceeds what any single reviewed study demonstrated

Target Learners¶

• in-service teachers
• pre-service teachers
• teacher educators

Target Learning Goals¶

• AI literacy and competence
• responsible and pedagogically justified AI integration

Affordances¶

• Ai Responsive Pedagogy Construct

Related Strategies¶

• Use sustained professional development and accompaniment—mentoring, coaching, communities of practice and iterative support—for digital integration
• Implement a coordinated set of safeguards: data-protection policies, fairness-oriented algorithms, assessment redesign, teacher professional development, subsidised tools, and infrastructure investment
• Provide differentiated scaffolding matched to teachers' behavioral-cognitive profiles when supporting multi-agent AI workflow design
• Strategies for integrating GenAI in STEAM teaching: outcome-anchored lesson planning, differentiation, inquiry and project variants, assessment redesign, and integrity as pedagogy
• Structure AI-focused professional development as a supported trajectory of planning, reflection, design autonomy, and embedded critical AI literacy
• Prioritize sustained, pedagogically grounded faculty TPACK development over one-off technology workshops and infrastructure investment
• Expand supervised practicum experiences in teacher preparation to include AI-focused pedagogies
• Support novice online teachers by introducing them to a larger pedagogical framework within which design decisions can be located
• Integrate structured opportunities for critical engagement with AI into teacher education programs

Examples¶

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Key Sources¶

• Patiño Hernández JF, Chiappe A and Ortega González E (2026). From digital competence to AI-responsive pedagogy: a scoping review of technology-supported teacher education. Front. Educ. 11:1949296. https://doi.org/10.3389/feduc.2026.1949296