Build teacher AI readiness through structured institutional support: professional development, mentoring, technical assistance, and AI literacy in teacher education¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that educational institutions strengthen teacher confidence through structured, ongoing support rather than treating resistance as individual reluctance. It recommends "targeted professional development programs emphasizing self-efficacy, adaptability, andpedagogicalskills," plus continuous access to resources, technical assistance, structured mentoring, and incorporating AI literacy in teacher education programs. Policymakers and school leaders are advised to recognize that resistance to AI often reflects systemic support gaps.

Design Implications¶

Context¶

Requirements¶

• Institutions must provide continuous access to resources, technical assistance, and structured mentoring, and incorporate AI literacy into teacher education programs

Constraints¶

• The recommendation is grounded in a survey of 260 teachers in Pampanga, Philippines, where support for internet reliability and infrastructure was reported as only moderate

Target Learners¶

• elementary, secondary, and college teachers

Target Learning Goals¶

• teacher readiness and confidence for AI integration

Related Strategies¶

• Operationalize the faculty standards through structured professional learning pathways with modules, microcredentials, and peer review
• Support faculty AI literacy through needs assessment, targeted training, teaching resources, and communities of practice
• Structure AI-focused professional development as a supported trajectory of planning, reflection, design autonomy, and embedded critical AI literacy
• Faculty professional development treating AI literacy as core professionalism with critical, ethical, and pedagogical emphasis
• Support faculty UDL uptake through shared resources, discussion forums, responsive accessibility services, and recognition of accessible design work
• Treat refusal diagnostically and provide non-AI pathways where AI use is not essential to the learning outcome
• Integrate structured opportunities for critical engagement with AI into teacher education programs

Examples¶

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Key Sources¶

• Vanessa Baltazar Sibug, Maria Anna David Cruz, Vicky Pineda Vital, Juvy Cruz Grume, Almer Balingit Gamboa, Emerson Quiambao Fernando, Lloyd David Feliciano, Jordan Lansang Salenga, and John Paul Palo Miranda. 2025. AI Adoption Among Teachers: Insights on Concerns, Support, Confidence, and Attitudes. In 2025 the 9th International Conference on Education and Multimedia Technology (ICEMT) (ICEMT 2025), July 29–August 01, 2025, Osaka, Japan. ACM, New York, NY, USA. https://doi.org/10.1145/3761843.3761881