Prioritize sustained, pedagogically grounded faculty TPACK development over one-off technology workshops and infrastructure investment¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on the identified importance-performance gap in faculty competence, the article recommends that institutions invest in sustained, pedagogically grounded TPACK development programs for instructors rather than one-off technology workshops, and that human capital development precede or parallel hardware investment in institutional AI strategies. It also recommends systematic mechanisms for updating AI content (e.g., industry-academic curriculum labs) and intelligent instructional support systems integrating adaptive learning and real-time feedback. The article explicitly cautions these are "strategic guidelines for program optimization, not as evidence-based interventions proven to enhance learning outcomes".

Design Implications¶

Context¶

Requirements¶

• Institutional commitment to sustained faculty development rather than one-off workshops

Constraints¶

• Recommendations are derived from expert-perceived priority rankings, not proven to enhance learning outcomes

Target Learners¶

• faculty and instructors in AI certificate programs
• higher education institutions

Target Learning Goals¶

• faculty integrated TPACK capacity, curriculum-technology alignment

Affordances¶

• Tpack Extended Ai Certificate Evaluation Framework

Related Strategies¶

• Invest in sustained, role-specific, discipline-specific professional learning and structured student AI literacy pathways across PK16
• Design AI-related teacher professional development as practice-oriented, case-based and connected to teachers' real pedagogical decisions
• Support faculty AI literacy through needs assessment, targeted training, teaching resources, and communities of practice
• Pair technology access with targeted investments in infrastructure, staffing, and support, and pilot initiatives with dedicated budgets
• Implement AI-supported STEM instruction through sustained, system-level integration of one to two months or more rather than isolated short interventions
• Sustain doctoral methodological competence through continued practice, feedback, and authentic application rather than isolated short courses

Examples¶

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Key Sources¶

• Zijing Wu and Qiang Li. (2026). Evaluation indicator system for AI certificate programs. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00604-x