Foster interdisciplinary collaboration and actively include student perspectives in institutional GenAI responses.¶

Strategy · All strategies
Evidence · 1 claim (1 mixed) · 1 study (1 qualitative), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

Beyond governance and training, the article recommends interdisciplinary collaboration and the active inclusion of student perspectives when institutions respond to GenAI. The authors conclude there is a need for "interdisciplinary collaboration, and the active inclusion of student perspectives," reflecting staff recognition of both opportunities and concerns across disciplines and the need to understand how students engage with GenAI.

Design Implications¶

Context¶

Requirements¶

• Mechanisms for cross-disciplinary dialogue and channels for gathering student voices on GenAI use.

Constraints¶

Target Learners¶

• University academic staff
• Higher education students

Target Learning Goals¶

• Institutional decision-making about generative AI in learning and teaching

Claims¶

• The value of the student-staff collaboration was explored from student, staff, and institutional perspectives, with benefits, limitations, and recommendations presented [~W]

Related Strategies¶

• Institutions should respond to GenAI with clear governance frameworks and structured professional training programs for staff.
• Higher education leaders should develop more inclusive and future-oriented GenAI policies integrating social equity, interdisciplinary experimentation, and sustainability considerations
• Foster communities of practice for AI governance instead of rigid top-down policies
• Build ethical AI integration on four coordinated levels: faculty professional development, ethics curricula, clear institutional guidelines, and interdisciplinary updating
• Define institutional value from the bottom up, incorporating learning outcomes, community engagement, and career readiness beyond earnings thresholds

Examples¶

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Key Sources¶

• Enright, H., Horvath, D., Petrovic, K., & Šarkić, B. (2026). “AI Should Help them Learn, Not Learn for Them”: University Staff Perspectives on the Role of Generative AI in Education. Journal of University Teaching and Learning Practice. https://doi.org/10.53761/d5n2yh02