Overview
What the framework is trying to do
Chan's AI Ecological Education Policy Framework shifts AI literacy from an individual learner issue to an institutional ecosystem issue. It organizes policy work into Pedagogical, Governance, and Operational dimensions.
The framework connects classroom practice with privacy, accountability, transparency, institutional support, training, access, and ongoing evaluation.
Framework structure
Core dimensions or competencies
Pedagogical
Assessment redesign, holistic competencies, workforce preparation, and balanced AI adoption.
Governance
Academic misconduct, ethical dilemmas, privacy, transparency, accountability, security, attribution, and equity of access.
Operational
Monitoring implementation and providing training and support for students, teachers, and staff.
Critical depth
Why this framework is rated Moderate–High
Rated Moderate–High because institutional accountability, privacy, transparency, access, and equitable implementation are substantial concerns. Power, labor, surveillance, environmental impact, and epistemic authority are less developed as organizing concepts.
Central
Privacy, transparency
Present
Bias, equity, verification, human agency
Limited
Power, labor, accessibility, environmental impact, epistemic authority
Not evident
See the Critical Dimensions Index for dimensions not assigned a stronger classification.
Evidence base
What supports the framework?
Empirical mixed-methods study with students, teachers, and staff
Practical use
Especially useful for
Institutional AI policy, governance structures, faculty support, implementation planning, and assessment redesign.
Evaluation
Strengths and limitations
Strengths
- Treats AI policy as a shared institutional responsibility.
- Connects pedagogy, governance, infrastructure, and professional learning.
- Empirically grounded in stakeholder perspectives.
Limitations
- Developed in a particular national and institutional context.
- Structural sociopolitical critique is not its primary purpose.
- The original study relied partly on self-report data.
Portability
How well does it travel?
High. The three-part ecological model transfers well to other higher education settings, although policy language should be localized.
Source
Citation
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, 38. https://doi.org/10.1186/s41239-023-00408-3