The Digital Education Council describes itself as “bringing together institutions with a shared vision of revolutionising the world of higher education & workforce development through technology and collaboration.”
It counts a number of Australian universities amongst its members, as well as Bendigo Kangan Institute and Holmesglen Institute, and a number of global polytechnics. That means that while its free resources are often developed by experts in the higher education sector, they also have broad applicability in VET.
Their latest resources may prove useful to VDC News readers still trying to come to grips with Generative AI.
The first is an ‘AI Readiness Framework’ designed with input from 27 leading institutions across 17 countries.
It contains 4 key principles of AI readiness:
- Resilience – building organisational capacity to “withstand challenges and adapt to AI advancements.”
- Adaptability – staying flexible by “responding to emerging technologies and industry needs.”
- Transformation – leveraging AI to drive innovation in teaching and assessment, and in the provider’s operations.
- Community – cultivating an “ecosystem of shared responsibility… and (ensuring) inclusive, equitable, and socially responsible AI integration.”
The framework combines 10 dimensions of AI readiness and enables providers to self-assess their current state of AI readiness – emerging, developing, established or mature.
The dimensions of AI readiness are:
- Strategic Alignment
- Institutional Governance
- Stakeholder Engagement
- Operational Readiness
- AI Literacy and Ethical Use
- Accessibility and Inclusion
- Faculty and Administrative Professional Development
- Teaching, Learning and Assessment Strategies
- Curriculum Development and Workforce Alignment
- Research and Innovation Leadership
The Council’s second resource is focussed more specifically on AI in Assessment. Developed by the Digital Education Council and Pearson, their report ‘The Next Era of Assessment: A Global Review of AI in Assessment Design’ is “the first comprehensive mapping of AI-integrated assessment practices” in tertiary education.
It draws on 101 global case studies, and offers providers “a clear and actionable framework to rethink and redesign assessment in the age of AI, featuring:
- 14 practical methodologies of AI-integrated assessment design
- A step-by-step guide to support assessment redesign at scale
- A dual-priority approach that ensures students develop both foundational human skills and AI fluency
- AI-resistant as a baseline design principle to uphold assessment validity and integrity.”
