Last month, Lumen’s Chief Academic Officer David Wiley joined Campus Technology’s Insider podcast to share his thoughts on AI in higher education. David and host Rhea Kelly discussed the relationship between AI and OER, how AI will impact instructional design for educators, and key learnings colleges and universities should keep in mind when developing policies around AI. Keep reading below for David’s key takeaways.
Generative AI as the logical successor to OER
There are several parallels between OER and new generative AI models. Both OER and AI can and should be viewed as tools to increase educational opportunities. David cautions that higher ed should avoid falling into the trap of too heavily promoting the solutions themselves and losing sight of the true outcome of making course materials more accessible. Additionally, content created with generative AI is not eligible for copyright protection, making it OER. Consequently, it can be continually updated and improved (unlike traditional textbooks).
AI’s impact on instructional design
AI will have significant positive impacts on instructional design. Establishing clear learning goals is the first step in building a strong instructional framework, and according to David, AI models can be trained to create learning objectives that are foundational to how instructors should design their lessons. AI can also be used to develop more effective content and assessments based on these learning objectives. Integrating AI throughout the entire course design process can make it more efficient and effective.
How colleges and universities should approach AI policy
It is still too early for higher ed institutions to develop specific policies around AI. David compares our current understanding of AI to our understanding of the internet in the late 1990s. We have not even begun to imagine the transformative potential of generative AI, and instructors and institutions both need more time to discover and experiment with its capabilities. If specific policies are established too early, they will likely inhibit innovation and experimentation now and be difficult to revoke or amend in the future. The untapped potential of AI and the current early stage of development necessitates light policy frameworks that serve more as living documents that can be revisited or updated as the technology and our understanding of it develops.
AI developments on the horizon
Developers are already building faster and cheaper AI models, which will increasingly support the current push for equitable access to AI learning solutions across higher ed. Generally, as technologies develop and become more ubiquitous, costs go down and performance improves. David predicts that the same will happen with AI – eventually, all educational institutions, including smaller community colleges, will be able to afford AI solutions for their students.
Upcoming Webinar
Join David as he shares innovative ways to leverage AI technology with students on Tuesday, April 16, 2024 @ 2:00 p.m. ET.
Register here.