Abstract:
The technology market is moving more quickly than online program design teams can handle. Teams that excessively chase promises of new forms of engagement spend their design capacity on adoption and rebuilding rather than on sustaining high-quality teaching and learning experiences. Based on several years of online program development at Brown University, and amid rapid adoption of generative AI, this session makes the case for locating innovation in the more durable enterprise technology that institutions already own.
Reporting:
- Why we started looking more deeply into tools we already license, and what that shift freed up for the team.
- How out-of-the-box vendor functionality can be leveraged to engage students in meaningful ways, with examples from our own courses.
- How a simplified design foundation separates what should stay stable from what should be expected to change, and the keep, revise or replace method we use to decide.
- What our R&D with university-approved AI tools is surfacing, including a distinction that has shaped our thinking around using AI to build learning experiences versus ones that require AI to run, and the relative costs.
- How we are planning for stability in a volatile market, and the case for foundations over novelty.