Updated Session Description
*** Session slides ***
Instructions: The pre-recorded consists of a slide deck and list of suggested readings, along with a twitter thread with discussion questions posted from the presenter’s account @txtbks during the scheduled session (with live responses).
Original Session Description
Data analytics is spreading fast in higher education, from early warning systems that identify students in need to adaptive learning that can improve outcomes. Vendors and proponents have widely advertised the benefits and possibilities of these new systems. However, there has been too little discussion of the possible downsides and how to mitigate the manifold risks.
Ethical and strategic questions about data analytics abound. Can artificial intelligence be deployed without further marginalizing underserved populations? Can institutions remain open and accountable to their missions while key decisions are made by black box algorithms? Can institutions benefit from the use of data analytics without ceding control over their data infrastructure to vendors?
Particularly in North America, these questions grow increasingly urgent as the education publishing industry evolves away from printed books toward models more like Netflix or Facebook. The growing adoption of subscription-based digital textbooks creates a pipeline for valuable data to flow into increasingly advanced analytics products, potentially giving publishers better insights into campus life than the institution itself. While data privacy laws afford some protection to individuals, many institutions have only begun to grapple with the broader strategic implications of data infrastructure and how it could limit efforts to be more open in the future.
This session will discuss the implications of data analytics for open education practice, drawing most analysis from a North American context, but considering how the findings can be more broadly applicable. It will also explore how open educational resources fit into a solutions framework for regaining and maintaining community control over education infrastructure recently published by SPARC. The framework offers concrete recommendations across three categories: immediate actions that can mitigate risk (including data inventories and contract negotiations), thinking strategically about trade-offs (such as how to balance human and AI decision making), and collective actions (including building or acquiring infrastructure and stronger public policy).
Resources supporting this session include the Landscape Analysis and Roadmap for Action published by SPARC available here: https://sparcopen.org/our-work/community-owned-infrastructure/
louisedrumm joined the session Data Analytics and Privacy, Equity, and Openness [O-129] 8 months ago
Navneet Kaur joined the session Data Analytics and Privacy, Equity, and Openness [O-129] 8 months ago
joined the session Data Analytics and Privacy, Equity, and Openness [O-129] 8 months ago
vmarinj joined the session Data Analytics and Privacy, Equity, and Openness [O-129] 8 months ago