SLL Episode on Big Data
Synthesis of points:
- Learning Management Systems collect thousands of data points on student touchpoints. How is this data used?
- Learning analytics is a burgeoning field that can predict students that are in “at risk” states based on additional data that might be available through secondary data sources (e.g. address location, english as a second language, ethnicity and more).
- Whether data collected on students, including grades is shared with third parties, and whether informed consent has been adequately gathered.
- The role of persuasive design in AI-based learning systems to encourage students to reach their potential and overcome weaknesses based on personalized learning opportunities.
- Amassing big data analytics for both aggregate knowledge that might aid large groups of learners, or microtargeted opportunities for individuals
- Controversial topic areas include: AI replacing teachers, mentoring by AI as opposed to humans, surveillance for care vs surveillance for control, commercializing education
Article of interest by the panelist:
Just How Much of Higher Education Can Be Automated? https://slate.com/technology/2021/03/trolley-solution-response-essay-automated-higher-education.html
https://www.youtube.com/watch?v=TZpJX_avpeE&feature=emb_logo (panel: Shiv Ramdas, Katina Michael, moderator Punya Mishra)
Biography: Katina Michael BIT, MTransCrimPrev, PhD is a professor at Arizona State University, a Senior Global Futures Scientist in the Global Futures Laboratory and has a joint appointment in the School for the Future of Innovation in Society and School of Computing and Augmented Intelligence. She is the director of the Society Policy Engineering Collective (SPEC) and the Founding Editor-in-Chief of the IEEE Transactions on Technology and Society. In 2007, Katina was awarded a teaching scholarship at the University of Wollongong toward faculty-based staff development initiatives to disseminate good teaching practice through sharing of expertise within faculties. She championed the concept of total curriculum management. Katina has continued to innovate within her teaching practice implementing distributive leadership strategies across interdisciplinary field including: technology/engineering, social sciences, humanities and law. Katina brings a unique understanding of the application of AI within higher education, and has much to contribute to the learning analytics space especially the secondary use of data.
Citation: Chris Dede (moderator), with Andrew Dean Ho, Avriel Epps-Darling, Katina Michael, 18 June 2022, “Big Data”, Silver Lining for Learning, https://silverliningforlearning.org/