The final talk in the Lab’s Spring 2021 Learning in a ‘Post-Truth’ World series took place Thursday, April 22 and featured the University of Wisconsin- Madison’s Dr. Noah Weeth Feinstein.
In 2020, Noah Weeth Feinstein and David Waddington argued for shifting the balance of science education away from individual truth-judgments and toward collective sense-making. How does that argument hold up? In this talk, Dr. Weeth Feinstein will review their argument and discuss both the promise and risks of wading deeper into the social world and engaging directly with messy problems in messy practical contexts. Dr. Weeth Feinstein concludes by asking whether concepts like value and appropriate respect offer more fruitful territory for science education than the familiar framing of truth and trust.
On Thursday, March 11, the Lab hosted its second talk in our Learning in a ‘Post-Truth’ World series. Drawing on recent collaborations with Sarit Barzilai and Ravit Golan Duncan, Dr. Clark Chinn (Rutgers University) presents an overview of how educators can effectively respond to the “post-truth” challenges of misinformation, conflicting information, and mistrust in formerly trusted institutions of knowledge (e.g. science, media). Dr. Chinn begins with an analysis of apt epistemic performance as the goal of epistemic education. This analysis identifies five aspects of apt epistemic performance; many post- truth challenges can be viewed as involving breakdowns in these five aspects of apt epistemic performance. Dr. Chinn then outlines a set of design principles to improve education and address these breakdowns. These principles specify new ways to design learning environments that can foster the individual and collective abilities needed to think well in the modern world.
The Lab’s Learning in a ‘Post-Truth’ World speaker series kicked off Monday, February 22, 2021 with Dr. Simon Knight‘s seminar Who to Believe? Conceptualizing and Navigating Disagreement. Dr. Knight is a senior lecturer in the University of Technology Sydney, Transdisciplinary School, Director of the Centre for Research on Learning in a Technological Society, and co-editor-in-chief of the Journal of Learning Analytics. His talk draws on research in epistemic cognition, including his own research on how people search for and talk about evidence, as well as recent work in conceptualizing expert-expert disagreement, to flag key implications for helping people navigate these issues.
On October 27, 2020, the Lab hosted a Learning Informatics Seminar featuring Dr. Marcelo Worsley, Assistant Professor of Computer Science and Learning Sciences at Northwestern University. The seminar’s title was: Multimodal Learning Analytics: Core Commitments for Intentionally Centering Inclusivity in Data Science. Replay the recording below:
On September 24, 2020, the Lab hosted a Learning Informatics Seminar featuring Dr. Simon Buckingham Shum, Professor of Learning Informatics at the University of Technology Sydney, where he serves as inaugural director of the Connected Intelligence Centre. The seminar’s title was: Learning Informatics: A.I. • Analytics • Accountability • Agency. Replay the recording below:
On July 28, 2020, the Lab hosted a Learning Informatics Seminar featuring Dr. Alyssa Wise, Associate Professor of Learning Sciences and Educational Technology at New York University and the Director of NYU-LEARN, NYU’s pioneering university-wide Learning Analytics Research Network. The seminar’s title was: Learning Analytics and the Changing Landscape of Higher Education. Replay the recording below:
Associate Professor Bodong Chen of the Department of Curriculum and Instruction recently co-led an invited learning analytics webinar organized by the Society for Learning Analytics Research (SoLAR). The talk, “Analyzing Learning and Teaching throught the Lens of Networks,” attracted more than 200 remote attendees. Together with Dr. Sasha Poquet from the University of South Australia, Chen shared the latest research in the use of networks in learning analytics as a methodology for understanding learning and the connections involved. Using case studies to demonstrate the usefulness of network analysis, they argue for greater consideration of learning as a networked phenomenon and call for future learning analytics work in this area.
A recording of the webinar has been uploaded to the SoLAR website as a learning resource for the community. It is also available below: