At the nexus of learning and innovation
Sep
05
September 5, 5:00 pm
Where

Location: New Law School Annex Seminar Room 444, The University of Sydney

Cost: Free

RSVP: Not required

What will learning be like tomorrow? What are the frontiers of learning innovation that will drive this? How do developments in different disciplinary domains contribute to those frontiers? What kinds of research and development agendas should be pursued by researchers and innovators who work on those frontiers?

This seminar is a part of the Sydney Research Seminar series “Reimagining the future of learning innovation” and will focus on how developments in the learning sciences that shape the frontiers of learning in higher education and beyond. It will be co-presented by two distinguished learning scientists: Professor Peter Reimann and Professor Michael Jacobson. The presentations will be followed by Q&A discussion with students and general audience.  Everyone is welcome to attend!

Where

Location: New Law School Annex Seminar Room 444, The University of Sydney

Cost: Free

RSVP: Not required

AI in Education: What can we realistically expect, Professor Peter Reimann

Abstract: AI (Artificial Intelligence) is the currently most important technology trend touted to change our life, including our professional life. No doubt that in education we will see a “2nd wave” of the use of AI in the very near future. Since I have participated in the 1st wave of AI in Education—which we could describe as “knowledge intensive”—I will share some of the experiences made with that approach. I then want to speculate a bit about what the 2nd wave might look like—which we might call “data-intensive”—and will try to separate real potential from hype.

Professor Peter Reimann is Professor in the Sydney School of Education and Social Work, where he co-directs the Centre for Research on Learning and Innovation (CRLI). Peter received his PhD from the University of Freiburg in Cognitive Psychology and worked as Professor for Educational Psychology at the University of Heidelberg before he moved to Sydney. His primary research area is educational computing in general and computer-supported collaborative learning in particular.

 

Open, flexible, and distance education and the use of learning analytics: A complexity and learning sciences theoretical critique, Professor Michael J Jacobson

Abstract: In this talk, I consider a range of issues for researchers and users of open, flexible, and distance learning (OFDL) systems. In particular, “human learning” is regarded as an emergent phenomenon occurring in educational complex systems, which may be non-digital or digital in nature. It is suggested that the term “learning” in OFDL, such as learning analytics and machine learning, refers to computational techniques that help identify patterns in large datasets generated in OFDL systems. It is also proposed that OFDL systems are in fact examples of complex systems, and an overview is provided of a set of complexity conceptual principles in the complex systems conceptual framework of learning (CSCFL). A discussion is provided about the types of data being collected for assessments of learning in OFDL systems, and about the limitations of currently available machine scoreable online items that may only validly assess low level declarative knowledge but not higher-level explanatory and procedural understandings resulting from OFDL learning experiences. Finally, a research example is provided to illustrate how CSCFL may be used with LA techniques to study an OFDL research topic. Implications of complexity theorizing for OFDL research are also discussed.

Michael Jacobson is a Professor and Chair of Education in the Sydney School of Education and Social Work and Co-Convener of the Advanced Learning Technologies SIG at the Centre for Research on Learning and Innovation at The University of Sydney. His research explores learning with intelligent virtual worlds and agent-based modeling and visualization tools, as well as theoretical and methodological implications of the field of complexity and new scientific perspectives emerging from the study of complex systems. Michael has published extensively in areas related to the learning sciences and technology, given invited talks at international conferences, and served as an educational and business consultant in Australia and internationally. He received his Ph.D. from the University of Illinois at Urbana-Champaign in 1991.