The seminar is co- sponsored by CITE and Sciences of Learning SRT, The University of Hong Kong
This talk will provide an overview of recent research projects I have been involved with in which virtual reality and modeling and visualization technologies have been used as part of research into how students can learn challenging conceptual knowledge and skills. An emerging theme in this research concerns the issue of pedagogical sequences of structure in learning activities. It is argued that most “traditional” instruction and socio-cognitive approaches such as cognitive apprenticeship and guided inquiry start with high structure experiences before introducing students to low structure or open-ended activities. An alternative pedagogical trajectory for learning activities is low-to-high structure. According to advocates of this general sequencing approach, under certain conditions in which learners persist, struggle, and even fail at tasks that have low structure and that are beyond their current abilities may result in short term failure but longer term success in learning. Research exploring this issue involving students learning the physics of electricity with NetLogo agent-based models is reported. Significantly higher learning gains were found for the low-to-high structure treatment group compared to the more “typical” high-to-low structure group. Implications for the pedagogical design of learning activities involving modeling and visualization systems and agent-augmented virtual worlds for education are discussed.
About the speaker(s):Michael J. Jacobson, Ph.D., is a Professor and Chair of Education in the Faculty of Education and Social Work at The University of Sydney. He is also the Co-director of the Centre for Research on Computer-supported Learning and Cognition (CoCo), the Associate Dean for Information and Knowledge Technologies in the Faculty, and Deputy Director of the new Sydney Institute for Innovation in Science and Mathematics Education. Michael’s research has focused on the design of learning technologies to foster deep conceptual understanding, conceptual change, and knowledge transfer in challenging conceptual domains. Most recently, his work has explored learning in agent-augmented multi-user virtual environments and with agent-based modeling and visualization tools, as well as cognitive and learning issues related to understanding new scientific perspectives emerging from the study of complex systems. Dr. Jacobson has published extensively in areas related to the learning sciences and technology.