COVID-19 has meant we need to increase the physical distance between on-campus students, while other students may not be able to attend face-to-face classes. One way to address both of these conundrums is to offer classes in Blended Synchronous Learning mode, where students can choose to attend a lesson either face-to-face or online. However, using Zoom or other technologies to simultaneously teach remote and face-to-face students involves several challenges, for instance heightened cognitive load for teachers.
This joint Learning Technology Research Cluster and Learning Innovation Hub presentation shares outcomes of a multi-institutional research project that investigated factors that support and constrain learning and teaching in blended synchronous learning environments. Several case studies are presented across a range of disciplines and contexts, as exemplar design patterns for offering blended synchronous learning classes. Based on the outcomes of the study, an integrated framework for teaching in blended synchronous learning environments is presented (see http://blendsync.org).
Title: COVID-19: Using Blended Synchronous Learning approaches to simultaneously teach remote and face-to-face students
Listen to the Zoom recording of the presentation from the Blended Synchronous Learning Forum (held 20 August, 2020)
Presenters: Matt Bower and Mathew Hillier
Who: Anyone interested in considering or discussing blended synchronous learning and teaching approaches.
**UPDATE: The slide deck from this presentation is now available**
Have you been using a blended synchronous approach for teaching in small group classes (e.g. including remote participants in an on-campus tutorial using Zoom or other video conferencing tools)? If so, we’d love to hear about your experiences so far to see how we can better support you by completing this survey.
Hi Matt, Iook forward to reviewing the recording of this session when it is available!
Hi Andrew – you can find the session recording here: https://macquarie.zoom.us/rec/play/tcYrd-mq-zs3TIDGsASDAKAoW9XpLP6s03QW-vMNmRm0ByVSZgGvY-FHNOcP2upX0tkH2WpfVpWTtPWj