From Crisis to Collaboration with Daniel Ingvarson
In schools where leaders understood the changes their teaching teams needed to make, COVID was the crisis some teaching practice 'had to have'.
Though a supported change process Daniel took the needs schools had for remote teaching and examined the tools, based on how well they aligned with some specific processes involved in Griffen's collaborative teaching teams. Using High Impact Teaching practices Daniel successfully evolved how teachers collaborated and co-developed such that on return teachers will maintain their changed practice.
Based on this and work Daniel has done with John Hattie he believes the use of Edtech during this pandemic can act as a support for school change.
This session will be part presentation and part dialog about your own experiences to help learn from each other.
Who Should Attend?
Primary and Secondary school leaders looking to process the lessons from the recent lockdown and support ongoing online collaboration and co-operation amongst staff.
About the presenter
Daniel Ingvarson’s expertise stems from qualifications in philosophy, comp-sci, a thesis in technology policy and masters subjects in education measurement. He specialises in joining his excellent technical skills with the education sectors wider needs. He recently conducted a study alongside John Hattie with the guiding question, “What are the teacher practice impacts of Edtech tools?” The study focussed on how the quality of teacher feedback changes with the use of EdTech Tools.
Daniel has deep technical skills in the education sector as evidenced with his development of SchoolsNet, the award winning Myclasses LMS and RICOne. He founded the K-12 Federation for the Gates Foundation, and was appointed Victorian Edtech ambassador.
Daniel developed a model for skilling leaders to assist teachers in remote learning settings with evidence based, collaborate teaching teams. He also has a great interest and insight into the future of assessment with the rise of smart curricula systems and machine learning.