Scaling a Model of Teacher Professional Learning – Harnessing MOOCS to Recreate Deep Learning Conversations - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2017

Scaling a Model of Teacher Professional Learning – Harnessing MOOCS to Recreate Deep Learning Conversations

Deirdre Butler
  • Function : Author
  • PersonId : 1030538
Michael Hallissy
  • Function : Author
Mark Brown

Abstract

This paper describes the most recent phase of an innovative model of teacher professional learning that has evolved over a decade (2006 to 2016). Building on the experiences of implementing this face-to-face model, the paper reports on the most recent phase which attempts to harness the emergence of a 4th wave of online learning. The initiative involves the design and development of a Massive Open Online Course (MOOC) that potentially enables the massive scaling up of access to this already validated model of teacher professional learning designed to shift teachers’ pedagogical orientations through school focussed, job embedded teacher professional learning. The importance of maintaining key elements, threshold concepts and signature pedagogies in the design of MOOCs for teacher professional learning are discussed. The paper also explores some of the challenges and potential opportunities different MOOC delivery models offer for sustaining the types of collaboration, rich dialogue and ongoing reflection observed in earlier phases of the project.
Fichier principal
Vignette du fichier
463502_1_En_17_Chapter.pdf (287.26 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01762875 , version 1 (10-04-2018)

Licence

Attribution

Identifiers

Cite

Deirdre Butler, Margaret Leahy, Michael Hallissy, Mark Brown. Scaling a Model of Teacher Professional Learning – Harnessing MOOCS to Recreate Deep Learning Conversations. 11th IFIP World Conference on Computers in Education (WCCE), Jul 2017, Dublin, Ireland. pp.149-160, ⟨10.1007/978-3-319-74310-3_17⟩. ⟨hal-01762875⟩
70 View
106 Download

Altmetric

Share

Gmail Facebook X LinkedIn More