365
Views
0
CrossRef citations to date
0
Altmetric
Articles

Professional Learning Communities in Physical Education: Preparing Teachers to Thrive

Pages 38-44 | Published online: 11 Jan 2023
 

Abstract

This article explores how physical education teacher education (PETE) programs can prepare physical education professionals for PLC engagement. A requisite competency domain for PLC engagement can be described as “co-assessment literacy” or “closing the loop” of a results cycle (utilizing assessment data to monitor student learning and improve teaching practice). Using a little-known process assessment called a Programmed Practice Sheet (PPS) can be an efficient way for a physical education PLC team to close the loop. The article concludes by describing how a PETE program utilized PLC structures, principles, and language in guiding undergraduate students in the process of research inquiry. Research inquiry concepts and the PLC results process for closing the loop are explored and compared.

Additional information

Notes on contributors

Zack Beddoes

Zack Beddoes ([email protected]) is an assistant professor in Department of Teacher Education at Brigham Young University in Provo, UT.

Keven Prusak

Keven Prusak is an associate professor in Department of Teacher Education at Brigham Young University in Provo, UT.

David Barney

David Barney is a an associate professor in the Department of Teacher Education at Brigham Young University in Provo, UT.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 72.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.