Schildkamp / Handelzalts / Poortman The Data Team™ Procedure: A Systematic Approach to School Improvement

1. Auflage 2018
ISBN: 978-3-319-58853-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 84 Seiten

Reihe: Education (R0)

This book describes the Data Team Procedure: a method for data-based decision making that can help schools to improve their quality. It involves the use of teams consisting of 4-6 teachers, 1-2 school leaders and a data expert. The members of the team collaboratively learn how to use data to solve an educational problem within the school, adopting a systematic approach. The data team procedure is an iterative and cyclic procedure consisting of eight steps. The data team members are trained in the data team procedure by a coach. The coach visits the data team’s school regularly for a meeting and facilitates working according to the systematic procedure. Teams participate in data analysis workshops for more specific support.

Divided into three parts, the book first describes the importance of data use and the data team procedure. Next, it describes two cases. The first case concerns a data team working on a school level problem: Reducing grade repetition. The second case concerns a data team working on a classroom level problem: low student achievement in English language. The last part of the book explains what it means to implement the data team procedure in the school, the conditions needed for implementing the data team procedure, and the factors that may hinder or support the use of data in data teams.

Zielgruppe

Research

Autoren/Hrsg.

Schildkamp, Kim

Handelzalts, Adam

Poortman, Cindy L.

Leusink, Hanadie

Meerdink, Marije

Smit, Maaike

Ebbeler, Johanna

Hubers, Mireille D.

Inhaltsverzeichnis

Preface: Data teams can make a difference; Lorna Earl & Helen Timperley.- Introduction: Data use with the data team™ procedure.- Part 1: The eight steps of the data team™ procedure.- 1. Step 1: Defining the problem.- 2. Step 2: Drawing up hypotheses.- 3. Step 3: Collecting data.- 4. Step 4: Verifying the quality of collected data.- 5. Step 5: Data analysis.- 6. Step 6: Interpretation and conclusion.- 7. Step 7: Taking measures.- 8. Step 8: Evaluation.- Part 2: Two examples of the data team™ procedure: Graduation rates and English language results.- 9. Case study: High school graduation rates.- 10. Case study: English language results.- Part 3: Integration into the organization.- 11. Introducing the data team™ procedure in schools.- 12. The road to sustainability.- Acknowledgements.- References.

Über Autor(innen)

Dr. Kim Schildkamp is an associate professor at the Faculty of Behavioural, Management, and Social Sciences of the University of Twente. Kim’s (international) research focuses on data-based decision making and formative assessment. She has been invited as a guest lecturer and keynote speaker at several conferences and universities, including AERA (American Educational Research Association). She is the president-elect of ICSEI (International Congress on School Effectiveness and Improvement), chair of the ICSEI data use network, and a member of the leadership team of the AERA Data-Driven Decision Making SIG. She has published widely on the use of (assessment) data and is the main developer of the EAPRIL (European Association for Practitioner Research on Improving Learning) award winning datateam® procedure. She is also the editor of several special issues on data use, and the book “Data-based decision making in education: Challenges and opportunities”, published by Springer.

Dr. Adam Handelzalts is the managing director of the teacher education department at the Vrije Universiteit Amsterdam. His research and practice concentrates on initial teacher education and the continuing professional development of teachers throughout their career.

Dr. Cindy Poortman isan assistant professor at the University of Twente, department of Teacher Development. Her research focuses on teacher professional development in Professional Learning Networks. She is the project leader of a national project ‘Pilots for the development of professional learning communities’, and the co-project leader of the Datateam Projects. She has published in books and scientific journals about teacher professional development in learning networks and specifically data teams, and was the main editor for a special issue about effects of professional development in data use for Teaching and Teacher Education (2016).

Hanadie Leusink, MSc. has a background in public administration and is working as a data team coach and coordinator for the Data team project. As a facilitator, she guides the data teams through the eight step data team® procedure: from the first steps (formulating a problem definition and hypothesis) to the final steps (analyzing data and implementing new measures to improve education).

Marije Meerdink, MSc. has a background in development and socialization in childhood and adolescence. She was working as a data team coach in the data team project and is now working as a quality care manager for a Dutch school board.

Maaike Smit, MSc. is an experienced advisor, facilitator and researcher of teacher learning communities and was working as a data team coach in the data team project.

Dr. Johanna Ebbeler is a primary school teacher and educational scientist. She was a team member of the data team project. During her PhD research, she focused on the effects of data-based decisionmaking and on the role of school leaders in data teams.

Dr. Mireille D. Hubers isan assistant professor at the University of Twente, department of Educational Science. Her doctoral dissertation explored the ways in which educators built capacity within their school in order to sustain their data use. Mireille’s research focuses on the ways in which organizations can sustain their improvement strategies through individual and organizational learning. She publishes and presents her work regularly, for example in the 2017 article “Share and succeed: the development of knowledge sharing and brokerage in data teams’ network structures”. In addition, she conducts practical workshops to support organizations (such as schools) in facing their sustainability challenge.