Lavoisier S.A.S.
14 rue de Provigny
94236 Cachan cedex
FRANCE

Heures d'ouverture 08h30-12h30/13h30-17h30
Tél.: +33 (0)1 47 40 67 00
Fax: +33 (0)1 47 40 67 02


Url canonique : www.lavoisier.fr/livre/autre/the-data-team-procedure-a-systematic-approach-to-school-improvement/schildkamp-kim/descriptif_3965349
Url courte ou permalien : www.lavoisier.fr/livre/notice.asp?ouvrage=3965349

The Data Team™ Procedure: A Systematic Approach to School Improvement, 1st ed. 2018 Springer Texts in Education Series

Langue : Anglais
Couverture de l’ouvrage The Data Team™ Procedure: A Systematic Approach to School Improvement
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.

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.

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

Presents one of the few interventions with regard to data use, proven to be effective

Describes an approach that can be used in a wide range of different contexts and countries

Provides the reader with concrete steps and examples

Includes supplementary material: sn.pub/extras

Date de parution :

Ouvrage de 84 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

63,29 €

Ajouter au panier