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Content available
Article
Publication date: 13 February 2007

Andy Adcroft

483

Abstract

Details

Management Decision, vol. 45 no. 1
Type: Research Article
ISSN: 0025-1747

Content available
Article
Publication date: 10 April 2017

Slawomir Jan Magala

418

Abstract

Details

Journal of Organizational Change Management, vol. 30 no. 2
Type: Research Article
ISSN: 0953-4814

Content available
Book part
Publication date: 19 February 2005

Willie Pearson and Jr.

Abstract

Details

Beyond Small Numbers
Type: Book
ISBN: 978-0-76230-562-9

Open Access
Article
Publication date: 9 March 2020

Rebecca Wolf, Joseph M. Reilly and Steven M. Ross

This article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the…

2179

Abstract

Purpose

This article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.

Design/methodology/approach

A literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.

Findings

Findings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.

Practical implications

Given the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.

Originality/value

This article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.

Details

Journal of Research in Innovative Teaching & Learning, vol. 14 no. 2
Type: Research Article
ISSN: 2397-7604

Keywords

Abstract

Details

Attaining the 2030 Sustainable Development Goal of Gender Equality
Type: Book
ISBN: 978-1-80455-835-5

Content available
Article
Publication date: 1 November 2006

Steven Walczak

362

Abstract

Details

The Learning Organization, vol. 13 no. 6
Type: Research Article
ISSN: 0969-6474

Content available
Article
Publication date: 1 October 2002

84

Abstract

Details

Anti-Corrosion Methods and Materials, vol. 49 no. 5
Type: Research Article
ISSN: 0003-5599

Content available
Book part
Publication date: 20 August 1996

Abstract

Details

The Peace Dividend
Type: Book
ISBN: 978-0-44482-482-0

Content available
Book part
Publication date: 8 September 2022

Stephen Turner

Abstract

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Mad Hazard
Type: Book
ISBN: 978-1-80382-670-7

Content available
Book part
Publication date: 24 September 2010

Abstract

Details

Special Issue Law Firms, Legal Culture, and Legal Practice
Type: Book
ISBN: 978-0-85724-357-7

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