View in EDS

Data-Driven Decision-Making in Creating Class Rosters

Saved in:
Bibliographic Details
Title: Data-Driven Decision-Making in Creating Class Rosters
Language: English
Authors: Rebecca Wolf, Joseph M. Reilly, Steven M. Ross
Source: Journal of Research in Innovative Teaching & Learning. 2021 14(2):162-177.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 16
Publication Date: 2021
Intended Audience: Practitioners
Document Type: Journal Articles
Information Analyses
Descriptors: Data Use, Decision Making, Teacher Attitudes, Journal Articles, Teacher Effectiveness, Job Performance, Low Achievement, Academic Ability, Student Placement, Grouping (Instructional Purposes), Criteria, Teacher Characteristics, Administrator Attitudes, Administrators, Staff Role
DOI: 10.1108/JRIT-03-2019-0045
ISSN: 1947-1017
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.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1466047
Database: ERIC
FullText Text:
  Availability: 0
Header DbId: eric
DbLabel: ERIC
An: EJ1466047
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Data-Driven Decision-Making in Creating Class Rosters
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Rebecca+Wolf%22">Rebecca Wolf</searchLink><br /><searchLink fieldCode="AR" term="%22Joseph+M%2E+Reilly%22">Joseph M. Reilly</searchLink><br /><searchLink fieldCode="AR" term="%22Steven+M%2E+Ross%22">Steven M. Ross</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Research+in+Innovative+Teaching+%26+Learning%22"><i>Journal of Research in Innovative Teaching & Learning</i></searchLink>. 2021 14(2):162-177.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 16
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2021
– Name: Audience
  Label: Intended Audience
  Group: Audnce
  Data: Practitioners
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Information Analyses
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Data+Use%22">Data Use</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+Making%22">Decision Making</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Journal+Articles%22">Journal Articles</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Effectiveness%22">Teacher Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Performance%22">Job Performance</searchLink><br /><searchLink fieldCode="DE" term="%22Low+Achievement%22">Low Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Ability%22">Academic Ability</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Placement%22">Student Placement</searchLink><br /><searchLink fieldCode="DE" term="%22Grouping+%28Instructional+Purposes%29%22">Grouping (Instructional Purposes)</searchLink><br /><searchLink fieldCode="DE" term="%22Criteria%22">Criteria</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Characteristics%22">Teacher Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Administrator+Attitudes%22">Administrator Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Administrators%22">Administrators</searchLink><br /><searchLink fieldCode="DE" term="%22Staff+Role%22">Staff Role</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1108/JRIT-03-2019-0045
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1947-1017
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1466047
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1466047
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1108/JRIT-03-2019-0045
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 162
    Subjects:
      – SubjectFull: Data Use
        Type: general
      – SubjectFull: Decision Making
        Type: general
      – SubjectFull: Teacher Attitudes
        Type: general
      – SubjectFull: Journal Articles
        Type: general
      – SubjectFull: Teacher Effectiveness
        Type: general
      – SubjectFull: Job Performance
        Type: general
      – SubjectFull: Low Achievement
        Type: general
      – SubjectFull: Academic Ability
        Type: general
      – SubjectFull: Student Placement
        Type: general
      – SubjectFull: Grouping (Instructional Purposes)
        Type: general
      – SubjectFull: Criteria
        Type: general
      – SubjectFull: Teacher Characteristics
        Type: general
      – SubjectFull: Administrator Attitudes
        Type: general
      – SubjectFull: Administrators
        Type: general
      – SubjectFull: Staff Role
        Type: general
    Titles:
      – TitleFull: Data-Driven Decision-Making in Creating Class Rosters
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Rebecca Wolf
      – PersonEntity:
          Name:
            NameFull: Joseph M. Reilly
      – PersonEntity:
          Name:
            NameFull: Steven M. Ross
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-print
              Value: 1947-1017
          Numbering:
            – Type: volume
              Value: 14
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Journal of Research in Innovative Teaching & Learning
              Type: main
ResultId 1