ERIC Number: ED657376
Record Type: Non-Journal
Publication Date: 2024
Pages: 78
Abstractor: As Provided
ISBN: 979-8-3828-3800-7
ISSN: N/A
EISSN: N/A
Using Data Dashboards to Identify and Address Disproportionate Outcomes in Exclusionary Discipline
Laura M. Samulski-Peters
ProQuest LLC, Ed.D. Dissertation, State University of New York at Buffalo
One of the most significant issues in education, as defined by the U.S. Department of Education Office of Accountability (2018), is disproportionality in exclusionary discipline. Disproportionality is defined as the over- and under-representation of racial/ethnic minorities in relation to their overall enrollment (Ahram et al., 2011). Currently, Black/African American students experience exclusionary discipline two to three times more often than all other groups combined (Bland & Mitchell, 2018). Traditionally, data use in schools has been focused on assessment and accountability data. Research has shown that using disaggregated discipline data and Data-Based Decision-Making (DBDM) processes to determine the main drivers of disproportionate outcomes is a promising strategy for neutralizing disproportionate outcomes (Girvan et al., 2017; Irvin et al., 2004). This Buffalo City School District developed a disproportionality data dashboard to allow schools to identify disproportionate outcomes in exclusionary discipline in real-time. This study explores whether school administrators are accessing their data via the dashboard. In addition, the study aims to determine if administrators who access the data are able to reduce disproportionate outcomes. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]
Descriptors: Disproportionate Representation, Discipline, Data Use, Minority Group Students, Race, Ethnicity, School Districts, Data Collection, Decision Making, Identification
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: New York (Buffalo)
Grant or Contract Numbers: N/A