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ERIC Number: ED538574
Record Type: Non-Journal
Publication Date: 2007
Pages: 186
Abstractor: As Provided
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Grades and Data Driven Decision Making: Issues of Variance and Student Patterns
Bowers, Alex Jon
Online Submission, Ph.D. Dissertation, Michigan State University
This study addresses the question: "To what extent are teacher assigned subject specific grades useful for data driven decision making in schools?" Recently, schools have been urged to bring teachers and school leaders together around student-level data in an effort to increase dialogue, collaboration and professional communities to improve educational practice through data driven decision making. However, schools are inundated with data. While much attention has been paid to the use and reporting of standardized test scores in policy, school and district-level data driven decision making, much of the industry of schools is devoted to the generation and reporting of grades. Historically, little attention has been paid to student grades and grade patterns and their use in predicting student performance, standardized assessment scores and on-time graduation. This study analyzed the entire K-12 subject-specific grading and assessment histories of two cohorts in two separate school districts through correlations and a novel application of cluster analysis. Results suggest that longitudinal K-12 grading histories are useful. Grades and standardized assessments appear to be converging over time for one of the two school districts studied, suggesting that for one of the districts but not the other, current accountability policies and state curriculum frameworks may be pushing into classrooms and modifying teacher's daily practice, as measured through an increasing correlation of grades and standardized assessments. Moreover, using cluster analysis, K-12 subject specific grading patterns appear to show that early elementary school grade patterns predict future student grade patterns as well as qualitative student outcomes, such as on-time graduation. The findings of this study also suggest that K-12 subject specific grade patterning using cluster analysis is an advance over past methods of predicting students at-risk of dropping out of school. Additionally, the evidence supports a finding that grades may be an assessment of both academic knowledge and a student's ability to negotiate the social processes of school. A bibliography is included. (Contains 20 tables and 28 figures.)
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Elementary Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: ACT Assessment