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ERIC Number: ED560386
Record Type: Non-Journal
Publication Date: 2013
Pages: 189
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-3033-6102-9
Which Variables Associated with Data-Driven Instruction Are Believed to Best Predict Urban Student Achievement?
Greer, Wil
ProQuest LLC, Ph.D. Dissertation, The Claremont Graduate University
This study identified the variables associated with data-driven instruction (DDI) that are perceived to best predict student achievement. Of the DDI variables discussed in the literature, 51 of them had a sufficient enough research base to warrant statistical analysis. Of them, 26 were statistically significant. Multiple regression and an iterative process of coding and recoding open-ended responses were used to identify perceived achievement predictors. Among the most important achievement predictor variables were working in grade- or content-alike teams, understanding and using DDI as a tool for closing achievement gaps, and having school leadership provide a clear vision for data use. In addition to achievement, a number of variables were perceived to predict equity, educator effectiveness, and educator efficacy. Open-ended responses revealed that DDI was perceived as a critical aid to future instruction and as a powerful tool for feedback. On the other hand, it was also perceived as time-consuming and as provoking a narrow focus on test scores. [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:]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site:
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A