Data Analysis and Data-Driven Decision-Making Strategies Implemented by Elementary Teachers in Selected Exited Program Improvement Safe Harbor Schools in Southern California

Autor/in	Senger, Karen
Titel	Data Analysis and Data-Driven Decision-Making Strategies Implemented by Elementary Teachers in Selected Exited Program Improvement Safe Harbor Schools in Southern California
Quelle	(2012), (226 Seiten) PDF als Volltext Verfügbarkeit Ed.D. Dissertation, University of La Verne
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-1-2678-9064-1
Schlagwörter	Hochschulschrift; Dissertation; Elementary School Teachers; Data Analysis; Decision Making; Educational Improvement; Public Schools; Elementary Schools; Academic Achievement; Alignment (Education); Curriculum Implementation; Qualitative Research; Educational Assessment; Action Research; Teacher Collaboration; Curriculum Development; Educational Change; California + Suchen Sie Ihr Suchwort? Thesis; Dissertations; Academic thesis; Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Auswertung; Decision-making; Entscheidungsfindung; Teaching improvement; Unterrichtsentwicklung; Public school; Öffentliche Schule; Schulleistung; Qualitative Forschung; Education; assessment; Bewertungssystem; Projektforschung; Lehrerkooperation; Curriculum; Development; Curriculumentwicklung; Lehrplan; Entwicklung; Bildungsreform; Kalifornien
Abstract	Purpose: The purposes of this study were to investigate and describe how elementary teachers in exited Program Improvement-Safe Harbor schools acquire student achievement data through assessments, the strategies and reflections utilized to make sense of the data to improve student achievement, ensure curriculum and instructional goals are aligned, and implement curricular and classroom changes resulting from data collection and analysis. Methodology: The subjects in the present study were 23 elementary teachers in three different elementary schools in Southern California. Subjects responded to an interview utilizing 4 structured interview questions regarding student achievement data analysis and data-driven decisions resulting from analysis. Subjects were observed during grade-level meetings. Archival data from previous grade-level meetings were reviewed for references to student achievement assessments, data analysis, curriculum, and data-driven decisions. Findings: Examination of qualitative data from the 3 public elementary schools identified reasons for successful student achievement in 3 elementary schools: consistent and frequent assessments, use of action research cycle for recognition of learning, collaborative professional teams of teachers, and embedded curricular changes in standards-based lessons. Conclusion: The study data support the conclusion that elementary schools which implement proven research strategies for frequent assessments, analysis of the assessments, alignment to state essential standards, and immediate instructional changes in the classroom are more likely to be successful in increasing student learning. Recommendations: Further research is advised: comparative case studies of frequent assessments within public elementary schools would uncover the variations between weekly and monthly assessments to increase student learning. Also, it is recommended that a qualitative study be conducted in public elementary schools analyzing active training of teachers in the area of data analysis and data-driven decisions. A third recommendation would be to research the impact district assessment and accountability offices have when they participate in the training of school staff in data-analysis topics. [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://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10