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Data analysis and data-driven decision-making strategies implemented by elementary teachers in selected exited Program Improvement Safe Harbor schools in Southern California.

机译：数据分析和数据驱动的决策策略由南加州部分退出的计划改进安全港学校的小学教师实施。

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摘要

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.
机译：目的：本研究的目的是调查和描述退出计划改进-安全港学校的小学教师如何通过评估，获取信息来提高学生成绩，确保课程和教学的战略和策略来获取学生成绩数据目标是一致的，并且通过数据收集和分析来实现课程和课堂的变化。方法：本研究的对象是南加州三所不同小学的23名小学教师。受试者使用4个结构化的访谈问题回答了访谈，这些问题涉及学生成绩数据分析和分析得出的数据驱动型决策。在年级会议上观察对象。审查了以前的年级会议的存档数据，以参考学生成绩评估，数据分析，课程表和数据驱动的决策。；发现：对3所公立小学的定性数据进行检查，确定了3所小学取得成功的原因学校：一致且频繁的评估，使用行动研究周期来认可学习，教师合作的专业团队以及基于标准的课程中嵌入的课程变化。；结论：研究数据支持以下结论：小学实施了可靠的研究策略对于频繁评估，评估分析，与州基本标准保持一致以及教室中的即时教学变化更有可能成功地增加学生的学习。；建议：建议进行进一步研究：在公共小学范围内进行频繁评估的比较案例研究学校会发现他在每周和每月的评估之间有所不同，以提高学生的学习水平。另外，建议在公立小学进行定性研究，分析在数据分析和数据驱动决策方面对教师的积极培训。第三项建议是研究学区评估和问责制办公室参与对学校工作人员进行数据分析主题的培训时所产生的影响。

著录项

  • 作者

    Senger, Karen.;

  • 作者单位

    University of La Verne.;

  • 授予单位 University of La Verne.;
  • 学科 Education Elementary.;Education Administration.;Education Leadership.
  • 学位 Ed.D.
  • 年度 2012
  • 页码 226 p.
  • 总页数 226
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 动物医学（兽医学）;
  • 关键词

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