File Name: data driven decisions and school leadership articles.zip
Data-driven instruction is an educational approach that relies on information to inform teaching and learning. The idea refers to a method teachers use to improve instruction by looking at the information they have about their students. It takes place within the classroom, compared to data-driven decision making.
Teachers generally have low efficacy in using student data to inform their day-to-day instructions. Teachers lack the basic skills to understand, interpret, and analyze data, develop instructional strategies based on data, and implement research-based instructional strategies in classrooms to address the weaknesses reflected from data analysis results. Any gap in this chain of instructional actions would lead to ineffective teaching and learning in classrooms.
This is a preview of subscription content, access via your institution. Rent this article via DeepDyve. Abrams, L. Teachers' formative use of benchmark testing data. Paper presented at the annual meeting of the American Education Research Association.
Armstrong, C. Belizean primary school teachers' understanding of assessment; assessment practices, and use of student assessment data. ProQuest Dissertations and Theses. Barry, M.
A school's use of data for teaching and learning: a case study of data's impact on instruction in an urban school. Brunner, C. Linking data and learning: the grow network study. Journal of Education for Students Placed at Risk, 10 3 , — Cho, V. Educational data use and computer data systems: policies, plans, and the enactment of practice. Districts' efforts for data use and computer data systems: the role of sensemaking in system use and implementation.
Teachers College Record, 2 , 1— Google Scholar. Coburn, C. Measurement, 9 4 , — Cosner, S. Teacher learning, instructional considerations and principal communication: lessons from a longitudinal study of collaborative data use by teachers. Courneene, J. Middle school teacher use of data-driven decision-making to improve student learning. Cruz, H. Kids plus data equals student success! Investigating the use of a structured data portfolio on students' motivation and personal accountability. Dalton, M.
A school's use of data-driven decision making to affect gifted students' learning. Datnow, A. Achieving with data: how-high performing elementary systems use data to improve student achievement.
Acting on data: how urban high schools use data to inform instruction. Available at: www. Affordances and constraints in the context of teacher collaboration for the purpose of data use. Journal of Educational Administration, 51 3 , — Deike, M. The principal as an instructional leader within the context of effective data use.
Farley-Ripple, E. Developing collaborative data use through professional learning communities: early lessons from Delaware. Studies in Educational Evaluation, 42 , 41— Ferguson, S. Teacher-leaders' use of reflective assessment practices to improve student learning. Filbin, J. Examining the impact of changes in data-driven teaching and leading on collective efficacy.
Fischer, B. Using data to increase student achievement: a case study of success in a sanctioned school. Gallagher, L. Report prepared for U. Washington, D. Gates, A. Wyoming teachers' knowledge and use of formative assessment. Godreau Cimma, K. A middle school principal's and teachers' perceptions of leadership practices in data-driven decision making. Hallinger, P. Review of research on educational leadership and management in Hong Kong, — topographical analysis of an emergent knowledge base.
Leadership and Policy in Schools, 12 3 , — Hamilton, L. Using student achievement data to support instructional decision making.
IES practice guide. NCEE — Henry, S. Principals' use of assessment data to drive student academic achievement. ProQuest Dissertations and Theses Heritage, M. Supporting teachers' use of formative assessment evidence to plan the next instructional steps.
Hill, K. Predictive indicators of high performing schools: a study of evaluative inquiry and the effective use of achievement test data. Hoover, N. Hubbard, L. Multiple initiatives, multiple challenges: the promise and pitfalls of implementing data. Studies in Educational Evaluation, 42 , 54— Ingram, D.
Accountability policies and teacher decision making: barriers to the use of data to improve practice. Teachers College Record, 6 , — Jameson, Molly M. Problem solving in action: using authentic assessment in elementary math classes. Jimerson, J. Thinking about data: exploring the development of mental models for "data use" among teachers and school leaders.
Studies in Educational Evaluation. Weave data into learning. Journal of Staff Development, 34 5 , 50— Keleher, J. Use of data management systems and data-driven decision making among school-level administrators and educators. Kerr, K.
Strategies to promote data use of instructional improvement: actions, outcomes, and lessons from thee urban districts. American Journal of Education, 4 , — King, M.
School- and district-level leadership for teacher workforce development: enhancing teacher learning and capacity. Miretsky Eds. Chicago: NSSE. Kort, T. Teachers making sense of data within a response to intervention model: a case study. Kowalski, T. Data-driven decisions and school leadership: best practices for school improvement.
Lachat, M. Practices that support data use in urban high schools.
Industry Advice Analytics. In the field of data analytics, there are several buzzwords that, while important, are poorly defined because of their complexity. One key to success in a data analysis career , however, is to establish a firm knowledge base by clearly defining these terms early on. Learning the language of data analysis will enhance your understanding and empower you to use this knowledge to your advantage. The term is generally used to describe the magnitude and complexity of information.
In addition to trying to convert a passive or reluctant CEO, three types of change programs can move an organization in the right direction: Educational programs, leading by example, and promotions and rewards. In companies with strong data cultures, important decisions are informed by data and analytics and executives act on analytically derived insights rather than intuition or experience. While digital-native companies like Amazon and Alibaba have strong digital cultures, many traditional companies are struggling to make progress. Data from surveys taken over time suggest that the problem may be getting worse. A NewVantage Partners survey of large U. In , more than three quarters reported that business adoption of big data and AI initiatives remains a major challenge. Clearly, culture depends in large part on the orientation of senior leaders, and especially the CEO.
Teachers generally have low efficacy in using student data to inform their day-to-day instructions. Teachers lack the basic skills to understand, interpret, and analyze data, develop instructional strategies based on data, and implement research-based instructional strategies in classrooms to address the weaknesses reflected from data analysis results. Any gap in this chain of instructional actions would lead to ineffective teaching and learning in classrooms. This is a preview of subscription content, access via your institution.
This study examined the effect of various district and site level conditions that influence the frequency of teacher data-driven decision-making behaviors. This study is motivated by four research questions: 1 Among various kinds of data available to teachers and principals in making data-driven decisions: a. What is the relative level of availability of that data? What is the relative frequency of use of that data? To what extent do teachers experience these conditions?
We read about it everywhere. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. Of course, this sounds incredible in theory.
Schifter, C. Contemporary Issues in Technology and Teacher Education , 14 4. Data-driven decision making is essential in K education today, but teachers often do not know how to make use of extensive data sets. Research shows that teachers are not taught how to use extensive data i. This paper presents a process used in an National Science Foundation NSF funded project to help middle-grade science teachers use elaborate and diverse data from virtual environment game modules designed for assessment of science inquiry.
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