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Software Enabling School Improvement through Analysis of Student Data. Report Number 67

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Title: Software Enabling School Improvement through Analysis of Student Data. Report Number 67
Language: English
Authors: Wayman, Jeffrey C., Stringfield, Sam, Yakimowski, Mary, Center for Research on the Education of Students Placed At Risk, Baltimore, MD.
Source: Center for Research on the Education of Students Placed at Risk (CRESPAR), Johns Hopkins University. 2004.
Availability: Center for Research on the Education of Students Placed at Risk (CRESPAR). Johns Hopkins University, 3003 N Charles Street Suite 2000, Baltimore, MD 21218-2685. Tel: 410-516-8810; Fax: 410-516-8890; Web site: http://www.csos.jhu.edu/crespar
Peer Reviewed: N
Page Count: 63
Publication Date: 2004
Sponsoring Agency: Institute of Education Sciences (ED), Washington, DC.
Document Type: Opinion Papers
Reports - Evaluative
Descriptors: Computer Uses in Education, Computer Software, Data Analysis, Information Management, Computer Software Reviews, Program Implementation, Student Records, Educational Improvement, Decision Making
Abstract: The No Child Left Behind legislation has drawn increased attention to student data. Data are most useful in educational decision-making when the purpose extends beyond vertical accountability and toward school- and classroom-level decision-making that enhances the experience and achievement of students. This necessarily involves getting practical data analyses into the hands of teachers and administrators. Recent technological advances in data warehousing and presentation have resulted in tools that can, in theory, facilitate educator use of student data. The use of these tools, however, is not yet widespread. The resulting condition is ripe for both educational improvement and research. In this report, the authors consider issues surrounding the use of student data and data-based decision-making, describing the state of the field, and possible future directions. Also presented are reviews of a range of commercially available software for analyzing student data, and a website that will contain ongoing updates of software reviews. Appended are: (1) a list of software companies with products the authors were unable to review for this report, but that provide analysis of student data; and (2) "screen shots" from vendors who provided examples of their software. (Contains 6 footnotes and 2 tables.)
Abstractor: Author
Number of References: 63
EIS Cited: ED506645
Entry Date: 2006
Accession Number: ED489950
Database: ERIC
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  Data: Software Enabling School Improvement through Analysis of Student Data. Report Number 67
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  Data: Center for Research on the Education of Students Placed at Risk (CRESPAR). Johns Hopkins University, 3003 N Charles Street Suite 2000, Baltimore, MD 21218-2685. Tel: 410-516-8810; Fax: 410-516-8890; Web site: http://www.csos.jhu.edu/crespar
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  Data: The No Child Left Behind legislation has drawn increased attention to student data. Data are most useful in educational decision-making when the purpose extends beyond vertical accountability and toward school- and classroom-level decision-making that enhances the experience and achievement of students. This necessarily involves getting practical data analyses into the hands of teachers and administrators. Recent technological advances in data warehousing and presentation have resulted in tools that can, in theory, facilitate educator use of student data. The use of these tools, however, is not yet widespread. The resulting condition is ripe for both educational improvement and research. In this report, the authors consider issues surrounding the use of student data and data-based decision-making, describing the state of the field, and possible future directions. Also presented are reviews of a range of commercially available software for analyzing student data, and a website that will contain ongoing updates of software reviews. Appended are: (1) a list of software companies with products the authors were unable to review for this report, but that provide analysis of student data; and (2) "screen shots" from vendors who provided examples of their software. (Contains 6 footnotes and 2 tables.)
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