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Philip A. Streifer - Tools and Techniques for Effective Data-Driven Decision Making - 9781578861231 - V9781578861231
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Tools and Techniques for Effective Data-Driven Decision Making

€ 74.19
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Description for Tools and Techniques for Effective Data-Driven Decision Making Paperback. Philip A. Streifer provides readers with a comprehensive understanding of what data-driven decision making can and cannot tell educators about student achievement and addresses the related issues for leadership, policy development, and accountability. Num Pages: 152 pages, black & white illustrations. BIC Classification: JNK. Category: (P) Professional & Vocational. Dimension: 232 x 154 x 8. Weight in Grams: 240.
With the new federal law, No Child Left Behind, there is ever increasing pressure on schools to be accountable for improving student achievement. That pressure is taking the form of focused efforts around data-driven decision making. However, very little is known about what data-driven decision making can really tell one about improving achievement nor is there a full explanation available about what it really takes to do this work. The few examples that do exist, while proposing to get at some of these issues, make huge assumptions about educators' knowledge base and available resources necessary for success. In this book, ... Read more

Product Details

Format
Paperback
Publication date
2004
Publisher
ScarecrowEducation United States
Number of pages
152
Condition
New
Number of Pages
152
Place of Publication
Lanham, United States
ISBN
9781578861231
SKU
V9781578861231
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Philip A. Streifer
Philip A. Streifer is associate professor of educational leadership at the NEAG School of Education, University of Connecticut, where he directs and teachers UCONN's Executive Leadership Program for superintendency preparation and certification. He is also program coordinator for the school's educational administration programs. His research interest is in how educational organizations improve in a data-driven rich environment, and ... Read more

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