Untangling Data-Based Decision Making: A Problem-Solving Model to Enhance MTSS (A practical tool to help you make sense of student data for effective use in MTSS)


Price: $43.95
(as of Dec 23,2024 13:35:25 UTC – Details)


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From the Publisher

robert marzano learning resources education teaching teacher author book classroom students guide

robert marzano learning resources education teaching teacher author book classroom students guide

Student data MTSS Students Team meetings Student learning Data-based decision making education teach

Student data MTSS Students Team meetings Student learning Data-based decision making education teach

Student data MTSS Students Team meetings Student learning Data-based decision making problem solving

Student data MTSS Students Team meetings Student learning Data-based decision making problem solving

 Jason E. Harlacher Jon Potter Adam Collins authors reseachers Marzano Resources education teaching

 Jason E. Harlacher Jon Potter Adam Collins authors reseachers Marzano Resources education teaching

Publisher ‏ : ‎ Marzano Resources (February 15, 2024)
Language ‏ : ‎ English
Perfect Paperback ‏ : ‎ 264 pages
ISBN-10 ‏ : ‎ 1943360782
ISBN-13 ‏ : ‎ 978-1943360789
Item Weight ‏ : ‎ 1.6 pounds

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Data-based decision making is a crucial aspect of implementing a Multi-Tiered System of Supports (MTSS) in schools. However, it can often feel overwhelming to sift through the vast amounts of student data available and determine the best course of action. To help educators make sense of this process, we have developed a problem-solving model that can enhance MTSS implementation and improve student outcomes.

Our model, Untangling Data-Based Decision Making, provides a practical tool to guide educators through the process of analyzing and using student data effectively. By breaking down the steps into manageable components, educators can more easily identify patterns, trends, and areas of need within their student population.

The first step in our model is to gather and organize relevant data, including academic, behavioral, and social-emotional information. This data can come from a variety of sources, including assessments, observations, and student records.

Next, educators should analyze this data to identify patterns and trends that may be impacting student performance. This analysis can help educators pinpoint specific areas of need and determine appropriate interventions to address these needs.

Once interventions have been implemented, educators should monitor student progress and adjust interventions as needed based on ongoing data collection. This cyclical process of data analysis, intervention implementation, and progress monitoring is key to effectively using data to inform decision making within an MTSS framework.

By following our problem-solving model, educators can untangle the complexities of data-based decision making and make informed choices to support student success within an MTSS framework. We hope that this practical tool will empower educators to use data more effectively and improve outcomes for all students.
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