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Data-Driven Decision Making For Better Instruction Online Course Week 2

Data-Driven Decision Making For Better Instruction Online Course Week 2. Weekly Objectives. Obtain skills necessary to create a computerized "Data Collection Tool" for collecting student information that will be used to improve classroom instruction.

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Data-Driven Decision Making For Better Instruction Online Course Week 2

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  1. Data-Driven Decision Making For Better Instruction Online CourseWeek 2

  2. Weekly Objectives • Obtain skills necessary to create a computerized "Data Collection Tool" for collecting student information that will be used to improve classroom instruction. • Read websites, Word documents, and PowerPoint presentations about collecting data, different data types, creating questions before building the Data Collection Tool, and scoring system. • Discuss information regarding collecting data with teammates. • Submit details about Data Collection Tool Final Project.

  3. Reflections As you review the PowerPoint presentation think about the following questions: • What is the difference between Demographic, Process, and Outcome Data? • Which of the different types of data have you used? • Can you relate to the 10 Things you Always Wanted to Know about Data-Driven Decision Making? • How does it relate to your profession?

  4. 10 Things You Always Wanted To Know About Data-Driven Decision Making • If you're not using data to make decisions, you're flying blind. • This is all about a process, not a specific technology. • Get ready to feel threatened. • You will be spending more money, not less. • Data-driven decision making does not save time. Article: http://content.scholastic.com/browse/article.jsp?id=423

  5. 10 Things You Always Wanted To Know About Data-Driven Decision Making • Your data's cleanliness is next to Godliness. • Don't shoot first and ask questions later. • A good D3M solution is one you can afford to change. • NLCB is just the beginning of your journey. • Word of warning: D3M is highly addictive. Article: http://content.scholastic.com/browse/article.jsp?id=423

  6. Various Data Collection Tools • Disaggregated student data in a spreadsheet or chart • A classroom observation tool using a form, checklist or database • An interview form to use with colleagues, students and parents • Teacher, parent and student surveys • A digital portfolio for each teacher to collect evidence • Performance assessment tools that include examples of student products • Threaded discussions, other online discussion tools, or databases for teachers to store or share reflections of what is working or not. Article: http://www.techlearning.com/story/showArticle.jhtml?articleID=13100789

  7. According to the Reading Success Network, there are the following Data Types: Demographic Data Process Data Outcome Data Demographic Data – Provides vital statistics regarding the students, their families, and the community. Process Data – Includes information relating to the school’s efforts to promote a high level of student achievement. Outcome Data – Describes how a student is doing at a particular point of time. Three Types of Data Article: http://www.sedl.org/secac/rsn/usingdata.pdf

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