data driven instructional leadership region 18 leadership development

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Making Sense Out of Chaos What data? How and When? How and When should it affect programs? How and when will it affect the classroom? How will we make time? How does it affect goal setting?

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Data Driven Instructional Leadership Region 18 Leadership Development Overview Told Constantly Common sense Data rich but information poor Making Sense Out of Chaos What data? How and When? How and When should it affect programs? How and when will it affect the classroom? How will we make time? How does it affect goal setting? Data Driven Instruction System It cannot be haphazard Designing and Implementing data can be the catalyst for school improvement Not as difficult as it sounds if carefully planned and implementation is clearly mapped out DDIS Model Data CollectionData ReflectionData Translation Data Driven Instructional Design Design Feedback Summative Formative Assessment Data Collection Most critical aspect Constantly changing Backbone of DDIS Data Reflection Student needs must drive staff development Data Translation Includes curriculum mapping Content adjustments Instructional adjustments Starts with curriculum experts Identifying the gaps Teaching staff involved in solution Data Driven Instruction Design Includes lesson design and differentiation The tiered lesson plan model 1.Analyze data about student learning 2.Design lessons to meet each students needs 3.Teach the lesson to multiple levels of students at once Teachers do not innately know how to do this We must get them training Design Feedback Provide information back to stakeholders Regarding the design and implementation of the school improvement activities Summative and Formative Feedback Conducted to determine success so far Teachers have got to stop seeing assessment as summative Assessment should be used to inform teachers about the gaps in the learning progress of students Goal Setting and Getting Started Fluid Process II. Data Collection Making sense of the data is critical Who, What, Where, When, Why, and How Use multiple measures of data Demographic Data Gender Title I Status Race Socio-Economic ELL Status Discipline Attendance Health Status Enrichment programs Remediation Programs Special Pops Student Learning Data Local Assessment State Assessment Classroom Lexile levels School Process Data Finance Transportation Bell Schedules Tutorials Key is to determine how this information relates to student learning Perceptions Data How do students view things? How do parents view things? What is the school known for? Typically overlooked Not easily collected The Who, When, and How of Data Collection Someone needs to be in charge Data is collected by many Establish a data discovery team Teams purpose is to identify what data is important Compile a list Everyone must understand their role and why it is critical District manager makes sure everything runs smoothly Create a data entry protocol No shortcuts Who is going to check for accuracy School must track the staff development teachers attend Have the students been successful Cost effective If students are not improving then what adjustments must be made Where to store the data? Must be assessable and Robust Must be able to drill down from several angles The district cannot be nonchalant about data collection District must be willing to make long term commitment to data process Do not assume that data gathering is easy just because it is first III. Data Reflection Teachers must be given time to talk When and When to Find Time District Data Retreat Workshop Professional Learning Time Formal and Informal Data Translation Is systemic and takes time Involves analyzing and interesting data Teachers and administrators must use their own data in order to know what changes must be made School district must support the process with resources Focus on one improvement V. Data-Driven Instructional Design Goal of entire program How and When Get data into the hands of teachers Ownership is the key Takes time and training Once teachers understand what is behind it they will embrace it A data driven culture will develop Constant follow-up and focus are needed Changes are made based on data that was reviewed and translated into curriculum and classroom instruction design VI. Design Feedback How is data assessed and how is this communicated to stakeholders How is DDIS Adjusted and Evaluated SMART goals Specific Measured Attainable Results oriented Time bound Adjustment Evaluation VII. Summative and Formative Assessment We must change the paradigm VIII. Summary and Results: Is It Worth It? Scores will increase Innovative programs will be developed ESL Literacy Gives you the framework for the improvement process How Do I Get Started? Put someone in charge of the process Four Keys Purpose Focus Communication and coordination Follow Through Important Limit the focus to one or two things If teachers are asked to do something they must understand why they are doing it