# data[].attributes.headline
Review missed questions and how to make edits for lessons in the future

# data[].attributes.subject
Review missed questions and how to make edits for lessons in the future

# data[].attributes.headline
Add in review practice problems from future problem sets, cool downs, and intro lessons

# data[].attributes.subject
Add in review practice problems from future problem sets, cool downs, and intro lessons

# data[].attributes.body
Edit lessons for future use. Make notes on lessons to modify pacing in the future.

# data[].attributes.body
Warm ups as a review, pacing depending on how many kids need reteaching

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Data Dives on what specific parts students are getting incorrectly, and then pulling small groups to address those skills

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You can display the work to the class anonymously of skills that were across the board mistakes and/or across the board successes

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use information to create small groups.

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Analyze responses with the PLC to make sure we are uniform and consistent with our scoring

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After my students complete an end-of-unit assessment, I distinguish whether students understood the information presented within the unit in its' entirety. I identify whether students have mastered the Learning Objective and are prepared to move to the next Unit. If students have not mastered the information successfully, I review the material that he/she/they did not master throughout the previous Unit.

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Identify opportunities to spiral review in future lessons for troublesome question types or skills

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Look at most missed questions in terms of standards and embed similar problems into future lessons.

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Look over data and compare with colleagues. We have a discussion of what worked and did not work to adjust for the future.

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Gather student feedback regarding the assessment and content. Using that feedback and all missed questions, determine how to better present the content next time.

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Analyze the responses for how to adjust the next lesson or for guidance if reteaching is needed

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Used the data to see if the student can be put into a more advanced class. For example, moving students from a standard class to the accelerated class. 

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Used the data to see if the student can be put into a more advanced class. For example, moving students from a standard class to the accelerated class. 

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Reflect on the effectiveness of instructional methods and materials. Consider what worked well and what might need adjustment in future lessons.

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Use end of unit assessments (and other data sources) to write IEP goals

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I go over key misconceptions and compare the data of the assessment.

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Analyze the data and compare with colleagues. Re-teach concepts that were still not mastered or proficient.

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I go over different questions with the students as a warm-up if it was a question that had a large number of students who didn't get it. I also use it to drive the instruction for future lessons with the same standards.

# data[].attributes.body
I grade the assessment using the rubric and I analyze the data. I see where the students were successful and where they still may need support or reteaching. I create spiral reviews with the areas of need to help them master the skill needed for the final and MCAP

# data[].attributes.body
review key concepts students have missed. use the data feature in performance matters.

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I review their assessments and discover where the students struggled. Especially how they answer the questions even after each question is explained.

# data[].attributes.body
the teacher should use the data from the assessment to lesson plan, review, and correct misconceptions that the students may have faced.

# data[].attributes.headline
break down needs by student in order to re-teach in small groups or review through warm ups and homework. 

# data[].attributes.subject
break down needs by student in order to re-teach in small groups or review through warm ups and homework. 

# data[].attributes.body
Review and analyze results and also provide feedbacks.