{ Data Driven Instruction Shifting from “what is taught” to “what is learned”

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Presentation transcript:

{ Data Driven Instruction Shifting from “what is taught” to “what is learned”

Investigate the value of data based instruction Evaluate available resources Identify methods and processes for data based instruction Objectives

 What is data driven instruction  Vail School District – Past, present, future  Research based practices Background

 Formative Assessments  Summative Assessments Background

 Marzano  Two Mistakes  Using Indirect Measures of Learning - does the measure match what is being taught  Having no explanatory model to interpret the data – data does not link to a model for success  NRCCTE Study – lack of preparation and training Concerns

 Professional Learning Communities  Create research based strategies fostering collaborative teaching environments  Utilizes data to guide and foster collaboration and learning  Outlined four fundamental questions regarding student learning Richard and Rebecca DuFour

What do we expect our students to learn?

How will we know they are learning?

How will we respond when they don’t learn?

How will we respond if they already know it?

PLC’s and Data: Using Data to drive instruction

Based on the data, what are trends that have emerged? What percentage of students demonstrate proficiency? What instructional strategies were used? Questions to guide a PLC

In simple terms… you can’t! How can we support teachers who do not have peers on site teaching the same subject? How can I have a PLC of one?

 Student Level  Program Level State Assessment Data

 Student Level  Class Level Classroom Data

 Student Level  Class Level Overall Grades

Other?

 Find the appropriate intervention to support the assessed need Matching Data to Interventions

 Data needs to represent learning  Interventions need to have specific outcomes Findings

 Aron Schmidt  Vail School District  Thank you!