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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
