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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

Aron Schmidt Vail School District schmidta@vail.k12.az.us

Thank you!