Using Data for Instructional Decisions Brenda Benson Fifth District Elementary

PT3 Grant Goal Prepare preservice teachers to use technology to interpret and analyze student and school data to develop data-driven instructional decisions.

Data and Dieting … What is the connection ?

How is Data Collection Like Dieting? Want to measure student learning Want to measure physical fitness One source of data to monitor student improvement: MSA One source of data to monitor weight loss: daily scale check Relationship between 1 test and reading ability is indirect. Relationship between a person’s weight and physical fitness is indirect.

Using the Data Data Collection Dieting Additional data: CTBS scores Unit tests Classroom performance Skill checks Inventories Additional Data: Resting heart rate Cholesterol level Strength Endurance

Using the Data Data Collection Dieting The data will not help to improve student achievement if there is not a plan for interpreting and using the data. The data will not improve a person’s physical fitness if there is not a plan for how to improve.

Data Collection “The only way for teachers and schools to identify which students can demonstrate proficiency on the Maryland Content Standards is to continuously assess and monitor students as part of their classroom instruction.” (http//www.mdk12.org/data/progress/index.html) Student performance on assignments and assessments enable teachers to make informed instructional decisions regarding teaching and re-teaching specific indicators.

What does this mean for the classroom teacher?

Teachers need to collect and analyze a variety of data in a variety of ways. Types of Data Collected Strategies for Analyzing Data Tools to collect and analyze data

Types of Data Collected

Types of Data Collected Formative Data Daily assessments Summative Data End of unit or theme Houghton Mifflin Theme Tests BCPS Math Summative Tests MSA and CTBS

Sample Formative Assessment Finding the Main Idea Complete the diagram with facts from All About Eagles. Main Idea Paragraph 2 Main Idea Paragraph 1 Details Details

Sample Summative Assessment Integrated Reading Theme Skills Datasheet EDHD 485 teachers: Examples will be provided later in our dace to face sessions

Strategies for Analyzing Data

Strategy 1 for Analyzing Data: Individual Teacher Data Collection

Individual Teacher Data Collection Teachers review individual student assignments and assessments to identify strengths and weaknesses. Teachers adjust daily instruction based on this information.

Strategy 2 for Analyzing Data: Grade Level Data Discussions

Grade level groups analyze data Teachers enter data into Excel and then manipulate it to see which students are still having trouble overall. Teachers analyze strengths and weaknesses as a grade level each month. Teachers identify interventions, staff development and materials needed at quarterly data discussions.

Grade 3 Theme Tests Term 1 and Term 2 Sample Data Grade 3 Theme Tests Term 1 and Term 2 1 2 1 2 1 2

Strategy 3 for Analyzing Data: Vertical Team Data Discussion

Vertical Teams Analyze Data Teams of teachers working with similar types of learners across grade levels share teaching strategies.

Tools to collect and analyze data

Tools Used for Collecting and Analyzing Data Individual Teacher Grade Books Paper or Electronic Houghton Mifflin Theme Test (required assessment by local school system) Grade Level Data Summary

Practice using Data Tools Analyzing Data… Working in small groups

Using Data to make Instructional Decisions Use the Houghton Mifflin Theme Test data provided. Use data to make decisions about instruction. What skills need re-teaching? What strategies will you provide? What resources/professional development do you need to help with your instruction? See Excel spreadsheet

What does this mean for the pre-service teacher?

MTTS IV : Module Planning “Remember that statistics don’t learn or teach.” Baltimore Sun January 8, 2004

Contact information Ms. Brenda Benson Fifth District Elementary 410-887-1726 Baltimore County Public Schools