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Data-Informed Decisions in Education: A Compilation of Research for Best Practices

Everything you need to know about best practices for data

Sydney Azure

on 29 July 2013

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Transcript of Data-Informed Decisions in Education: A Compilation of Research for Best Practices

Data-Informed Decisions in Education: A Compilation of Research For Best Practices
Within the contents of this presentation, you can expect to read about the best practices concerning:
How to get data
Components of data collection
Ensuring that data does its job correctly
Data collection tools
Exit Slips
A brief plan to keep your data on track.

Data-Driven Instruction Overview
Data Driven Instruction is all about informing your instruction through the collection of data.
Teachers and administrators use data to improve teaching and learning within their schools and districts.
Think of it as a way to collect data from standardized assessments (Schmoker, 2009)
Gives the learner responsibility of their learning

Data Everywhere
Standardized Assessments
Classroom assignments
Small group instruction
The “What”, “When”, “Reassessment” plan:
Data can be confusing and even intimidating. Be sure to talk with grade-level teachers and administrators to decide:
What standards will be retaught
When to reteach standards
Reassess students on standards
Data-Collection Tools
Data Collection tools are:
The regular use of data
Able to do a number of things besides monitoring students progress
Used to get feedback to improve policies district-wide

Ensuring that Data Informs Instruction
There are ways to ensure that data is being analyzed and used correctly. Below are some ways to ensure proper data use.
Make sure that instructional focus is on critical thinking, reading, problem solving, discussion, and writing
Teachers in New York high schools have focused on literary analysis, scientific and reading experiments and research, and lengthy math problems
Be sure to collect data on any interventions given to students (Davis, 2012)
Four Major Components for Data Collection
According to Fenton and Murphy (2013), Data contains four major components:
How to Get Data
There are ways to get data. Below are some common ways that data is obtained.
Diagnostic Tests (This occurs before teaching takes place)
Formative Assessments (This occurs during teaching and informs instruction)
Summative Assessments (This assessment is conducted after teaching takes place)
Exit Slips
Exit slips are simple and fast way for teachers to obtain data on their students. Below are different types of prompts that can be used for Exit Slips:
Formative Assessment Prompts used to see where students are in their learning of the current content.
Students Self-Assessment Prompts are used as a way to have student assess their effort and how they use different learning approaches.
Teaching Strategy Prompts ask students to reflect on how items were taught and how the instruction has helped them.
Prompts to Openly Communicate are not usually used. These prompts allow students to give constructive criticism about the teacher and their teaching style.
More Data Reading Fun
You can get data from:
Data culture does not refer to your students racial background or at-home practices.
Culture refers to the students' aspirations and overall feelings about school and education.
Culture is important because teachers must feel like they will be able to improve overall school and class culture through professional development, which in turn, improves student learning.
Culture is important because students must feel that they are getting feedback in order to improve learning.
It is important to use assessments to drive instruction.
Make sure that assessment questions are clearly aligned to the standards
Assessments should also have the same format and consistency of state assessments

Once data collection is complete, take action
Take small steps in the beginning and work toward full understanding of the standard
Analyze data to improve teaching:
questions that students answered correctly and incorrectly
Dig deeper on the incorrect answers to understand what needs improvement and decide different ways to improve.
Refocus teaching according to question and answer analysis
Necessary Tools for Data Collection
Comprehensive Data Systems
Follows students to compare assessments and growth
Gives information on student's academic and behavioral needs
Continuous monitoring of the system and the tools
Formative Assessments
Monitored closely by a team
Structured time to analyze the tools and data
Trust for the Data
Data-Collection Tools: What to Know
Before a data-collection tool is purchased, administrators should ask themselves some questions first:
How can teachers use the system to inform their instruction?
How can students use the system to inform their learning?
What data should be tracked and how can it be tracked?

A Good Data-Collection Tool Should:
Allow teachers and administrators to decipher whether students have learned targeted standards
Allow teachers and administrators to discover if students are retaining knowledge
Show which students are ready to move on
Compare current student performance with their past performances
Provide a communication tool between teachers, administrators, and parents
Improving Data Analysis
Create data teams
Make the team culture a trusting culture
Create norms that enhance partnership
Decide why the data will be analyzed
Decide how independent teachers can be when re-teaching standards (should they follow pacing guides or is it more flexible)
Give constant support to teams (provide coaching and time to look at data and re-teach
When gains are made, decipher what piece of data contributed to the gains and be proud of accomplishments
Fenton & Murphy, 2013
Fenton & Murphy, 2013
Fenton & Murphy, 2013
Fenton & Murphy, 2013
Fenton & Murphy, 2013
Kaplank12Online, 2011
Kaplank12Online, 2011
(Marzano, 2012)
(Zavadsky, 2013)
(Zavadsky, 2013)
(Scholastic, 2013)
(Scholastic, 2013)
When Data Doesn't Do Its Job:
Too much focus on numbers (Schmoker, 2009)
Not enough focus on challenging tasks for students (Schmoker, 2009)
Data isn't doing its job if it doesn't change what is taught or how content is taught (Schmoker, 2009)
If data scores are improving because test preparation and review is what's responsible for score increase (Schmoker, 2009)
Just because the score comes from a test does not mean that it is worth taking data from (Popham, 2009)
Some states receive their test scores in comparison clusters requiring the teacher to have to rummage for appropriate scores (Popham, 2009)
Sometimes, data is used in a way that doesn't inform teaching. Below are some examples:
Schmoker, 2009
The New-Age of Data Collection
Some schools have taken data from more sources than just standardized tests. Below are some ways schools are using different types of data to inform instruction.
Schools improve through accountability: Uses multi-data sources and constantly improves as done by Denver Schools. (Zavadsky, 2013)
Risk Factor Scorecard (computerized analysis): This uses attendance, behavior, summative and formative assessments, as well as grades on each student. Used by North Carolina and can pinpoint students as early as kindergarten. (Davis, 2012)
New developments include looking at physical fitness, health issues, and socioeconomics (Davis, 2012)
Informing large-scale interventions: This is used in Long Beach, California. (Zavadsky, 2013)
Use data to inform instruction: A great example is the Sacramento, California school district that created a data model based off of the Data Wise model created in Harvard by Richard Murnane, Elizabeth City and Kathryn Parker Boudett. (Zavadsky, 2013)
Thomas, 2011
(Fenton and Murphy, 2013)
Portfolio assessment is a great way to collect data on students. Below is a brief overview on how to ensure that portfolios are successful forms of data collection.
Used as an assessment
Used as a formative assessment
Must be methodical and orderly
Standards should be specified
Must reveal what students are interested in improving
Should reflect best practices
Parental feedback is necessary
Records must be kept on progress
(Blackbourn, J.M, Blackbourn, R., Britt, Papason, Thomas, Tyler, & Williams 2005)
Annotated Bibliography
Mr. Scruff (2008). Kalimba. Recorded by Ninja Tuna. On Ninja Tuna.
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