School Data Analysis (SDA)
"Is what we are doing working, and HOW do we know?"
In April 2012, the SDP/A was streamlined by reducing the questions from 82 down to 60, then in February 2013 where gap and cause questions were moved to the SDA causing an increase to 68 questions. Now in 2015, the SDA has actually been reduced to 28 questions (with multiple parts "a-c"). An introduction of "Process Data" questions has been added and the achievement data reduced to each content area strength, weakness, trends and a school response related to the SIP.
Due to the reduction in questions related to achievement, schools should consider utilizing a process to analyze the data such as the Data-Driven Dialogue Protocol adopted from Bruce Wellman and Laura Lipton's Data-Driven Dialogue: A Facilitator’s Guide.
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You may want to use this quick link to the NEW SDA Guidance Document (reduced to 28 questions in 2015) which includes step-by-step instructions for how to locate/access the data necessary for answering the SDA questions.
In addition, the video on the left features this MS Excel document that will help convert scale sores to percentiles relative to the state to compare MEAP data with M-STEP. |
State Data in 2015?The convertion in the podcat and accompanying Excel document is completely optional. MDE simply recommends using the most recent state and local data you have available to inform your DIP or SIP. The image on the right will enlarge when selected, it contains the official recommenation from MDE from the May 7 "Spotlight."
Another option is looking at a trend the past three years through the lens of the Reading Now Network. |
Are you in the Top 20% of RNN Data? |
The Reading Now Network (RNN) Data tool is a NEW way to look at your reading data over the past three years. Background on the study and videos to support the use of the tool available.
Click the ASSIST Support page to see directions and/or YouTube videos on how to copy any diagnostic report that has not changed from last year. There is also guidance how to start a new report, attach to the portfolio task, mark complete (when actually completed) and schools to submit the report. Of course, districts will also be given guidance on how to accept/approve the school level reports. |
Updating the SDA by digging deeper into the data
When digging into data, remember to celebrate successes as well as looking for areas of concern. In addition to tracking all students, consider any subgroups that apply to your school such as gender, English Learner (EL), Students with Disabilities (SWD), Socio-Economically Disadvantaged (ED or SES), migrant, and all applicable ethnic groups.
The basic steps to completing the School Data Analysis (or Needs Assessment Diagnostic in the new ASSIST platform) are below; you may click the Digging Deeper tab to the left to see screen shots and sample observations that would be collected during the process.
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Basic Steps for SDA Completion
1) Dialogue with staff regarding how they believe achievement data from state and local assessments will look.
2) Print the current SDA to view the questions in order to create an awareness of the type of conclusions to be drawn and to highlight responses that most likely need to be updated.
3) Create small groups of teachers to analyze different sections of the SDA and different content areas using the Data-Driven Dialogue Protocol and the accompanying Data-Driven Dialogue spreadsheet.
4) Utilize MiSchoolData.org to look at enrollment and schools of choice data across subgroups; also identify achievement trends compared to state or ISD averages per grade level per content.
5) Drill down beyond global data found on MI School Data to include timely, diagnostic, and local data such as ACT Plan, Explore, Delta Math, DIBELS, etc. Also include HS Strand and EL/MS GLCE historical trend reports most likely available on a local data warehouse (IGOR, IRIS, Data Director, etc.).
6) Once the data is gathered, lift key findings and report out to the larger group. Facilitate a discussion regarding causality which will lead to brainstorming possible solutions. Remember, when identifying causes, focus on the factors which the staff controls or at least over which they have influence.
7) REPORT the updated "answers" to the questions on the ASSIST site in mid-April (drop-point deadline Sept 1).
8) You have now identified the target areas necessary to determine whether or not to "keep" the strategies in your current school improvement plan; proceed to the SIP page to begin your planning process.
For further support, view the video demonstrating the above process (20 minutes w/ the first 3 minutes setting the stage, 15 minutes navigating MI School Data and the final 2 minutes accessing the Google Doc)
2) Print the current SDA to view the questions in order to create an awareness of the type of conclusions to be drawn and to highlight responses that most likely need to be updated.
3) Create small groups of teachers to analyze different sections of the SDA and different content areas using the Data-Driven Dialogue Protocol and the accompanying Data-Driven Dialogue spreadsheet.
4) Utilize MiSchoolData.org to look at enrollment and schools of choice data across subgroups; also identify achievement trends compared to state or ISD averages per grade level per content.
5) Drill down beyond global data found on MI School Data to include timely, diagnostic, and local data such as ACT Plan, Explore, Delta Math, DIBELS, etc. Also include HS Strand and EL/MS GLCE historical trend reports most likely available on a local data warehouse (IGOR, IRIS, Data Director, etc.).
6) Once the data is gathered, lift key findings and report out to the larger group. Facilitate a discussion regarding causality which will lead to brainstorming possible solutions. Remember, when identifying causes, focus on the factors which the staff controls or at least over which they have influence.
7) REPORT the updated "answers" to the questions on the ASSIST site in mid-April (drop-point deadline Sept 1).
8) You have now identified the target areas necessary to determine whether or not to "keep" the strategies in your current school improvement plan; proceed to the SIP page to begin your planning process.
For further support, view the video demonstrating the above process (20 minutes w/ the first 3 minutes setting the stage, 15 minutes navigating MI School Data and the final 2 minutes accessing the Google Doc)
Four Types of Data

In addition to the Process Profiles (SSR26 or Interim SA) and the perception surveys, the SDA focuses primarily on demographic and achievement data. The SDA and SSR26 (or Interim SA) make up the Comprehensive Needs Assessment (CNA). Collect any data not available on mischooldata.org such as staff demographics, suspensions/expulsions, survey data, and local assessment data. All necessary data can be categorized as depicted in the graphic on the left.
Understanding the Intersections

Upon completion and analysis of the School Data Profile, teams must choose appropriate strategies to address target areas. While academic data is almost always the focus for such decision-making, there are three other types of data gathered and studied in the profile that should be taken into consideration: demographic, perception, and process.
This Intersection Activity from Victoria Bernhardt's Data Analysis for Comprehensive Schoolwide Improvement provides easy-to-use support for utilizing the four types of data together to make the best decisions possible for your students.
The featured graphic succinctly illustrates and describes the various data points provided through an analysis of how each of the four types of data intersect. Also included in the link is a blank form of the graphic for use with staff--scaffolding for the introduction of the represented concepts.
This Intersection Activity from Victoria Bernhardt's Data Analysis for Comprehensive Schoolwide Improvement provides easy-to-use support for utilizing the four types of data together to make the best decisions possible for your students.
The featured graphic succinctly illustrates and describes the various data points provided through an analysis of how each of the four types of data intersect. Also included in the link is a blank form of the graphic for use with staff--scaffolding for the introduction of the represented concepts.