In the first Data learning series, Leading a Culture of Effective Data Use, we focused on the culture, capacity, and quality of data and set a foundation for this learning series, Engaging in Data-Based Problem Solving. We want to foster coherence by connecting all three of the Data learning series and your vision of improving outcomes for all students. Establishing a data culture (Series 1) allows districts and schools to engage in authentic data-based problem solving (Series 2) and creating a plan for improvement using data to inform decisions (Series 3).
The IL MTSS-N is a project of the Illinois State Board of Education, with funding from the State Personnel Development Grant. Due to federal funding requirements and to provide feedback for internal development, please complete the pre-post test at the bottom of this page after viewing all of the following modules.
The Introductory Module for Series 2, Engaging in Data-Based Problem Solving, provides a flyover view of the series’ modules; the most effective way to use/view the modules; and how to access and use handouts.
Continuous improvement helps districts advance their entire system – a framework to improve teaching for all teachers and learning for all students. Continuous improvement happens by using a problem-solving method of decision-making. The Illinois MTSS Network utilizes and will demonstrate in our learning sessions, a four-step process. In this module, learners will compare the four-step problem-solving approach to their district’s framework for continuous improvement.
A comprehensive data profile is a tool to organize, house, and provide access to the school’s data. Bernhardt says that a data profile tells the story of the district and school. Analyzing multiple sources of data provides district and school teams a more comprehensive picture of the reality that currently exists in their district or school. The first step is to fully understand and describe each of the data measures that make up a comprehensive data profile. In this module, we will explore the four specific data types that need to be collected at the beginning of the continuous improvement journey.
Data use is a process that integrates the analysis of educational data to support decisions intended to improve teaching and learning at the school and classroom levels. In this module, we will lead you through a process that brings all of the data together and engages staff to identify strengths, challenges, and implications for the continuous district/school improvement plan. By engaging in this learning, you will be able to identify the six steps of the data analysis process and compare these steps to the process that your district and/or school teams currently use.
To understand how and why the organization is getting the results it is getting now; what is working and what is not working; and, to learn more about what to do differently to get different results, we need to delve deeper into the data to get answers. In Module 4, Parts 1 and 2, you will apply the knowledge and skills you learned in Modules 1 – 3 to delve deeper into data analysis. In Part 1, your objective is to understand how intersections of data measures support deeper analysis and then apply intersections of multiple measures of data for a deeper analysis. In Part 2, you will demonstrate an understanding of contributing cause analysis and how to apply this understanding.
The IL MTSS-N is a project of the Illinois State Board of Education, with funding from the State Personnel Development Grant. Due to federal funding requirements and to provide feedback for internal development, we kindly request you complete this short pre-post survey after viewing each series.