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STAGE 1 of the OIP begins with this kind of assessment using Ohio’s Decision Framework (DF) tool. The DF is a decision-making aid designed to assist districts in making informed decisions – based on what their data tell them – about where to spend their time, energy, and resources to make significant and substantial improvements in student performance. A state-developed data warehouse allows for relevant data needed to complete the DF process to be readily available to districts and buildings, and community schools (AKA charter schools). Such data are organized in such a way as to allow district leadership teams (DLTs) and building leadership teams (BLTs), and community school leadership teams (CSLTs), to answer essential questions and make decisions about their greatest need related to improving student learning and performance.

The DF was created for districts and buildings because while many districts have an abundance of data, they have limited expertise in sorting and/or analyzing these data. Districts with experienced data managers rely on that person to analyze data, but there is seldom a shared understanding of what the data mean; data managers seldom connect the data they are seeing to behaviors and practices around curriculum, assessment, instructional practice, and professional development (PD).

Since the DF tool contains pre-populated data and “essential questions,” districts can use the tool to sort through and categorize data in meaningful ways; prioritize areas of need and make more focused decisions based on an analysis of data; identify the root causes of prioritized needs; and develop a more focused plan leading to improve student achievement. Almost all student performance data included in the tool are three-year trend data for all students tested – by grade-level, building, and major disaggregated student groups. In addition to performance data, discipline, expulsion/suspension, dropout, graduation rate, and attendance data are pre-populated.

For more information about identifying critical needs at Stage 1, go to:

http://www.ohioleadership.org/mod_view.php?nav_id=716

This tool aims to facilitate planning for improvement of data systems based on data collected from users. The tool can be used to identify data collection goals and to document decisions made based on the data collected.


“Using the Decision Framework tool helped us really look at the data and define our own expectations. We had focused and collaborative discussions around student leaning that helped us create an environment of learners for students and adults across the district.”

Dr. Jeffrey Graham, Superintendent
Parma City Schools

The DF uses essential questions to help the district use data to tie problems, such as the lack of significant student progress, to curriculum, local assessments, instructional practice, and PD. The essential questions set the stage for district teams to make more informed and intentional decisions about their most pressing problems, including decisions about internal issues such as the use of time, personnel and funding, and provide a structure for informing their community, including parents and students, about the decisions.

Using the DF analysis allows districts to focus on facts, not opinions or preferences about what is not working and the issues that need to be addressed, and to reach agreement about solutions.

The DF is organized around the four levels outlined below, each of which asks teams to consider essential questions and their degree of implementation and/or level of concern in relation to each (e.g., curriculum alignment and accessibility) identified as being important for improving academic performance of all students, including sub-group populations.

Level I: Student Proficiency

In Level I, leadership teams review student proficiency data across four years by grade level, building level/grade span, and disaggregated student groups to identify up to two content areas of greatest concern. Further analyses using subscale performance data are completed by the team only for those content area(s) identified as areas of greatest concern. The remainder of the DF – Levels II, III, and IV– provide essential questions for helping districts conduct a root cause analysis of those factors contributing to the district’s current situation. Level II, which has a direct impact on student performance, is completed for each area of concern identified under Level I of the DF. Levels III and IV, which have a more global impact, are completed once.

Level II: Instructional Management

(Curriculum, Assessment, & Instructional Practice; Educator Quality; Professional Development)
In Level II, leadership teams answer essential questions in relation to each of the content area(s) of greatest concern identified under Level I. Essential questions under Level II focus on curriculum, assessment, instructional practices; educator qualifications, teacher and principal turnover; and the degree to which district professional development (PD) is aligned to problem areas, is designed to promote shared work across the district/buildings, and is effective in helping teachers acquire and apply needed knowledge and skills related to the improvement of instructional practice and student performance. Following the completion of the Level II analyses, teams make decisions about the most probable causes contributing to the major problem areas identified under Level I.

On DWW, this Expert Interview (Supporting Teachers in Understanding and Using Data) by Ellen B. Mandinach, Ph.D. discusses the importance of providing professional development to help teachers learn how to use data. She emphasizes the need for the professional development to be aligned with the school's goals and needs. The professional development should be timely and ongoing. (5:17 min)

Level III: Expectations & Conditions

(Leadership; School Climate; Parent/Family, Student, Community Involvement)
In Level III, leadership teams answer essential questions related to leadership; school climate (including student discipline occurrences, student attendance and mobility, students with multiple risk factors, and teacher and student perception); and parent/family, student, and community involvement and support to identify additional probable causes contributing the areas of greatest need identified in Level I.

Level IV: Resource Management

In Level IV, leadership teams answer essential questions related to resource management – defined as the intentional use of time, personnel, data, programmatic, and fiscal resources – to identify additional causes contributing the area(s) of greatest need identified in Level I.

Through the completion of the DF, leadership teams prioritize areas of greatest concern, as well as causes contributing to those areas of concern. The decisions made by the team at Stage 1 of the OIP using the DF provide the foundation for the creation of a district plan with a limited number (two to three) of focused goals and a limited number (three to five) of focused strategies associated with each goal.

At the school level, Building Leadership Teams (BLTs) complete a similar process at Stage 1 of the OIP by using a building-level decision framework to review data and identify a limited number of action steps for improving performance to reach district goals. Marzano, Waters, and McNulty (2005) describe the development of strong building leadership teams (BLTs) and the distribution – throughout the team – of some of the 21 practices that characterize the job of an effective principal as key steps in enhancing student achievement. Such practices, identified through McREL’s meta-analysis of 35 years of research on school-level leadership, suggests that leading a building requires a “complex array of skills” not likely to be found in a single individual and support the need for strong leadership team structures. The DF assists DLTs, BLTs, and CSLTs in selecting the right work (i.e., work that has a high probability of improving student achievement), based on data-based decision making and focused planning, as well as developing the collective know-how to do the right work across the system.