Data‐driven Decision Making and Dynamic Planning: A School Leader's Guide

Citation

Richardson, T. (2008), "Data‐driven Decision Making and Dynamic Planning: A School Leader's Guide", Journal of Educational Administration, Vol. 46 No. 5, pp. 663-665. https://doi.org/10.1108/09578230810895573

At first glance, our current educational emphasis on test scores appears to increase school accountability and to drive excellence with almost industrial vigor and justification. However, having now lived with a sometimes punitive methods of accountability that frequently look primarily at student learning data on multiple choice tests, educators can validly argue that the areas that enrich life and provide meaning and depth for the development of future leaders and democratic citizens may now be increasingly ignored due to the narrow nature of our current politically driven school evaluation. These areas include applications of math, science and language arts learning through simulations and advanced projects such as drama, art, music, and personal interaction. Despite this saddening consequence of our overvaluing of students' multiple‐choice standardized test scores as sole or primary criteria of achievement, educators would agree that there is a need for accountability, structured approaches to guide change, and a desire to help all children to maximize their potential.

In his book Data‐driven Decision Making and Dynamic Planning: A School Leader's Guide Preuss (2007) presents seven chapters focused on various concepts of data management for decision making and planning including ongoing process of identification of specific problems and issues, a comparison of the current problem condition to the ideal, clarification of priorities, development of goals, awareness of “root causes”, selection of strategies for improvement, and the implementation of action plans. To fuel this change process, multiple methods of assessment are suggested by the author that can be tailored to meet the needs of different schools and applied in a systematic way to analyze problems and make change. “Making positive things happen for students” is at the core of Preuss' 36 years of service in the public schools of New York State as a teacher, principal, superintendent, author, and change agent.

In addition to the more traditional uses of student learning data and demographic data, Preuss suggests Victoria Bernhardt's Multiple Measures of Data approach. Bernhardt's approach focuses not only on these two types of data but also on perception data and school process data as four major sources of information that may more accurately expand understanding of student's level of learning, their school experience and the functioning of the school environment. The utilization of multiple types of data could indeed prove beneficial, if related to the chosen problem or areas for improvement identified by the school, school district, state or country for which the data are used.

As one use of student learning data other than multiple choice test results, Peuss draws our attention to several questions: what is the teacher‐given‐grade failure rate at school? Where are the failures? Which departments, which classes, and which students have the higher rates of failure? Why do students fail? What is the major cause of failure? How can we eliminate failures while increasing standards? While looking at student learning data, Preuss not only suggests a variety of data sources other than multiple choice tests, but also he moves us beyond the standard practice of combining all student learning data to develop school or school district report cards of reported student statistics, to the more critical value‐added analysis. It is this value‐added analysis that determines where each student's individual progress is annually compared so educators can focus on the success and progress for each student rather than comparing one group of students in a grade level to a different group of students the next year in that same grade level. The issues explored by Preuss in determining the level that students make progress but also the depth and breadth of student progress. The author highlights the three areas that are critical for helping children learn. These include the analysis of the causes of progress or lack of progress, strategies for change, and the implementation of helping strategies. Perception data may be the area that receives the least focused in most current school evaluation. Through this approach all stakeholders (i.e. parents, students, teachers and staff) may be given the opportunity to share their perceptions in areas such as satisfaction with student learning, ability to be heard, feelings about safety and discipline, positive feelings of inclusion, fairness, self efficacy, and areas in need of improvement.

Preuss provides additional information for the reader about Dr Victoria Bernhardt, Director of Education for the Future (EFF), located on the California State University Chico, who has developed a series of questionnaires that have been used in work with schools. A web site is provided as a source for those interested in the development and use of questionnaires to gather perceptions. The site contains free downloads of questionnaires and can be found at: http://eff.csuchico.edu/home/. Furthermore, a glossary of terms is provided at the back of the book along with tutorials and graphic organizers. The book Data‐driven Decision Making and Dynamic Planning: A School Leader's Guide is a highly recommended volume for those who are invested in data driven instruction and data management. It is particularly recommended for school administrators, teachers, parents, district office personnel, and policy makers who wish to further understand how to integrate data‐based decisions into the daily work of the school. It is a practical and relevant handbook for converting data into wise decision making and planning and will help enhance skills to make data‐based decisions, to successfully measure student learning and program effectiveness, to more effectively evaluate student progress, to use data to improve instruction, and to better integrate a dynamic planning process into the daily operation of schools. The plethora of examples of test item interpretation and its application to a systematic approach to improvement strategies are most useful for those planning and developing action plans to identify perceived problems and then working through the action plans for purposes of effective implementation.

With a team of administrators, teachers, other educators and parents working toward a common goal, schools can become the hub of local community that move beyond overemphasis on multiple choice tests as the primary focus of school success to data‐ based options. All schools can become change agents that continue to monitor the progress of all children and use research‐based interventions to meet each child's individual needs. Accountability, structured approaches to guide change, and the desire to help all children to maximize their potential are realities that are here to stay. Authors like Preuss provide their wisdom based on years of experience to help each community work toward educating all children.