ORIGINS OF THIS BOOK
We began conceptualizing this text around 1995, with the original intent of writing a follow-up to Craig Richards's 1987 book Microcomputer Applications for Strategic Management in Education. In the early stages, we began to realize not only how much the microcomputer tools of leadership had changed, but also the extent to which the general context for school leadership and the concept of leading complex dynamic organizations had changed.
Since 1995, an explosion of available electronic information and a proliferation of relatively inexpensive technologies for accessing, analyzing, and presenting data have occurred. Numerous books have been introduced that attempt to teach school leaders simple techniques of data analysis and presentation using available technologies such as spreadsheet, database, and statistical analysis software.
Although we believe it important that individuals have the opportunity to develop these skills, we believe it equally important to provide a mental model and disciplined approach for using such tools. The mental model we present is the Ecological Model of Leading and Learning. Our use of ecological is not to be confused with a literal definition of "environmental studies," but it is to be seen as a way of understanding schools and school systems as complex, interconnected ecological systems.
Our disciplined approach is collaborative improvisation. Whether jazz improvisation such as that performed by the small acoustic ensembles of the 1940s on 52nd Street in New York or baroque improvisation as performed by the great organ masters of the early 1700s, one element is critical to mastery of the artpractice. The great improvisers practiced for hours on enddecomposing music; learning to physically and musically perform a plethora of patterns, sequences, and tones; then recomposing and improvising with their newly expanded vocabulary.
Through the exercises in this book, we hope to provide students with comparable opportunities to practice decomposing and deconstructing data on schooling systems. Further, we hope that students may develop a sufficient analytic vocabulary to begin to recompose, reconstruct, and improvise with their new-tools.
ORGANIZATION OF THE BOOK
This book is organized into six parts:
- Part ISetting the Stage: Part I provides an introduction to the ecological model and the improvisational approach. In chapter 2 we provide students with a toolthe policy options brieffor organizing and distributing information on their organization.
- Part IIUsing Data to Describe the Schooling Context: In Part II we introduce the student to a series of analytic tools in Microsoft Excel for organizing and presenting descriptive analyses of data. Each chapter concludes with a narrowly focused data set and a series of questions to be addressed with the data. This part concludes with a more comprehensive data set on international investment in education and student outcomes. Students are encouraged to write a policy brief on their findings from the data.
- Part IIISearching for Relationships in Education Data: The third part introduces the student to more advanced analytic tools in Microsoft Excel. The primary emphasis is studying relationships between variables. Tools include group comparisons, scatterplots with trend-line analysis, and bivariate and multivariate regression analysis. The end of each chapter contains a narrowly focused problem set that applies the tools presented in the chapter to data ranging from student test scores across classes to state-level data on school funding and student outcomes. At the end of part III, we provide a complex and more comprehensive data set including various school resource measures and student outcomes measures. Students are provided guidance on the process of preparing analyses for a policy brief on relationships in data.
- Part IVMeasuring Time and Change in Schools: This part introduces students to the analysis of change across time. Chapter 9 addresses conceptual issues involved in studying change across time; working with time-series data, including event analysis; and understanding short- and long-run cycles. Chapters 10 and 11 address more technical issues of calculating change rates and forecasting, and a special section on financial analysis, including amortization and present and future value functions. Part IV concludes with a simulation of various demographic, economic, and financial changes occurring across time in Mission Valley Springs Unified School District. Students are encouraged to write policy briefs in which they identify important changes in the district's internal and external environment, including emergent fiscal stresses.
- Part VSystem Dynamics of Schooling: This part introduces system dynamics as an interconnected and dynamic framework for analyzing schools and school systems. Chapter 12 provides a transition from data-driven analysis to model-driven analysis. The example of student enrollment forecasting is used to show students how to transition from the spreadsheet approach of cohort survival forecasting presented in part IV to conceptualizing and eventually simulating enrollment changes across time as a series of interconnected stocks of students in grade levels and flows of students from grade to grade. Chapter 13 integrates systems modeling techniques with systems thinking concepts, including feedback loops and classic archetypes of organizational behavior such as those discussed by Senge (1990) in The Fifth Discipline. Downloadable system dynamic models of the archetypes are available on the book Web site. Part V concludes with a series of more complex, comprehensive case analyses, ranging from the unintended consequences of class size reduction in California to achieving fiscal parity in New Jersey.
- Part VIPulling It All Together: The book provides an opportunity for synthesis with part VI. This part guides the student through a comprehensive, ecological analysis of his or her organization by using the various data and model-driven strategies presented throughout the text.
USE OF THIS BOOK IN A COURSE
For the past few years, this book has been piloted in a course titled Analysis of Administrative Problems at the University of Kansas, Lawrence and Overland Park, and in The Ecology of Data-Driven Leadership at Teachers College, Columbia University. We realize that too many data and problem sets are included in this book for you to have your students use them all for preparing full-blown policy briefs. Both of us (the authors) use chapter problem sets as lab activities to familiarize students with ways to apply the various tools to the given data and to practice going through the developmental process of preparing a data-driven policy analysis. Students then choose two of the three available part simulations (Simulations II, III, and IV), for which they prepare comprehensive policy analyses and briefs.
A note of caution: The first go-round on any such activity can be a demanding and even somewhat frustrating process because students are applying new analytic methods, sometimes using new technology and preparing documents in a novel format and writing style. However, our experience has been that, despite having initial difficulties with a steep learning curve, students rapidly grow and develop skills as they progress through the activities.
THE COMPANION WEBSITE
The Companion Website that accompanies this book is central to accomplishing your teaching objectives. In fact, think of the Companion Website as the primary instructional resource and the book as a guiding handbook. If one objective is to develop and refine analytical skills, students must practice these skills over and over. The Companion Website and book offer a practice data set and problem for each chapter of sections II through V, as well as simulations at the end of sections II, III, and IV Students can readily access data, models, and documentation for all-these chapter problem sets and section simulations on the Companion Website at http://www.prenhall.com/baker .
Diverse types of data and problems are presented. Data range from the classroom level to the international level, and from student performance data to financial, demographic, and economic data. Many of the data are derived from actual situations, including student performance and economic data on 13 countries from the Organization for Economic Cooperation and Development (OECD), and elementary and high school data published annually by the state of Vermont. Additional data sets can be downloaded from the Data and Models Support link on the Companion Website.