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Ecology of Educational Systems: Data, Models, and Tools for Improvisational Leading and Learning [Pehme köide]

  • Formaat: Paperback / softback, 304 pages, kõrgus x laius: 235x191 mm, kaal: 513 g
  • Ilmumisaeg: 08-Apr-2004
  • Kirjastus: Pearson
  • ISBN-10: 0130977713
  • ISBN-13: 9780130977717
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  • Formaat: Paperback / softback, 304 pages, kõrgus x laius: 235x191 mm, kaal: 513 g
  • Ilmumisaeg: 08-Apr-2004
  • Kirjastus: Pearson
  • ISBN-10: 0130977713
  • ISBN-13: 9780130977717

This informative, interesting book addresses those who need to understand educational data and its place in school leadership and decision-making. It provides a set of practical tools for data analysis and decision-making using spreadsheet software and system dynamic models. Examples of the use of the popular Microsoft® Excel, several system dynamic models created by ITHINK6.0, and an introduction to the development of dynamic simulations all contribute to the reader's understanding of the concepts presented. The use of real data ensures that readers receive a realistic “feel” for handling and manipulating information, guaranteeing an understanding of the broad diversity of financial, demographic, and economic situations that occur. Topics include: information sharing in schools, organizing and manipulating data, system linkages, system dynamics, applied systems thinking, and structured improvisation. An excellent resource for all school administrators, especially those who plan budgets and need to report to school boards and their communities.

Part I SETTING THE STAGE
1(46)
Introduction
3(3)
Continuation of a Novel Approach
6(1)
Organization of This Book
6(4)
Overview: General Scope and Sequence
6(1)
Part Synopses
7(3)
Data and Models Web Site
10(3)
Rationale
10(1)
Web Site Contents
10(1)
Use of the Web Site
11(2)
Toward an Ecology of Leadership
13(14)
Perspectives on Management
17(3)
Principles of Ecological Systems
20(4)
Emergence
20(1)
Adaptive Decentralization
21(1)
Redundancy
22(1)
Anticipation
22(1)
Distinctions
22(1)
Holism
23(1)
Ecological Thinking About Leadership
24(3)
Writing Policy Briefs
27(20)
Objectives of the Policy Brief
28(1)
Universal Rules for Preparing Policy Briefs
29(1)
Rule #1: Keep It Short
29(1)
Rule #2: Keep It Simple
29(1)
Rule #3: Keep It Logical
30(1)
Structure and Universal Elements of Policy Briefs
30(2)
Executive Summary
30(2)
Introduction
32(1)
Problem or Goal Statement
32(1)
The Data-Driven Analytic Brief
32(2)
Conceptual Overview
32(1)
Preparation of the Brief
33(1)
Structure of the Brief
33(1)
The Model-Driven Policy Brief
34(3)
Conceptual Overview
34(2)
Construction of the Brief
36(1)
Structure of the Brief
36(1)
The Ecological Policy Options Brief
37(8)
Elements of the Brief
38(7)
Policy Presentations
45(2)
Part II USING DATA TO DESCRIBE THE SCHOOLING CONTEXT
47(58)
Organizing and Manipulating Data
49(20)
Types of Data
50(1)
Quantification of Information
50(1)
Sampling
51(1)
Basic Structure and Analysis of Financial Data
52(4)
Matrices and Matrix Operations
56(3)
Suggested Activity
58(1)
Structure and Peculiarities of Student Performance Data
59(2)
(Re)Organization and Manipulation of Data Sets
61(6)
Ranking, Sorting, and Filtering Data
61(2)
Subtotaling
63(1)
Pivot Table
64(3)
Summary
67(1)
Additional Resources
67(1)
Problem A: Introduction to Data Manipulation and Graphing
67(2)
Developing Indicator Systems
69(17)
Ratio Analyses Applied
74(2)
Ratios in Funding-Equity Analysis
74(1)
Ratios in Cost-Effectiveness Analysis
75(1)
The Concept of Value Added
76(2)
Value-Added Assessment in Policy and Practice
76(2)
Cohort Tracking
78(1)
Importance of Student-Level Data
78(2)
Construction of Indexes
80(3)
Efficiency
80(1)
Cost-Effectiveness
81(1)
Relative Share
81(2)
Cautions
83(1)
Summary
83(1)
Problem B: Shares and Indexes
84(2)
Applying Descriptive Statistics to the Schooling Context
86(19)
Different-Size Groups: Weighted Analysis
89(2)
Mean and Median Deviation and z Scores
91(1)
The Descriptive Analysis Tool
92(3)
Rank and Percentile Analysis
95(2)
Notes on Measuring Value Added with Norm-Referenced Data
97(1)
Notes on the Structure of Data
98(1)
Summary
98(1)
Problem C: Creation of a Descriptive Profile
99(2)
Part II Simulation
101(1)
Where We Stand: U.S. Performance and Efficiency
101(1)
Sample Summary Table for Simulation
102(1)
Part II Summary
102(3)
Part III SEARCHING FOR RELATIONSHIPS IN EDUCATION DATA
105(54)
Similarities and Differences Among Groups
107(14)
Research Literature on Group Comparison
108(1)
Same Group, Two Points in Time
109(2)
Two Groups, Same Test
111(2)
Two Groups, Two Points in Time
113(1)
Differences Within and Among Multiple Groups
113(3)
Statistical Significance Versus Policy Relevance
116(1)
Results from the Research Literature: Tennessee Findings
117(1)
Summary
118(1)
Problem D: Group Comparisons
118(3)
Education Data and Statistical Relationships: I
121(14)
Research Literature on Organizational Input-Outcome Relationships
122(1)
Data in Two Dimensions: x and y
123(2)
Interpretation of Relationships Between x and y
125(4)
The Search for Relationships in Larger Data Sets
129(3)
Summary
132(1)
Problem E: Finding System Linkages
133(1)
Appendix A: Possible Scatterplot Variations
134(1)
Education Data and Statistical Relationships: II
135(24)
More Concepts from the Input-Outcome Literature
136(1)
Dependence and Independence: The Relative Roles of x and y
137(1)
Analysis of Types of Linear Relationships
138(2)
Formal Linear Regression Analysis
140(3)
The Effects of Many xs on a Given y
143(3)
Alternative Relationships
146(2)
Findings from the Research Literature
148(3)
Summary
151(1)
Problem F: Finding System Linkages
151(1)
Appendix A: Interpretation of Your Results
152(3)
Part III Simulation
155(1)
Redesigning Schooling in Vermont
155(2)
Approaching a Complex Study of Linkages
157(1)
Exploratory Phase
157(1)
Constructing and Following a Rational Path
157(1)
Part III Summary
158(1)
Part IV MEASURING TIME AND CHANGE IN SCHOOLS
159(42)
Time: The Forgotten Dimension
161(10)
Tools for Analyzing Change Across Time
162(1)
The Search for Events
163(2)
The Study of Events in Educational Systems
165(2)
Trends and Patterns
167(2)
Measurement of Data Across Time
169(1)
Summary
169(1)
Problem G: Storytelling with Time Series
170(1)
Studying Change with Data
171(13)
System Kinematics
172(2)
Relative Motion
174(4)
Case Example
176(2)
Special Section: A Primer on Financial Tools in Excel
178(3)
Present and Future Value
179(1)
Amortization
180(1)
Summary
181(1)
Problem H: Storytelling with Time Series
181(3)
A Look into the Future
184(17)
Linear Extrapolation Forecast
185(1)
Moving-Average Forecast
186(1)
Moving-Average/Linear Extrapolation Shortcut
187(1)
Exponential Smoothing
187(2)
Smoothed Forecasts
189(1)
Option 1: Forecast Data, Then Smooth Forecasted Data
189(1)
Option 2: Smooth Data, Then Forecast Smoothed Data
190(1)
Integrated Application: Matrices, Moving Averages, and Enrollments
190(3)
Assessment of Forecast Accuracy and Model Testing
193(1)
Advanced Topic: Multivariate Forecasting
194(3)
Summary
197(1)
Problem I: Forecasting and Checking
197(2)
Part IV Simulation
199(1)
Feeling the Budget Crunch in Mission Valley Springs
199(1)
Part IV Summary
199(2)
Part V SYSTEM DYNAMICS OF SCHOOLING
201(56)
From Data-Driven Analysis to Model-Driven Analysis
203(10)
Modeling Processes
204(1)
Two Views on a Classic Education Operations Problem
205(5)
Reviewing the Matrix Model
205(1)
Introducing a Systems Model of the Process
206(2)
Introducing User Controls
208(2)
Running the Model, Testing Scenarios
210(1)
Analyzing Sensitivity
210(1)
Summary
210(1)
Problem J: Experiments with the Enrollment Model
211(2)
Systems Thinking Applied
213(19)
ithink Models of Feedback Structures
215(1)
Out of the Shower and into the School
216(8)
Sample Systems Archetypes
224(5)
Limits to Success
224(1)
Shifting the Burden
224(1)
Escalation
225(2)
Tragedy of the Commons
227(2)
Summary
229(1)
Problem K: Reversing Reinforcing Feedback: A Policy Example
229(3)
Dynamic Models of Schooling
232(25)
Case 1: Simultaneity of Language and Knowledge Acquisition
233(3)
Background
233(1)
The Model---NYC.ITM
234(1)
Suggested Simulations
235(1)
Modification and Extension
236(1)
Case 2: Chasing the Moving Target---Meeting Equity Demands in New Jersey
236(5)
Background
236(1)
Model Structure
237(1)
Suggested Simulations
238(3)
Case 3: Unintended Consequences of Class Size Reduction
241(9)
Background
241(2)
Model Structure and Assumptions
243(7)
Suggested Activities with the Class Size Reduction Model
250(1)
Technical Note on the Class Size Reduction Model
250(1)
Notes on Approaches to Systems Modeling in Education
250(2)
Physical Systems Modeling
251(1)
Hypothetical Systems Modeling
251(1)
Research Synthesis Modeling
251(1)
Notes on Model Development
252(1)
Summary
253(2)
Part V Summary
255(2)
Part VI PULLING IT ALL TOGETHER
257(16)
A Guide to Structured Improvisation
259(14)
Data-Driven Analyses
260(4)
Compliance Analysis
261(2)
Performance Analysis
263(1)
Dynamics Mapping
264(1)
Model-Driven Analyses
264(4)
Organization
264(1)
Modifications for Class Activities and Practice Exercises
265(1)
Problem Definition
266(1)
Conceptualization of the Model Structure
267(1)
Ecological Analyses
268(3)
Exogenous Conditions
269(1)
Policy Levers
269(1)
Reconciliation of Discrepancies
270(1)
Feedback and Follow-Up
270(1)
Summary
271(2)
References 273(2)
Name Index 275(2)
Subject Index 277