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Data-Driven Decisions and School Leadership: Best Practices for School Improvement [Pehme köide]

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  • Formaat: Paperback / softback, 288 pages, kõrgus: 10 mm
  • Ilmumisaeg: 04-Sep-2007
  • Kirjastus: Pearson
  • ISBN-10: 0205496687
  • ISBN-13: 9780205496686
Teised raamatud teemal:
Data-Driven Decisions and School Leadership: Best Practices for School ImprovementSuurem pilt
  • Formaat: Paperback / softback, 288 pages, kõrgus: 10 mm
  • Ilmumisaeg: 04-Sep-2007
  • Kirjastus: Pearson
  • ISBN-10: 0205496687
  • ISBN-13: 9780205496686
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780205496686.html
Märksõnad:

This book integrates theory and practice in decision-making, with a specific focus on data-driven decision making. Applications are demonstrated in the contexts of administration, supervision, and teaching.

 

The book provides a unique contribution to the literature in this field in that the studies of decision theory and data-based decision making are integrated. Focusing on educators assuming leadership roles in school improvement, the book’s content is equally relevant for administrators, supervisors, and teachers.

The book, however, is centered on data-driven decision making, both as a requirement of the No Child Left Behind Act and as a normative professional standard. Issues related to accumulating, storing, and protecting data in districts and schools also are covered. Applications in administration, supervision, and teaching are demonstrated. 



The book provides a unique contribution to the literature in this field in that the studies of decision theory and data-based decision making are integrated. Focusing on educators assuming leadership roles in school improvement, the book’s content is equally relevant for administrators, supervisors, and teachers.

The book, however, is centered on data-driven decision making, both as a requirement of the No Child Left Behind Act and as a normative professional standard. Issues related to accumulating, storing, and protecting data in districts and schools also are covered. Applications in administration, supervision, and teaching are demonstrated.

Muu info

The book provides a unique contribution to the literature in this field in that the studies of decision theory and data-based decision making are integrated. Focusing on educators assuming leadership roles in school improvement, the book's content is equally relevant for administrators, supervisors, and teachers. The book, however, is centered on data-driven decision making, both as a requirement of the No Child Left Behind Act and as a normative professional standard. Issues related to accumulating, storing, and protecting data in districts and schools also are covered. Applications in administration, supervision, and teaching are demonstrated.
Preface ix
PART I Foundations of Decision Making in Schools
1(98)
Problem Solving and Decision Making in the Context of School Reform
3(22)
Chapter Focus
3(1)
Case Study
3(2)
Contemporary School Reform
5(5)
School Reform during the 1980s
5(1)
School Reform after the 1980s
6(2)
School Reform and Leadership
8(2)
Problem Solving, Decision Making, and Data-Driven Decisions
10(7)
Problem Solving
11(4)
Decision Making
15(1)
Data-Driven Decisions
16(1)
Reflective Practice
17(4)
Summary
21(1)
Questions and Suggested Activities
21(4)
Decision-Making Behavior
25(25)
Chapter Focus
25(1)
Case Study
25(1)
Understanding Educator Behavior
26(2)
Societal Variables
28(4)
Legal Requirements
28(1)
Meta-Values
28(2)
Politics
30(1)
Economics
31(1)
Organizational Variables
32(7)
School Climate and Culture
32(4)
Organizational Politics
36(1)
Threat and Risk
37(1)
Uncertainty, Ambiguity, and Conflict
38(1)
Personal Variables
39(6)
Knowledge and Skills
40(1)
Personality
41(1)
Values
41(1)
Bias
42(2)
Decision-Making Style
44(1)
Summary
45(1)
Questions and Suggested Activities
45(5)
Decision Complexity, Models, and Action Theories
50(22)
Chapter Focus
50(1)
Case Study
50(2)
Complexity and Analysis
52(4)
Decision Complexity
53(2)
Decision Analysis
55(1)
Decision-Making Models
56(10)
Classical Model
57(3)
Expected Utility Model
60(1)
Behavioral Model
60(1)
Ethical Model
61(2)
Participatory Model
63(1)
Political Model
63(1)
Garbage Can Model
64(2)
Action Theories and Reflective Practice
66(2)
Summary
68(1)
Questions and Suggested Activities
69(3)
Group Decision Making
72(27)
ChapterFocus
72(1)
Case Study
72(2)
Decision Behavior in Groups
74(4)
Social Nature of Groups
75(2)
Group Behavior and Data-Based Instructional Decisions
77(1)
Purported Advantages and Disadvantages of Groups
78(2)
Advantages
78(1)
Disadvantages
79(1)
Rationale for Using Groups
80(1)
Leading Groups
80(3)
Structuring Groups
83(4)
Effectiveness Variables
83(2)
Member Selection
85(2)
Common Problems with Groups
87(4)
Groupthink
87(1)
Absence of Trust
88(1)
Not Managing Dysfunctional Conflict
88(1)
Poor Communication
89(1)
Low Commitment
90(1)
Accountability Avoidance
90(1)
Dysfunctional Members
91(1)
Group Processes
91(2)
Nominal Technique
91(1)
Delphi Technique
92(1)
Brainstorming
92(1)
Brainwriting
93(1)
Summary
93(1)
Questions and Suggested Activities
93(6)
PART II Data-Based Decisions
99(92)
Understanding Data-Driven Decision Making
101(22)
Chapter Focus
101(1)
Case Study
101(1)
What Is Data-Based Decision Making?
102(1)
Why Is Data-Based Decision Making Important?
102(4)
How to Get Started: Asking the Right Questions
106(1)
Types of Data
107(2)
Using Data Effectively
109(2)
Connecting Data to School Improvement
111(7)
Collecting Data
111(1)
Connecting the Data
112(1)
Creating: Doing Something with the Data
113(1)
Confirming the Findings
114(4)
The School Leader's Role
118(1)
The Teacher's Role
119(1)
The Student's Role
120(1)
Summary
120(1)
Questions and Suggested Activities
121(2)
Research to Drive Education Decision Making
123(24)
Chapter Focus
123(1)
Case Study
123(1)
Role of Research in School Improvement
124(3)
Examining Current Practices
125(1)
Assessing New Materials
126(1)
Extending the Knowledge Base
126(1)
Preparing to Research Educational Practices
127(1)
Types of Research
128(14)
Quantitative (Experimental) Research
129(4)
Qualitative Research
133(1)
Descriptive Research
134(8)
Using the Research
142(2)
Summary
144(1)
Questions and Suggested Activities
145(2)
Collecting and Accessing Data
147(25)
Chapter Focus
147(1)
Case Study
147(1)
Data Sources: External
148(5)
Direct Sources
149(1)
Nondirect Sources
150(3)
Data Sources: Internal
153(6)
Direct Observation and Analysis
155(4)
Indirect Observation and Analysis
159(1)
Identifying Learning Targets
159(4)
Creating Learning Assessments
163(4)
Selected Responses
163(2)
Essay Questions
165(1)
Performance Assessment
165(1)
Personal Communication
166(1)
Personal Action Research
167(2)
Summary
169(1)
Observational Resources for Administrators
169(1)
Questions and Suggested Activities
170(2)
Technology and Information Management
172(19)
Chapter Focus
172(1)
Case Study
172(1)
Information Management Concepts
173(6)
Technology and Information Literacy
175(1)
Information Technology
176(1)
Management Information System
177(2)
Building and Using Databases
179(7)
Database Basics
180(2)
Using Spreadsheets
182(2)
Data Security and Integrity
184(1)
Data Warehousing and Mining
185(1)
Summary
186(1)
Questions and Suggested Activities
187(4)
PART III Applying Data-Based Decisions
191(70)
Curriculum and Instruction
193(26)
Chapter Focus
193(1)
Case Study I
193(2)
Case Study II
195(1)
Creating an Academic Foundation
195(1)
High-Stakes Testing: Seeing beyond the Tests
196(2)
The Standards Debate: The Movement to National Standards
198(4)
The State of State Standards
199(3)
Design of Instruction for Maximizing Results
202(10)
Principles
206(6)
Design of Assessment to Direct Student Learning
212(4)
Principles of Assessment
213(3)
Summary
216(1)
Questions and Suggested Activities
216(3)
Effective School Improvement
219(20)
Chapter Focus
219(1)
Case Study
219(2)
Effective Paradigms
221(4)
Basic Characteristics
222(1)
The PDCA Cycle
222(1)
Five School-Level Factors Model
223(2)
Fundamental Components of School Improvement Models
225(8)
Results-Driven Goals
225(1)
Data
226(1)
Data Systems
227(1)
Instruction Connected to Learning
228(2)
Professional Development
230(1)
Organizational Learning
231(1)
Collaborative Teams
232(1)
Knowing versus Doing
233(1)
School Improvement and Leadership
234(2)
Summary
236(1)
Questions and Suggested Activities
236(3)
Implementing and Monitoring Decisions
239(22)
Chapter Focus
239(1)
Case Study
239(1)
Implementing Data-Driven Decisions
240(4)
Why the Implementation Process Fails
244(3)
How to Improve the Chances of Success
247(1)
Aligning Tests with Assessing Performance
248(4)
Engaging in Inquiry to Ensure Good Decisions
252(3)
Summary
255(3)
Questions and Suggested Activities
258(3)
Index 261