Table of Contents: Reliability and Validity of International Large-Scale Assessment :

Reliability and Validity of International Large-Scale Assessment : Understanding IEA's Comparative Studies of Student Achievement.

Bibliographic Details
Main Author:	Wagemaker, Hans.
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing AG, 2020.
Edition:	1st ed.
Series:	IEA Research for Education Series
Subjects:	Electronic books.
Online Access:	Click to View

Table of Contents:

Intro
Foreword
Contents
About the Editor
1 Introduction to Reliability and Validity of International Large-Scale Assessment
1.1 Introduction
1.2 Outline of This Book
References
2 Study Design and Evolution, and the Imperatives of Reliability and Validity
2.1 Introduction
2.2 Decisions Informing the Design of IEA Studies and Test Development
2.3 Addressing the Challenges
2.3.1 Governance and Representation (Validity and Fairness)
2.3.2 Reliability and Validity
2.3.3 Changing Contexts
2.3.4 Compositional Changes
2.3.5 Financial Support
2.3.6 Expansion in Assessment Activities
2.3.7 Heterogeneity
2.3.8 Advances in Technology
2.3.9 Assessment Delivery
2.4 Conclusions
References
3 Framework Development in International Large-Scale Assessment Studies
3.1 Introduction
3.2 Assessment Frameworks
3.3 Contextual Frameworks
3.4 Design and Implementation
3.5 Steps in Framework Development
3.6 Types of Framework
3.6.1 Curriculum-Referenced Frameworks
3.6.2 Frameworks for Measuring Outcomes in Cross-Curricular Learning Areas
3.6.3 Frameworks for Measuring Real-Life Skills
3.6.4 Frameworks for Measuring Contexts
3.7 Conclusions
References
4 Assessment Content Development
4.1 Introduction
4.2 Key Features of ILSAs that Influence Assessment Content Development
4.3 Validity in International Large-Scale Assessments
4.4 The Assessment Frameworks
4.5 Stimulus Material and Item Development: Quality Criteria Associated with Validity
4.5.1 Representation of the Construct
4.5.2 Technical Quality
4.5.3 Level of Challenge
4.5.4 Absence of Bias
4.5.5 Language and Accessibility
4.5.6 Cultural and Religious Contexts
4.5.7 Engagement of Test-Takers
4.5.8 Scoring Reliability
4.6 Stimulus and Item Material: An Overview.
4.6.1 Stimulus Characteristics, Selection, and Development
4.6.2 Item Characteristics and Development
4.6.3 Item Types
4.7 Phases in the Assessment Development Process
4.7.1 Phase 1: Drafting and Sourcing Preliminary Content
4.7.2 Phase 2: Item Development
4.7.3 Phase 3: The Field Trial and Post Field Trial Review
4.7.4 Post Main Survey Test Curriculum Mapping Analysis
4.8 Measuring Change Over Time and Releasing Materials for Public Information
4.9 Conclusions
References
5 Questionnaire Development in International Large-Scale Assessment Studies
5.1 Introduction
5.2 Approaches to Questionnaire Design and Framing
5.3 Targeting of Questionnaires to Different Groups and a Diversity of Contexts
5.4 Typology of Questions, Item Formats and Resulting Indicators
5.5 Development Procedures, Process and Quality Management
5.6 Questionnaire Delivery
5.7 Conclusions
References
6 Translation: The Preparation of National Language Versions of Assessment Instruments
6.1 Introduction
6.2 Translation Related Developments in IEA Studies
6.3 Standards and Generalized Stages of Instrument Production
6.4 Source Version and Reference Version
6.4.1 Terms Used: Translation Versus Adaptation
6.4.2 Collaborative Efforts
6.5 Translation and Adaptation
6.6 Decentralized Translations and Adaptations
6.7 Centralized Verification
6.8 Translation Verifiers
6.9 Layout Verification
6.10 Development Linked to Computer-Based Assessment
6.11 Reviewing Results of Translation and Verification Processes
6.12 Procedure Chain and Timeline
6.13 Conclusions
References
7 Sampling, Weighting, and Variance Estimation
7.1 Introduction
7.2 Defining Target Populations
7.3 Preparing Valid Sampling Frames for Each Sampling Stage
7.4 Sampling Strategies and Sampling Precision.
7.4.1 Multiple Stage Sampling and Cluster Sampling
7.4.2 Stratification
7.4.3 Sampling with Probabilities Proportional to Size
7.4.4 Estimating Sampling Precision
7.5 Weighting and Nonresponse Adjustment
7.6 Sampling Adjudication
7.7 Conclusions
References
8 Quality Control During Data Collection: Refining for Rigor
8.1 Introduction
8.2 Manuals
8.2.1 Early Quality Control Procedures and the Development of Manuals
8.2.2 Current Implementation of Manuals
8.3 National Quality Control Procedures
8.3.1 Development of National Quality Control Procedures
8.3.2 Implementation of National Quality Control Procedures
8.4 International Quality Control
8.4.1 Development of International Quality Control Procedures
8.4.2 Implementation of International Quality Control Procedures
8.5 Future Directions
References
9 Post-collection Data Capture, Scoring, and Processing
9.1 Introduction
9.2 Manual Post-collection Data Capture and Management Training
9.2.1 Data Capture from Paper-Based Instruments
9.2.2 Software Used for Data Capture
9.2.3 Quality Control: Data Entry
9.3 Scoring Cognitive Data: Test Booklets
9.3.1 Process of Scoring Constructed-Response Cognitive Items
9.3.2 Software Used for Scoring Data
9.3.3 Quality Control
9.4 Coding Data
9.4.1 Process of Coding Data
9.4.2 Software Used for Coding Data
9.4.3 Quality Control
9.5 International Data Processing
9.5.1 Processes in International Data Processing
9.5.2 Software Used for International Data Processing and Analysis
9.5.3 Quality Control
9.6 Conclusions
References
10 Technology and Assessment
10.1 Introduction
10.2 Technology in Education
10.3 Promises and Successes of Technology to Reform Assessment Data Collection
10.3.1 Efficiency.
10.3.2 Increased Reliability: Direct Data Capture
10.3.3 Inclusion of More Comprehensive Measures of the Overall Construct
10.3.4 Reading: Additional Competencies Needed in the Information Age
10.3.5 Mathematics and Science: Inclusion of Innovative Problem-Solving Strategies
10.3.6 Computational Thinking: Developing Algorithmic Solutions
10.3.7 Increased Reliability: Use of Log-File Data
10.3.8 Development of More Engaging and Better Matching Assessments
10.4 The Transition
10.4.1 Delivering Questionnaires Online
10.4.2 Computer-Based Assessment
10.5 Challenges
10.6 The Future: Guiding Principles for the Design of an EAssessment Software
10.6.1 Adaptive Testing
10.6.2 Translation
10.6.3 Printing
10.6.4 Web-Based Delivery
10.6.5 General Considerations
10.7 Conclusions
References
11 Ensuring Validity in International Comparisons Using State-of-the-Art Psychometric Methodologies
11.1 Introduction
11.2 Modern Educational Measurement: Item Response Theory
11.2.1 From Chess Ranking to the Rasch Model
11.2.2 Characteristics of the Rasch Model
11.2.3 More General IRT Models
11.2.4 Central Assumptions of IRT and Their Importance
11.2.5 Unidimensionality
11.2.6 Local Independence
11.2.7 Population Homogeneity/ Measurement Invariance
11.3 Simultaneous Modeling of Individual and Group Differences
11.4 Statistical Modeling of Individual and Group Differences in IEA Survey Data
11.4.1 Comparability as Generalized Measurement Invariance
11.4.2 Multiple-Group IRT Models
11.4.3 Population Models Integrating Test and Background Data
11.4.4 Group Ability Distributions and Plausible Values
11.5 Conclusions
References
12 Publications and Dissemination
12.1 Introduction
12.2 Core Project Publications
12.3 Project-Related Publications.
12.4 Academic Journal
12.5 IEA International Research Conference (IRC)
12.6 IEA Compass Briefs
12.7 Quality Assurance in Publications
12.8 Public Dissemination of IEA's Work
12.9 Conclusions
References
13 Consequential Validity: Data Access, Data Use, Analytical Support, and Training
13.1 Introduction
13.2 Data Access
13.3 Facilitating Analysis: The IEA IDB Analyzer
13.4 Capacity Building: Workshops
13.4.1 Promoting High-Quality Research Based on Large-Scale Assessment Data
13.4.2 The IEA-ETS Research Institute (IERI)
13.4.3 IEA International Research Conference
13.4.4 Academic Visitors/Scholars
13.4.5 IEA Awards
13.5 Conclusions
References
14 Using IEA Studies to Inform Policymaking and Program Development: The Case of Singapore
14.1 Introduction
14.2 Why Singapore Participates in International Large-Scale Assessments
14.2.1 Participating in International Large-Scale Assessment Facilitates Benchmarking of Student Developmental Outcomes and Educator Practices
14.2.2 Participating in International Large-Scale Assessment Provides Additional High-Quality Rich Data Sources for Secondary Analyses
14.2.3 Participating in International Large-Scale Assessment Builds International Networks of Educationists and Experts
14.3 How MOE Has Used Large-Scale Assessment Data
14.3.1 STELLAR: "We Must and Can Do Better!"
14.3.2 A New Pedagogical Approach to Learning Science: "We Tried a Different Method, Did It Materialize?"
14.3.3 Bold Curricular and Pedagogical Shifts: "We Made Some Trade-Offs, What Did We Sacrifice?"
14.4 Some Principles Underpinning MOE's Use of Large-Scale Assessment Data
References
15 Understanding the Policy Influence of International Large-Scale Assessments in Education
15.1 Introduction
15.2 Impact, Influence, and Education Policy.
15.3 Policy Influence?.

Reliability and Validity of International Large-Scale Assessment : Understanding IEA's Comparative Studies of Student Achievement.

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