Table of Contents: Theoretical and Practical Advances in Computer-Based Educational Measurement.

Theoretical and Practical Advances in Computer-Based Educational Measurement.

Bibliographic Details
Main Author:	Veldkamp, Bernard P.
Other Authors:	Sluijter, Cor.
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing AG, 2019.
Edition:	1st ed.
Series:	Methodology of Educational Measurement and Assessment Series
Subjects:	Electronic books.
Online Access:	Click to View

Table of Contents:

Intro
Preface
Introduction
Contents
Improving Test Quality
1 The Validity of Technology Enhanced Assessments-Threats and Opportunities
1.1 Introduction
1.2 Innovations in Technology-Enhanced Assessments
1.2.1 Innovations in Items and Tasks
1.2.2 Innovations in Test Construction, Assembly and Delivery
1.2.3 Innovations Regarding Personal Needs and Preferences
1.3 Validity and Validation
1.4 Validity of Innovative Technology-Enhanced Assessments
1.4.1 Inferences Within the IUA
1.4.2 Validity Argument of Technology-Enhanced Assessments
1.5 Concluding Remarks
References
2 A Framework for Improving the Accessibility of Assessment Tasks
2.1 Accessibility of Assessments
2.2 Principles that Underlie Accessible Assessment Design
2.2.1 Principles from Universal Design
2.2.2 Principles from Cognitive Load Theory
2.3 Evaluating and Improving Accessibility of Assessment Tasks from a Test Takers' Perspective
2.3.1 Supporting Orientation by a Clear Assignment
2.3.2 Supporting Information Processing and Devising Solutions
2.3.3 Facilitating Responding
2.3.4 Facilitating Monitoring and Adjusting
2.4 An Application of the Test Accessibility Framework: The Dutch Driving Theory Exam
2.4.1 Innovations in the Dutch Traffic Theory Exam for Car Drivers
2.4.2 Applied Modifications in the Response Mode of Theory Items
2.4.3 Psychometric Indications of Accessibility Improvement?
2.4.4 Item Selection
2.4.5 Data Collection
2.4.6 Data Analyses
2.4.7 Results
2.5 Discussion
References
3 The Design and Validation of the Renewed Systems-Oriented Talent Management Model
3.1 Introduction
3.1.1 Problem Situation and Purpose of the Study
3.2 Theoretical Framework
3.2.1 The Management Building Blocks Framework
3.2.2 Systems Theory.
3.2.3 Evidence-Based Systems-Oriented Talent Management
3.3 Renewed STM Diagrams
3.3.1 Renewed STM Diagram 1: Aligning Organisational Structure and Human Talent
3.3.2 Renewed STM Diagram 2: Aligning Organisational Culture and Human Talent
3.3.3 Renewed STM Diagram 3: Aligning Business Strategy and Human Talent
3.4 Implications of the STM for Educational Measurement
3.5 Conclusion, Limitations, and Recommendations
3.5.1 Conclusion
3.5.2 Application to Educational Measurement
3.5.3 Limitations
3.5.4 Recommendations and Implications
References
4 Assessing Computer-Based Assessments
4.1 Introduction
4.2 The RCEC Review System for the Evaluation of Computer-Based Tests
4.2.1 Purpose and Use of the Educational Test or Exam
4.2.2 Quality of Test Material
4.2.3 Representativeness
4.2.4 Reliability
4.2.5 Standard Setting and Standard Maintenance
4.2.6 Test Administration and Security
4.3 Reviewing a Computer Based Test
4.3.1 Purpose and Use of the Test
4.3.2 Quality of Test Material
4.3.3 Representativeness
4.3.4 Reliability (Measurement Precision)
4.3.5 Standard Setting and Standard Maintenance
4.3.6 Test Administration and Security
4.3.7 Review Conclusion
4.4 Discussion
References
Psychometrics
5 Network Psychometrics in Educational Practice
5.1 Introduction
5.2 The Curie-Weiss Model
5.2.1 Some Statistical Properties of the Curie-Weiss Model
5.2.2 The Curie-Weiss to Rasch Connection
5.3 Maximum Likelihood Estimation of the Curie-Weiss Model
5.3.1 Maximum Likelihood in the Complete Data Case
5.3.2 Maximum Likelihood Estimation in the Incomplete Data Case
5.3.3 The M-Step
5.4 Numerical Illustrations
5.4.1 Simulated Example
5.4.2 The Cito Eindtoets 2012
5.5 Discussion
References.
6 On the Number of Items in Testing Mastery of Learning Objectives
6.1 Introduction
6.2 Method
6.2.1 Simulation Study with Homogeneous Item Characteristics
6.2.2 Empirical Example
6.2.3 Simulation Study Based on Empirical Data and Heterogeneous Item Characteristics
6.2.4 Estimating and Validating a Predictive Model for Bayes Factors
6.3 Results
6.3.1 Simulation Study with Homogeneous Item Characteristics
6.3.2 Empirical Example
6.3.3 Simulation Based on the Empirical Data and with Heterogeneous Item Characteristics
6.3.4 Prediction Model
6.4 Discussion and Conclusions
References
7 Exponential Family Models for Continuous Responses
7.1 Introduction
7.2 A Rasch Model for Continuous Responses
7.2.1 The Model
7.2.2 Parameter Estimation
7.3 An Extension of the Müller Model
7.3.1 The Model
7.3.2 Parameter Estimation
7.4 Comparison of Information Functions Across Models
7.4.1 The Unit of the Latent Variable
7.4.2 An Example
7.5 Discussion
Appendix
References
8 Tracking Ability: Defining Trackers for Measuring Educational Progress
8.1 Introduction
8.2 Methods
8.2.1 Formalizing a Tracker
8.2.2 Example of a Tracker
8.2.3 Convergence in Kullback-Leibler Divergence
8.2.4 Simulating Surveys
8.3 Discussion
References
9 Finding Equivalent Standards in Small Samples
9.1 Introduction
9.2 Method
9.3 Results
9.4 Conclusion and Discussion
References
Large Scale Assessments
10 Clustering Behavioral Patterns Using Process Data in PIAAC Problem-Solving Items
10.1 Introduction
10.1.1 Problem-Solving Items in PIAAC
10.1.2 Employability and PSTRE Skills
10.2 Method
10.2.1 Sample
10.2.2 Instrumentation
10.2.3 Features Extracted from Process Data
10.2.4 Clustering Sequence Data
10.2.5 K-Means Clustering
10.3 Results.
10.3.1 Cluster Determination
10.3.2 Cluster Membership and Proficiency Level
10.3.3 Cluster Membership and Employment-Based Background Variables
10.4 Discussion
References
11 Reliability Issues in High-Stakes Educational Tests
11.1 Outline of the Problem
11.2 Preliminaries
11.3 MAP Proficiency Estimates Based on Number-Correct Scores
11.4 Equating Error
11.5 Simulation Study of Equating Errors
11.6 Conclusion
References
12 Differential Item Functioning in PISA Due to Mode Effects
12.1 Introduction
12.2 Changes in PISA 2015
12.3 Data
12.4 Differential Item Functioning
12.5 Results
12.5.1 DIF Between Modes
12.5.2 Trend Effects in the Netherlands
12.6 Conclusions and Discussion
References
13 Investigating Rater Effects in International Large-Scale Assessments
13.1 Introduction
13.2 Scoring Human-Coded Items in PISA 2015
13.2.1 Categorization of Items by Item Formats
13.2.2 Coding Design and Procedures
13.3 Construct Equivalence of Different Scoring Types in PISA
13.3.1 Methods
13.3.2 Findings
13.4 Rater Effects that Are Comparable Across Countries
13.4.1 Methods
13.4.2 Findings
13.5 Conclusion
References
Computerized Adaptive Testing in Educational Measurement
14 Multidimensional Computerized Adaptive Testing for Classifying Examinees
14.1 Introduction
14.2 Multidimensional Item Response Theory
14.3 Classification Methods
14.3.1 The SPRT for Between-Item Multidimensionality
14.3.2 The Confidence Interval Method for Between-Item Multidimensionality
14.3.3 The SPRT for Within-Item Multidimensionality
14.3.4 The Confidence Interval Method for Within-Item Multidimensionality
14.4 Item Selection Methods
14.4.1 Item Selection Methods for Between-Item Multidimensionality.
14.4.2 Item Selection Methods for Within-Item Multidimensionality
14.5 Examples
14.5.1 Example 1: Between-Item Multidimensionality
14.5.2 Example 2: Within-Item Multidimensionality
14.6 Conclusions and Discussion
References
15 Robust Computerized Adaptive Testing
15.1 Introduction
15.2 Robust Test Assembly
15.3 Robust CAT Assembly
15.3.1 Constructing a Robust Item Pool
15.3.2 Numerical Example to Illustrate the Concept of Robust Item Pools
15.3.3 Towards an Algorithm for Robust CAT
15.4 Simulation Studies
15.4.1 Study 1
15.4.2 Study 2
15.4.3 Study 3
15.4.4 Study Setup
15.5 Results
15.6 Conclusion
References
16 On-the-Fly Calibration in Computerized Adaptive Testing
16.1 Introduction
16.1.1 Replenishment Strategies and On-the-Fly Calibration
16.1.2 On-the-Fly Calibration Methods
16.1.3 The Use of Reference Items in Modelling Bias
16.1.4 The Need for Underexposure Control
16.1.5 A Combination of Calibration Methods
16.2 Research Questions
16.3 Simulation Studies
16.3.1 Use of Reference Items in Elimination of Bias
16.3.2 Comparison of the Methods
16.4 Discussion
References
17 Reinforcement Learning Applied to Adaptive Classification Testing
17.1 Introduction
17.2 Method
17.3 Framework
17.3.1 General Idea
17.3.2 Sequential Classification
17.3.3 Item Selection
17.3.4 Algorithm
17.4 Experiments
17.5 Discussion
References
Technological Developments in Educational Measurement
18 Feasibility and Value of Using a GoPro Camera and iPad to Study Teacher-Student Assessment Feedback Interactions
18.1 Introduction
18.1.1 The Value of Video Feedback
18.2 Method
18.2.1 Participants and Context
18.2.2 Data Collection Instruments and Procedures
18.2.3 Analysis
18.3 Results
18.3.1 Technical Results.
18.3.2 Teacher and Student Experiences.

Theoretical and Practical Advances in Computer-Based Educational Measurement.

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