Archives

• Item Selection Rules for Content Adaptive Progress Testing

  Vol. 13 No. 2 (2026)

  Content adaptive progress testing (CAPT) introduces a new approach to longitudinal testing of candidates who take progress tests as part of their educational program. CAPT assessments adapt between subsequent assessments, tailoring items on an individual level to assist each candidate in demonstrating knowledge across many topics which are all mapped to the overall course learning outcomes. In this way, success is measured by topic completion on an individual level. Some of the key benefits include a truly personalized learning experience, with individual feedback throughout, while also tracking each candidate’s progress against a single long-term goal of demonstrating attainment across all required topics. For the learning experience to be personalized, there needs to be automatic software selection of different items for each candidate based on their performance across a sequence of assessments. The advantages, disadvantages and practical implementation of different item selection rules are discussed. There is a need to ensure that no item is repeated to the same candidate in any test: No two items in the same test belong to the same topic for the same candidate, a minimum number of topics per broader area are administered in every assessment, and selection of incomplete topics is prioritized over complete topics. These rules need to be clear and transparent to motivate appropriate learning.

• Optimizing Test Completion in Time-Constrained Adaptive Tests: A Post-Hoc Simulation Study

  Vol. 13 No. 1 (2026)

• Estimating the Joint Item-Score Density Using an Unrestricted Latent Class Model: Advancing Flexibility in Computerized Adaptive Testing

  Vol. 12 No. 3 (2025)

• Stochastic Curtailment: A New Approach to Improve Efficiency of Variable-Length Computerized Adaptive Tests

  Vol. 12 No. 4 (2025)

• Estimating the Joint Item-Score Density Using an Unrestricted Latent Class Model: Advancing Flexibility in Computerized Adaptive Testing

  Vol. 12 No. 3 (2025)

• A Score-Based Method for Detecting Item Compromise and Preknowledge in Computerized Adaptive Testing

  Vol. 12 No. 2 (2025)

  In recent years, several methods have been proposed to detect compromised items (CI) and examinees with preknowledge (EWP) simultaneously. However, most of these methods are limited in one of two ways: (1) The method was specifically designed for non-adaptive tests and might therefore not be suitable for adaptive tests, or (2) the method involves the analysis of more than just the item scores. In this paper, a new method is developed for computerized adaptive tests that requires only an analysis of the item scores. The perfor-mance of the method is evaluated using simulations in which several factors are manip-ulated, such as test length, the percentage of CI, the percentage of EWP, and EWP ability distribution. Across most conditions, the method is shown to produce reasonable false positive rates and favorable true positive rates for both items and examinees.

• Special Issue: Through-Year Assessments: Advancements and Implications for Hybrid Interim-Summative Testing

  Vol. 12 No. 1 (2025)

• Evaluating the Effectiveness of the Standard Error of Score Estimation as a CAT Termination Criterion

  Vol. 11 No. 2 (2024)

• The Influence of Computerized Adaptive Testing on Psychometric Theory and Practice

  Vol. 11 No. 1 (2024)

  The major premise of this article is that part of the stimulus for the evolution of psychometric theory since the 1950s was the introduction of the concept of computerized adaptive testing (CAT) or its earlier non-CAT variations. The conceptual underpinnings of CAT that had the most influence on psychometric theory was the shift of emphasis from the test (or test score) as the focus of analysis to the test item (or item score). The change in focus allowed a change in the way that test results are conceived of as measurements. It also resolved the conflict among a number of ideas that were present in the early work on psychometric theory. Some of the conflicting ideas are summarized below to show how work on the development of CAT resolved some of those conflicts.

• How Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?

  Vol. 10 No. 3 (2023)

• Expanding the Meaning of Adaptive Testing to Enhance Validity

  Vol. 10 No. 2 (2023)

• An Extended Taxonomy of Variants of Computerized Adaptive Testing

  Vol. 10 No. 1 (2023)

• The (non)Impact of Misfitting Items in Computerized Adaptive Testing

  Vol. 9 No. 2 (2022)

• Improving Precision of CAT Measures

  Vol. 9 No. 1 (2022)

  This paper was the author’s presidential address at the 2015 conference of the International Association for Computerized Adaptive Testing.

• Three Measures of Test Adaptation Based on Optimal Test Information

  Vol. 8 No. 1 (2020)

• Time-Efficient Adaptive Measurement of Change

  Vol. 7 No. 2 (2019)

• How Adaptive Is an Adaptive Test: Are All Adaptive Tests Adaptive?

  Vol. 7 No. 1 (2019)

• Implementing Three CATs Within Eighteen Months

  Vol. 6 No. 3 (2018)

• Adaptive Item Selection Under Matroid Constraints

  Vol. 6 No. 2 (2018)

• Factors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test

  Vol. 6 No. 1 (2018)

• Latent-Class-Based Item Selection for Computerized Adaptive Progress Tests

  Vol. 5 No. 2 (2017)

• Uniform Test Assembly: Concepts, Problems, Solvers, and Applications for Adaptive Testing

  Vol. 5 No. 1 (2017)

• Effect of Imprecise Parameter Estimates on Ability Estimates in a Multistage Test in an Automatic Item Generation Context

  Vol. 4 No. 1 (2016)

• Implementing a CAT: The AMC experience

  Vol. 3 No. 1 (2015)

• Vol. 2 No. 1-4 (2014)

• Vol. 1 No. 1-5 (2014)