Adaptive testing

Nathan Thompson earned his PhD in Psychometrics from the University of Minnesota, with a focus on computerized adaptive testing. His undergraduate degree was from Luther College with a triple major of Mathematics, Psychology, and Latin. He is primarily interested in the use of AI and software automation to augment and replace the work done by psychometricians, which has provided extensive experience in software design and programming. Dr. Thompson has published over 100 journal articles and conference presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/ .
computerized adaptive testing
Adaptive testingPsychometrics

Computerized Adaptive Testing (CAT): An Introduction

Computerized adaptive testing is an AI-based approach to assessment where the test is personalized based on your performance as you take the test, making the test shorter, more accurate, more secure, more engaging, and fairer. 

Multistage testing algorithm
Adaptive testingEducationPsychometrics

Multistage Testing

Multistage testing (MST) is a type of computerized adaptive testing (CAT).  This means it is an exam delivered on computers which dynamically personalize it for each examinee or student.  Typically, this is done with respect

Multistage testing algorithm
Adaptive testingAssessment In The News

Adaptive Testing SAT: Intro & Free Practice Test

The adaptive SAT (Scholastic Aptitude Test) exam was announced in January 2022 by the College Board, with the goal to modernize the test and make it more widely available, migrating the exam from paper-and-pencil to

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Adaptive testingPsychometricsTest Development

Three Approaches for IRT Equating

If you are delivering high-stakes tests in linear forms – or piloting a bank for CAT/LOFT – you are faced with the issue of how to equate the forms together.  That is, how can we

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Adaptive testingEducationPsychometricsTest DevelopmentTest Security

Paper-and-Pencil Testing: Still Around?

Paper-and-pencil testing used to be the only way to deliver assessments at scale.  The introduction of computer-based testing (CBT) in the 1980s was a revelation – higher fidelity item types, immediate scoring & feedback, and

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Adaptive testing

MICROCAT: What was assessment like in the 1980s?

ASC has been empowering organizations to develop better assessments since 1979.  Curious as to how things were back then?  Below is a copy of our newsletter from 1988, long before the days of sharing news

automated item generation AI
Adaptive testingPsychometrics

Monte Carlo simulation in adaptive testing

Simulation studies are an essential step in the development of a computerized adaptive test (CAT) that is defensible and meets the needs of your organization or other stakeholders. There are three types of simulations: Monte

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Adaptive testingEducationPsychometrics

What is the Sympson-Hetter Item Exposure Control?

Sympson-Hetter is a method of item exposure control within the algorithm of Computerized adaptive testing (CAT).  It prevents the algorithm from over-using the best items in the pool. CAT is a powerful paradigm for delivering tests

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Adaptive testingPsychometrics

Machine Learning in Psychometrics: Old News?

In the past decade, terms like machine learning, artificial intelligence, and data mining are becoming greater buzzwords as computing power, APIs, and the massively increased availability of data enable new technologies like self-driving cars. However, we’ve