The appeal of a shorter testing time makes a computer adaptive testing approach highly desirable for use in multiple assessment and learning contexts. However, for those who have been tasked with designing, configuring, and deploying adaptive tests for operational use at scale, preparing an adaptive test is anything but simple. The process often…

Many recent studies have looked at the viability of applying recurrent neural networks (RNNs) to educational data. In most cases, this is done by comparing their performance to existing models in the artificial intelligence in education (AIED) and educational data mining (EDM) fields. While there is increasing evidence that, in many situations,…

A large-scale simulation study of the assessment effectiveness of a particular instantiation of knowledge space theory is described. In this study, data from more than 700,000 actual assessments in mathematics using the ALEKS (Assessment and LEarning in Knowledge Spaces) software were used to determine response probabilities for the same number of…

While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing)…

This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods--including classical test theory, item response theory, and computer adaptive testing--and integrates them with multidimensional student models used by intelligent educational systems.…