This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item…

In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…

This paper describes how item response theory (IRT) methods of test-equating could be applied to the maintenance of public examination standards in England. IRT methods of test-equating have been sparingly applied to the main public examinations in England, namely the General Certificate of Secondary Education (GCSE), the equivalent of a school…

An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

A Bayesian alternative to interpretations based on classical reliability theory is presented. Procedures are detailed for calculation of a posterior score and credible interval with joint consideration of item sample and occasion error. (Author/SLD)

This proposal attempts to follow in Allan Birnbaum's tradition by using Bayesian ideas to show that his mental test model possesses even broader applicability than previously realized. Birnbaum's two significant contributions to the theories of statistics and educational testing are: (1) the proof that the sufficiency and conditionality principles…

A general framework for making mastery/nonmastery decisions based on multivariate test data is described in this study. Over all, mastery is granted (or denied) if the posterior expected loss associated with such action is smaller than the one incurred by the denial (or grant) of mastery. An explicit form for the cutting contour which separates…

In an invitational address to the Victorian Institute of Educational Research, the author discussed Bayesian theory and its relationship to the design and construction of tailored or adaptive tests. Bayesian thinking involves recognizing the role of prior probabilities and using these probabilities in combination with new data to arrive at future…

Relationships between Bayesian ability estimates and the parameters of a normal population distribution are derived in the context of classical test theory. Analogies are provided for use as approximations in work with item response theory (IRT). The following issues are addressed: (1) the relationship between the distribution of the latent…

Some applications of Bayesian decision theory to intelligent tutoring systems are considered. How the problem of adapting the appropriate amount of instruction to the changing nature of a student's capabilities during the learning process can be situated in the general framework of Bayesian decision theory is discussed in the context of the…

Relationships between Bayesian ability estimates and the parameters of a normal population distribution are derived in the context of classical test theory. Formulas are presented for practical work with Bayesian ability estimates, and a numerical illustration is provided. (SLD)

Educational assessments that exploit advances in technology and cognitive psychology can produce observations and pose student models that outstrip familiar test-theoretic models and analytic methods. Bayesian inference networks (BINs), which include familiar models and techniques as special cases, can be used to manage belief about students'…

An alternative to the Rasch model is introduced. It characterizes strength of response according to the ratio of ability and difficulty parameters rather than their difference. Joint estimation and marginal estimation models are applied to two test data sets. (SLD)

Educational assessment concerns inference about student knowledge, skills, and accomplishments. Test theory has evolved in part to address questions of weight, coverage, and import of data. Resulting concepts and techniques can be viewed as applications of more general principles for inference in the presence of uncertainty. (SLD)

Diagnostic testing confronts several challenges at once, among which are issues of test interpretation and immediate modification of the test itself in response to the interpretation. Several methods are available for administering and evaluating a test in real-time, towards optimizing the examiner's chances of isolating a persistent pattern of…