The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…

Frontal lobe patients reproduced a sequence of capital letters or abstract shapes. Immediate and delayed reproduction trials allowed the analysis of short- and long-term memory for time order by means of suitable Markov chain stochastic models. Patients were as proficient as healthy subjects on the immediate reproduction trial, thus showing spared…

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…

A lognormal model for the response times of a person on a set of test items is investigated. The model has a parameter structure analogous to the two-parameter logistic response models in item response theory, with a parameter for the speed of each person as well as parameters for the time intensity and discriminating power of each item. It is…

This paper explores the application of a technique for hierarchical item response theory (IRT) calibration of complex constructed response tasks that has promise both as a calibration tool and as a means of evaluating the isomorphic equivalence of complex constructed response tasks. Isomorphic tasks are explicitly and rigorously designed to be…

Reviews the performance of computer programs for writing poetry and prose, including MARK V. SHANEY, MELL, POETRY GENERATOR, THUNDER THOUGHT, and ORPHEUS. Discusses the writing principles of the programs. Provides additional information on computer magnification techniques. (YP)

This paper provides a method for analyzing data consisting of event sequences and covariate observations associated with Markov chains. The objective is to use the covariate data to explain differences between individuals in the transition probability matrices characterizing their sequential data. (TJH)

In 2 eye-movement experiments, the authors tested whether transitional probability (the statistical likelihood that a word precedes or follows another word) affects reading times and whether this occurs independently from contextual predictability effects. Experiment 1 showed early effects of predictability, replicating S. A. McDonald and R. C.…

It is high time for Indian universities to transform themselves from sellers to marketers, though they are non-profit organizations, in marketing their degrees to its customers (students). In this direction e-learning could be one of the tools that helps achieve this objective. The authors in this survey-based article studied the consumers'…

Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…

The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…

Probability theory can be developed from a theoretical or experimental probability approach. The problem, "The Gambler's Ruin," is used to study whether students are naturally sensitive to learning probability from an experimental probability approach through simulations. Results indicated that use of simulations can contribute to…

A hierarchical latent regression model is suggested to estimate nested and nonnested relationships in complex samples such as found in the National Assessment of Educational Progress (NAEP). The proposed model aims at improving both parameters and variance estimates via a two-level hierarchical linear model. This model falls naturally within the…

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

This study used Markov chain matrices to simulate the effect of varying degrees of change in student characteristics on retention and graduation rates. Data were applied to a 1-year enrollment transition matrix that tracks how students of each class level progress into the same or higher class levels, to a completed degree, or to non-returning…