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Team-Based Learning's Effects on Standardized Test Scores and Student Reactions
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Ulrich, Deborah L.; Brewer, Tracy; Steele-Johnson, Deborah; Juvina, Ion; Peyton, Elizabeth; Hammond, Crystal – Journal on Excellence in College Teaching, 2017
We examined the effects of team-based learning (TBL) versus traditional and enhanced lecture-based instruction over time (Study 1; N = 532 nursing students) and the psychometric properties of the Team Based Learning Student Assessment Instrument (TBL-SAI), a popular measure of reactions to TBL (Study 2; N = 323 nursing and medical students).…
Descriptors: Teaching Methods, Teamwork, Lecture Method, Conventional Instruction
Recovery of Graded Response Model Parameters: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation
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Kieftenbeld, Vincent; Natesan, Prathiba – Applied Psychological Measurement, 2012
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
Descriptors: Test Length, Markov Processes, Item Response Theory, Monte Carlo Methods
Estimation of the Correlation Coefficient Based on Selected Data
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Hagglund, Gosta; Larsson, Rolf – Journal of Educational and Behavioral Statistics, 2006
In psychometrics, it is often the case that one encounters data that may not be considered random but selected in a systematic way according to some explanatory variable. In this article, maximum likelihood estimation is considered when data are supposed to arise from a bivariate normal distribution that is truncated in an extreme way. Two methods…
Descriptors: Psychometrics, Correlation, Computation, Methods
Noniterative Estimation and the Choice of the Number of Factors in Exploratory Factor Analysis.
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Kano, Yutaka – Psychometrika, 1990
Based on the usual factor analysis model, this paper investigates the relationship between improper solutions and the number of factors. The properties of the noniterative estimation method of M. Ihara and Y. Kano in exploratory factor analysis are also discussed. The estimators were compared in a Monte Carlo experiment. (TJH)
Descriptors: Comparative Analysis, Estimation (Mathematics), Factor Analysis, Mathematical Models
Additive and Multiplicative Models for Gamma Distributed Random Variables, and Their Application as Psychometric Models for Response Times.
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Maris, Eric – Psychometrika, 1993
A class of models is presented for gamma distributed random variables. These additive, multiplicative, and combined additive-multiplicative models are more flexible than classical linear models with respect to the structure that can be imposed on expected values. As a special case, a class of psychometric models for reaction times is presented.…
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Logistic Achievement Test Scaling and Equating with Fixed versus Estimated Lower Asymptotes.
Phillips, S. E. – 1983
This study compared the lower asymptotes estimated by the maximum likelihood procedures of the LOGIST computer program with those obtained via application of the Norton methodology. The study also compared the equating results from the three-parameter logistic model with those obtained from the equipercentile, Rasch, and conditional…
Descriptors: Achievement Tests, Comparative Analysis, Equated Scores, Estimation (Mathematics)