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Description
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex performance assessment within a digital-simulation

This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex performance assessment within a digital-simulation educational context grounded in theories of cognition and learning. BN models were manipulated along two factors: latent variable dependency structure and number of latent classes. Distributions of posterior predicted p-values (PPP-values) served as the primary outcome measure and were summarized in graphical presentations, by median values across replications, and by proportions of replications in which the PPP-values were extreme. An effect size measure for PPMC was introduced as a supplemental numerical summary to the PPP-value. Consistent with previous PPMC research, all investigated fit functions tended to perform conservatively, but Standardized Generalized Dimensionality Discrepancy Measure (SGDDM), Yen's Q3, and Hierarchy Consistency Index (HCI) only mildly so. Adequate power to detect at least some types of misfit was demonstrated by SGDDM, Q3, HCI, Item Consistency Index (ICI), and to a lesser extent Deviance, while proportion correct (PC), a chi-square-type item-fit measure, Ranked Probability Score (RPS), and Good's Logarithmic Scale (GLS) were powerless across all investigated factors. Bivariate SGDDM and Q3 were found to provide powerful and detailed feedback for all investigated types of misfit.
ContributorsCrawford, Aaron (Author) / Levy, Roy (Thesis advisor) / Green, Samuel (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Institutions of higher education often tout that they are developing students to become lifelong learners. Evaluative efforts in this area have been presumably hindered by the lack of a uniform conceptualization of lifelong learning. Lifelong learning has been defined from institutional, economic, socio-cultural, and pedagogical perspectives, among others. This study

Institutions of higher education often tout that they are developing students to become lifelong learners. Evaluative efforts in this area have been presumably hindered by the lack of a uniform conceptualization of lifelong learning. Lifelong learning has been defined from institutional, economic, socio-cultural, and pedagogical perspectives, among others. This study presents the existing operational definitions and theories of lifelong learning in the context of higher education and synthesizes them to propose a unified model of college students' orientation toward lifelong learning. The model theorizes that orientation toward lifelong learning is a latent construct which manifests as students' likelihood to engage in four types of learning activities: formal work-related activities, informal work-related activities, formal personal interest activities, and informal personal interest activities. The Postsecondary Orientation toward Lifelong Learning scale (POLL) was developed and the validity of the resulting score interpretations was examined. The instrument was used to compare potential differences in orientation toward lifelong learning between freshmen and seniors. Exploratory factor analyses of the responses of 138 undergraduate college students in the pilot study data provided tentative support for the factor structure within each type of learning activity. Guttman's <λ>λ2 estimates of the learning activity subscales ranged from .78 to .85. Follow-up confirmatory factor analysis using structural equation modeling did not corroborate support for the hypothesized four-factor model using the main student sample data of 405 undergraduate students. Several alternative reflective factor structures were explored. A two-factor model representing factors for Instructing/Presenting and Reading learning activities produced marginal model-data fit and warrants further investigation. The summed POLL total scores had a relatively strong positive correlation with global interest in learning (.58), moderate positive correlations with civic engagement and participation (.38) and life satisfaction (.29), and a small positive correlation with social desirability (.15). The results of the main study do not provide support for the malleability of postsecondary students' orientation toward lifelong learning, as measured by the summed POLL scores. The difference between freshmen and seniors' average total POLL scores was not statistically significant and was negligible in size.
ContributorsArcuria, Phil (Author) / Thompson, Marilyn (Thesis advisor) / Green, Samuel (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2011
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Description

Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.

ContributorsAnand, Rohan (Co-author) / Dicke, George (Co-author) / Stephens, Corey (Co-author) / Sadusky, Brian (Thesis director) / Schiller, Christoph (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.

ContributorsDicke, George (Co-author) / Anand, Rohan (Co-author) / Stephens, Corey (Co-author) / Sadusky, Brian (Thesis director) / Schiller, Christoph (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
The use of exams for classification purposes has become prevalent across many fields including professional assessment for employment screening and standards based testing in educational settings. Classification exams assign individuals to performance groups based on the comparison of their observed test scores to a pre-selected criterion (e.g. masters vs. nonmasters

The use of exams for classification purposes has become prevalent across many fields including professional assessment for employment screening and standards based testing in educational settings. Classification exams assign individuals to performance groups based on the comparison of their observed test scores to a pre-selected criterion (e.g. masters vs. nonmasters in dichotomous classification scenarios). The successful use of exams for classification purposes assumes at least minimal levels of accuracy of these classifications. Classification accuracy is an index that reflects the rate of correct classification of individuals into the same category which contains their true ability score. Traditional methods estimate classification accuracy via methods which assume that true scores follow a four-parameter beta-binomial distribution. Recent research suggests that Item Response Theory may be a preferable alternative framework for estimating examinees' true scores and may return more accurate classifications based on these scores. Researchers hypothesized that test length, the location of the cut score, the distribution of items, and the distribution of examinee ability would impact the recovery of accurate estimates of classification accuracy. The current simulation study manipulated these factors to assess their potential influence on classification accuracy. Observed classification as masters vs. nonmasters, true classification accuracy, estimated classification accuracy, BIAS, and RMSE were analyzed. In addition, Analysis of Variance tests were conducted to determine whether an interrelationship existed between levels of the four manipulated factors. Results showed small values of estimated classification accuracy and increased BIAS in accuracy estimates with few items, mismatched distributions of item difficulty and examinee ability, and extreme cut scores. A significant four-way interaction between manipulated variables was observed. In additional to interpretations of these findings and explanation of potential causes for the recovered values, recommendations that inform practice and avenues of future research are provided.
ContributorsKunze, Katie (Author) / Gorin, Joanna (Thesis advisor) / Levy, Roy (Thesis advisor) / Green, Samuel (Committee member) / Arizona State University (Publisher)
Created2013