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Engagement And Development Of Professional Skills Among Low-Income, High-Achieving Students: A Structural Equation Model, Nasser Alresaini Jan 2021

Engagement And Development Of Professional Skills Among Low-Income, High-Achieving Students: A Structural Equation Model, Nasser Alresaini

Electronic Theses and Dissertations

This dissertation tested the effect of academic engagement and social engagement on developing soft professional skills for low-income, high-achieving students in higher education. Using the publicly available data of GMS scholarship, the analysis was consisted of EFA and SEM. The general effect model gave a general idea about the tested population, whereas the conditional model highlighted the groups' specific significance. Low-income, high-achieving students continued their academic and social engagement growth during their school years. Academic engagement positively enhanced students' soft professional skills for students who did not receive the GMS scholarship, students from educated and uneducated parents, Asian and Hispanic …


A Comparison Of Bayesian Estimation Techniques In A Multidimensional Two-Parameter Partial Credit Item Response Model, Peiyan Liu Jan 2019

A Comparison Of Bayesian Estimation Techniques In A Multidimensional Two-Parameter Partial Credit Item Response Model, Peiyan Liu

Electronic Theses and Dissertations

Bayesian estimation methods have shown better performance than the traditional Marginal Maximum Likelihood (MML) estimation method for parameter estimation in relatively simple item response models. However, extant literature is lacking on the investigation of Bayesian parameter estimation approaches for a multidimensional two parameter partial credit (M2PPC) model, therefore this simulation study investigated the performance of two Bayesian Markov Chain Monte Carlo (MCMC) algorithms: Gibbs Sampler and Hamiltonian Monte Carlo-No-U-Turn-Sampler (HMC-NUTS) for M2PPC models' parameter estimation. It compared the estimation accuracy and computing speed in different combinations of situations, including prior choices, test lengths, and the relationships between dimensions.

The datasets …