An instrument to measure information and communication technology user-skills ability for engineering learning

Some of the most important skills for engineering education in today’s digital world are information and communication technology (ICT) user-skills. This research concerned two main issues regarding ICT user-skills of engineering students. The first issue was the lack of a reliable and valid instrument to measure ICT user-skills ability for engineering learning. The second issue was the lack of profile information on students’ existing ICT user-skills, such as what their ICT skills level were, how they acquired the skills, their conception of ICT user-skills, to what extent ICT user-skills support engineering learning, as well as the difficulties faced in acquiring those skills. This information would provide the basis for student ICT skills improvement strategies. Thus, this research sought to address these issues by developing an instrument to measure students’ ICT user-skills and subsequently establishing the ICT user-skills profile. This study adopted an across-stage mixed method design, combining quantitative and qualitative approaches. The research process comprised eight major phases: problem identification, literature review, determining problem statement and research objectives, instrument design and development, sample selection, data collection, data analysis, discussion and conclusion. Instrument development and validation were performed in five phases: determining what to measure, a review and assessment of major existing instruments, drafting a new instrument, getting expert reviews and student feedback, pilot testing the instrument, checking the internal consistency and refining the instrument, testing the modified instrument, and finally conducting the main study using a stratified random sample. Reliability and validity of the instrument were established using a Rasch model. Quantitative data analyses were performed using the PASW and WINSTEPS software. Thematic analysis of interview transcriptions was conducted to corroborate quantitative findings. The outcomes of this study were a new survey instrument to measure ICT user-skills within context of the study population, and a profile of engineering students’ ICT user-skills

Some exact tests for manifest properties of latent trait models

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle, be performed. But the existing test methodology is based on asymptotic approximation, which is impractical in most applications since the required sample sizes are often unrealistically huge. To overcome this problem, a class of tests is proposed for making exact statistical inference about four manifest properties: covariances given the sum are non-positive (CSN), manifest monotonicity (MM), conditional association (CA), and vanishing conditional dependence (VCD). One major advantage is that these exact tests do not require large sample sizes. As a result, tests for CSN and MM can be routinely performed in empirical studies. For testing CA and VCD, the exact methods are still impractical in most applications, due to the unusually large number of parameters to be tested. However, exact methods are still derived for them as an exploration toward practicality. Some numerical examples with applications of the exact tests for CSN and MM are provided

Bayesian model criticism: prior sensitivity of the posterior predictive checks method

Use of noninformative priors with the Posterior Predictive Checks (PPC) method requires more attention. Previous research of the PPC has treated noninformative priors as always noninformative in relation to the likelihood, regardless of model-data fit. However, as model-data fit deteriorates, and the steepness of the likelihood's curvature diminishes, the prior can become more informative than initially intended. The objective of this dissertation was to investigate whether specification of the prior distribution has an effect on the conclusions drawn from the PPC method. Findings indicated that the choice of discrepancy measure is an important factor in the overall success of the method, and that different discrepancy measures are affected more than others by prior specification

Some exact tests for manifest properties of latent trait models

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle, be performed. But the existing test methodology is based on asymptotic approximation, which is impractical in most applications since the required sample sizes are often unrealistically huge. To overcome this problem, a class of tests is proposed for making exact statistical inference about four manifest properties: covariances given the sum are non-positive (CSN), manifest monotonicity (MM), conditional association (CA), and vanishing conditional dependence (VCD). One major advantage is that these exact tests do not require large sample sizes. As a result, tests for CSN and MM can be routinely performed in empirical studies. For testing CA and VCD, the exact methods are still impractical in most applications, due to the unusually large number of parameters to be tested. However, exact methods are still derived for them as an exploration toward practicality. Some numerical examples with applications of the exact tests for CSN and MM are provided.Conditional distribution Exact test Monte Carlo Markov chain Monte Carlo

Some Exact Tests for Manifest Properties of Latent Trait Models

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle, be performed. But the existing test methodology is based on asymptotic approximation, which is impractical in most applications since the required sample sizes are often unrealistically huge. To overcome this problem, a class of tests is proposed for making exact statistical inference about four manifest properties: covariances given the sum are non-positive (CSN), manifest monotonicity (MM), conditional association (CA), and vanishing conditional dependence (VCD). One major advantage is that these exact tests do not require large sample sizes. As a result, tests for CSN and MM can be routinely performed in empirical studies. For testing CA and VCD, the exact methods are still impractical in most applications, due to the unusually large number of parameters to be tested. However, exact methods are still derived for them as an exploration toward practicality. Some numerical examples with applications of the exact tests for CSN and MM are provided.Conditional distribution, Exact test, Monte Carlo, Markov chain Monte Carlo