Item Psychometric Property of Marital Quality Scale of Javanese People Using Rasch Model

The measurement of marital quality has been done in many countries including Indonesia. This article described the characteristics of the item parameter endorsement index and item fit model in the data as the results of measurement of marital quality of Javanese people. The 420 couples (N = 840) from Daerah Istimewa Yogyakarta, Solo, Banyumas, and Pekalongan involved this research. The data collected were analyzed using the Rasch model with the Quest program. In general, the endorsement index moves higher as the category increases, and there were four items from the dimension of relation quality and twelve items the dimensions of well-being quality that were misfit model. These indicated that the items did not really measure the latent construct desired and need to be removed or reviewed

Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map

In content- and knowledge-based recommender systems often a measure of (dis)similarity between items is used. Frequently, this measure is based on the attributes of the items. However, which attributes are important for the users of the system remains an important question to answer. In this paper, we present an approach to determine attribute weights in a dissimilarity measure using clickstream data of an e-commerce website. Counted is how many times products are sold and based on this a Poisson regression model is estimated. Estimates of this model are then used to determine the attribute weights in the dissimilarity measure. We show an application of this approach on a product catalog of MP3 players provided by Compare Group, owner of the Dutch price comparison site http://www.vergelijk.nl, and show how the dissimilarity measure can be used to improve 2D product catalog visualizations.dissimilarity measure;attribute weights;clickstream data;comparison

Robustness of Rasch Fit Statistics in Dichotomous and Rating Scale Data

To understand the role of fit statistics in Rasch measurement, it is necessary to comprehend why fit is important in measurement. The answer to this question is simple: applied researchers can only benefit from the desirable properties of the Rasch model when the data fit the model; however, the currently available fit statistics are flawed. A problem with fit statistics which are based on residuals is that they are based on unknown distributional properties (Masters & Wright, 1997; Ostini & Nering, 2006). Rost and von Davier (1994) developed the Q-Index. The Q-Index makes use of the statistical properties of the Rasch model, namely, parameter separability and conditional inference. Ostini and Nering, as early as 2006, called attention to the fact that little research has been performed on the Q-Index and thus there is little knowledge regarding the fit statistic’s robustness. To assess the Q-Index robustness, its performance was compared, in the present study, to the currently popular fit statistics known as Infit, Oufit, and standardized Infit and Oufit (ZSTDs) under varying conditions of test length, sample size, item difficulty (normal and uniform), and Rasch model (dichotomous and rating scale). The simulation consisted of 128 conditions that varied in sample size, test length, item difficulty distribution, and dimensionality. A series of factorial ANOVAs were conducted to examine the effect of sample size, test length, item difficulty distribution, and dimensionality on the fit statistics of interest. The results showed the Q-Index had a large effect size for dimensionality and for the dichotomous model a medium effect size for test length. Factorial ANOVAs for Infit, ZSTD Infit, Outfit, and ZSTD Infit resulted in trivial effect sizes for all the variables of interest. Parameter recovery was also examined, these findings suggest that the correlation between true and estimated parameters were high (r \u3e .930) for both the dichotomous Rasch and the rating scale Rasch model indicating good pameter recovery despite the manipulation of test length, sample size, item difficulty distribution and dimensionality. Future research may explore the Q-Index under different measurement disturbances such as local independence or the robustness of the person Q-Index. Overall more research is needed regarding the robustness of the Q-Index

CONSTRUCTION AND VALIDATION OF A HOLISTIC EDUCATION SCHOOL EVALUATION TOOL USING MONTESSORI ERDKINDER PRINCIPLES

The purpose of this study was to construct a holistic education school evaluation tool using Montessori Erdkinder principles, and begin the validation process of examining the proposed tool. This study addresses a vital need in the holistic education community for a school evaluation tool. The tool construction process included using Erdkinder literature to justify the development of each item through the use of an item matrix, ultimately leading to the development of the 23 item formative Montessori Erdkinder School Evaluation Survey. The validation process included a series of three Rasch Rating Scale Model analyses with data from a sample school. The validation process used item anchoring estimates from the earlier analyses in the later analyses and included determining the tool’s dimensionality, reliability, item fit, possible differential item functioning, and comparing the order of item difficulty levels to the holistic model of Maslow’s hierarchy of needs. Results of the study showed that six items had issues with fit and would need to be revised, and that the items in the cognitive and moral facet will need to be revised to better match Maslow’s model. This study provides the foundation for the development of a holistic education evaluation or accreditation system, and constructed a resource that could be directly implemented in schools

Development and Validation of Psychological Fitness to Drive Scale for Filipinos

AbstractRoad transportation for Filipinos is a daily task that subjects an individual to risks and dangers, leading to damages and deaths annually, this leads to developing and validating a Psychological Fitness to Drive Scale for Filipinos (PFDSF) to assess Filipino drivers’ mental readiness and save lives. Via test development, 154 items were generated after a rigorous process of conceptualization and item generation from pre-survey, interviews, and related literature with English and Filipino test booklets as delivered to 102 participants for pilot testing. Online field testing was delivered due to the COVID-19 pandemic. About 463 samples went through a series of factor analyses to determine the existing factors and retain highly relevant items, resulting in two factors namely, Risky Driving Behavior (RDB) with 50 items (α=0.968), and Responsible and Safe Mobility (RSM) having 22 items (α=0.915), for a total of 72 items. PFDSF was found to be psychometrically sound with validity in its content, construct, factors, and high reliability (α=0.967). Future researchers are invited to use the scale and explore other areas for utility with specific population, age, gender, exploration of a social desirability factor, further strengthening of its criterion, convergent and divergent validity considering computer-assisted online version its localization to different major dialects.Keywords: Psychological fitness to drive, test development and validation, Filipino drivers, road safety and traffic psycholog

Torque Prediction Model of a CI Engine for Agricultural Purposes Based on Exhaust Gas Temperatures and CFD-FVM Methodologies Validated with Experimental Tests

A truly universal system to optimize consumptions, monitor operation and predict maintenance interventions for internal combustion engines must be independent of onboard systems, if present. One of the least invasive methods of detecting engine performance involves the measurement of the exhaust gas temperature (EGT), which can be related to the instant torque through thermodynamic relations. The practical implementation of such a system requires great care since its torque-predictive capabilities are strongly influenced by the position chosen for the temperature-detection point(s) along the exhaust line, specific for each engine, the type of installation for the thermocouples, and the thermal characteristics of the interposed materials. After performing some preliminary tests at the dynamometric brake on a compression-ignition engine for agricultural purposes equipped with three thermocouples at different points in the exhaust duct, a novel procedure was developed to: (1) tune a CFD-FVM-model of the exhaust pipe and determine many unknown thermodynamic parameters concerning the engine (including the real EGT at the exhaust valve outlet in some engine operative conditions), (2) use the CFD-FVM results to considerably increase the predictive capability of an indirect torque-detection strategy based on the EGT. The joint use of the CFD-FVM software, Response Surface Method, and specific optimization algorithms was fundamental to these aims and granted the experimenters a full mastery of systems’ non-linearity and a maximum relative error on the torque estimations of 2.9%

Characterisation of flow structures inside an engine cylinder under steady state condition

The in-cylinder flow of internal combustion (IC) engines, formed during the intake stroke, is one of the most important factors that affect the quality of air-fuel mixture and combustion. The inducted airflow through the inlet valve is primarily influenced by the intake port design, intake valve design, valve lift and valve timing. Such parameters have a significant influence on the generation and development of in-cylinder flow motion. In most combustion systems the swirl and tumble motions are used to aid the air-fuel mixing with the subsequent decay of these bulk flow motions generating increased turbulence levels which then enhance the combustion processes in terms of rate of chemical reactions and combustion stability. Air motion formed inside the engine cylinder is three-dimensional, transient, highly turbulent and includes a wide spectrum of length and time scales. The significance of in-cylinder flow structures is mainly reflected in large eddy formation and its subsequent break down into turbulence kinetic energy. Analysis of the large scale and flow motions within an internal combustion engine are of significance for the improvement of engine performance. A first approximation of these flow structures can be obtained by steady state analysis of the in-cylinder flow with fixed valve lifts and pressure drops. Substantial advances in both experimental methods and numerical simulations provide useful research tools for better understanding of the effects of rotational air motion on engine performance. This study presents results from experimental and numerical simulations of in-cylinder flow structures under steady state conditions. Although steady state flow problem still includes complex three-dimensional geometries with high turbulence intensities and rotation separation, it is significantly less complex than the transient problem. Therefore, preliminary verifications are usually performed on steady state flow rig. For example, numerical investigation under steady state condition can be considered as a precondition for the feasibility of calculations of real engine cylinder flow. Particle Image Velocimetry (PIV) technique is used in the experimental investigations of the in-cylinder flow structures. The experiments have been conducted on an engine head of a pent-roof type (Lotus) for a number of fixed valve lifts and different inlet valve configurations at two pressure drops, 250mm and 635mm of H2O that correlate with engine speeds of 2500 and 4000 RPM respectively. From the 2-D in-cylinder flow measurements, a tumbling vortex analysis is carried out for six planes parallel to the cylinder axis. In addition, a swirl flow analysis is carried out for one horizontal plane perpendicular to the cylinder axis at half bore downstream from the cylinder head (44mm). Numerically, modelling of the in-cylinder flow is proving to be a key part of successful combustion simulation. The numerical simulations require an accurate representation of turbulence and initial conditions. This Thesis deals with numerical investigation of the in-cylinder flow structures under steady state conditions utilizing the finite-volume CFD package, STAR CCM+. Two turbulence models were examined to simulate the turbulent flow structure namely, Realizable k-ε and Reynolds Stress Turbulence Model, RSM. Three densities of generated mesh, which is polyhedral type, are examined. The three-dimensional numerical investigation has been conducted on the same engine head of a pent-roof type (Lotus) for a number of fixed valve lifts and both valves are opened configuration at two pressure drops 250mm and 635mm of H2O that is equivalent to engine speeds of 2500 and 4000 RPM respectively. The nature and modelling of the flow structure together with discussions on the influence of the pressure drop and valve lift parameters on the flow structures are presented and discussed. The experimental results show the advantage of using the planar technique (PIV) for investigating the complete flow structures developed inside the cylinder. It also highlighted areas where improvements need to be made to enhance the quality of the collected data in the vertical plane measurements. Based on the comparison between the two turbulence models, the RSM model results show larger velocity values of about 15% to 47% than those of the Realizable k-ε model for the whole regions. The computational results were validated through qualitative and quantitative comparisons with the PIV data obtained from the current investigation and published LDA data on both horizontal and vertical cross sections. The calculated correlation coefficient, which is above 0.6, indicated that a reasonable prediction accuracy for the RSM model. This verifies that the numerical simulation with the RSM model is a useful tool to analyse turbulent flows in complex engine geometries where anisotropic turbulence is created

Map Based Visualization of Product Catalogs

Traditionally, recommender systems present recommendations in lists to the user. In content- and knowledge-based recommendation systems these list are often sorted on some notion of similarity with a query, ideal product specification, or sample product. However, a lot of information is lost in this way, since two even similar products can differ from the query on a completely different set of product characteristics. When using a two dimensional, that is, a map-based, representation of the recommendations, it is possible to retain this information. In the map we can then position recommendations that are similar to each other in the same area of the map. Both in science and industry an increasing number of two dimensional graphical interfaces have been introduced over the last years. However, some of them lack a sound scientific foundation, while other approaches are not applicable in a recommendation setting. In our chapter, we will describe a framework, which has a solid scientific foundation (using state-of-the-art statistical models) and is specifically designed to work with e-commerce product catalogs. Basis of the framework is the Product Catalog Map interface based on multidimensional scaling. Also, we show another type of interface based on nonlinear principal components analysis, which provides an easy way in constraining the space based on specific characteristic values. Then, we discuss some advanced issues. Firstly, we discuss how the product catalog interface can be adapted to better fit the users' notion of importance of attributes using click stream analysis. Secondly, we show an user interface that combines recommendation by proposing with the map based approach. Finally, we show how these methods can be applied to a real e-commerce product catalog of MP3-players

Development and initial validation of a creative self-efficacy scale for undergraduates: categorical confirmatory factor analysis and multidimensional item response theory

Creative self-efficacy (CSE) has recently received much attention due to its association with student learning and creativity. To that end, a CSE scale was developed for undergraduates and sources of validity evidence based on scale content, response processes, and internal structure were collected. Score reliability, using categorical omega based on the categorical confirmatory factor analysis model and marginal reliability for response pattern scores based on item response theory (IRT), were estimated. After various revision iterations of the initial 28-item pool by 10 subject matter experts and 18 undergraduates, some items were revised, four items were dropped, and ultimately 24 items were field tested for measuring two hypothesized dimensions of CSE among 602 undergraduates. Categorical confirmatory factor analysis results indicated that the two-dimensional model had better fit. Similarly, between the two competing multidimensional IRT models, the two-dimensional graded response model had the best fit. Categorical omega coefficients and marginal reliability for response pattern scores were, respectively, 0.88 and 0.81 for the two underlying dimensions