STUDENTS' EVALUATIONS OF UNIVERSITY TEACHING: A STRUCTURAL EQUATION MODELING ANALYSIS

In this paper a Student Satisfaction survey was conducted. The used questionnaire was proposed by a very large Research Group in 2010. The collected data was elaborated by a full reflective Structural Equation Model using PLS path model estimation. The first results showed that the influence of the Organization and Infrastructure on the Student Satisfaction were not statistically significant. Therefore a more complex model was supposed, the end results showed that the influence of Organization and Infrastructure on the SS was indirect, that is the Organization and the Infrastructures exert an influence upon the SS through the Didactics

A statistical model for self-evaluation of teacher's satisfaction: A study in an Italian secondary school

Job Satisfaction is a set of favorable or unfavorable feelings and emotions linked to how employees view their work environment. If employees are not satisfied with their jobs, the overall progress of the entire system is affected. This paper reports on a study of teacher job satisfaction that examined a sample of 362 teachers. The study used a Common Assessment Framework & Education questionnaire to collect data, and a Structural Equation Model taking age, total years of service and gender into account was used to identify the factors that most influence Job Satisfaction. The results obtained from the Job Satisfaction model underline a significant difference between male and female teachers

Generalized log odds ratio analysis for the association in two-way contingency table.

The odds ratio is a measure of association used both for the analysis of a contingency table and an contingency table, where I and J are bigger than 2. Nevertheless, the total number of odds ratios to check grows with I and J and several methods have been developed to summarize them. In the present paper we present a general framework for the analysis of the complete set of log odds ratio. Particularly we propose and connect two different methodologies performed on two different data sets. Moreover starting from these methodologies, we focus our attention on the factorial representation of the log odds ratios

Polycyclic Aromatic Hydrocarbons Pollution in a Coastal Environment: the Statistical Analysis of Dependence to Estimate the Source of Pollution

Polycyclic Aromatic Hydrocarbons (PAHs) are a group of carcinogenic contaminants widespread in the environment. PAHs are produced by both anthropogenic and natural processes. Difficulties exist in identifying their origins. This paper reports a practical application of Principal Component Analysis (PCA) and Principal Component Regression (PCR) to identify the pyrolytic, petrogenic and diagenesis sources of PAH pollution in the Sarno River and Estuary. Nicknamed "the most polluted river in Europe", the Sarno River originates in south-western Italy and has a watershed of about 715 km(2). PCA indicated that the PAH contamination in the Sarno River and Estuary resulted from a mixed pattern. The first principal component (PC1) had significant positive loading in high molecular weight PAHs. This profile of PAH usually includes products of high temperature combustion/pyrolitic processes, reflecting the effects of traffic pyrolysis. The second principal component (PC2) had significant positive loading in two-to-four ring PAHs. So, PC2 may be considered as components from petrogenic sources. PC3 was characterized by a high loading of perylene, thought to originate from diagenetic alteration of perylenequinone pigment or some other organic matter. Therefore, this factor can be considered as natural-origin PAHs. In the PCR, the regression coefficients for components 1-3 were 66.6, 40.4 and 19.5, respectively. In this application, the PCR was a very useful statistical technique for handling the problem of multicollinearity. Results from the application of PCR have been compared with Partial Least Square (PLS) and no significant differences were reported in the prediction errors and latent variables available by PCR and PLS

Three-way Decomposition of Weighted Log-odds Ratio for Customer Satisfaction Analysis

In literature several methods have been proposed for the service quality assessment. A large number of models have been proposed to evaluate Service Quality (Servqual, Normed Quality, Servperf etc.). Starting from the SERVPERF paradigm, in this paper we propose to use Odds Ratio analysis to evaluate Customer Satisfaction. In particular the data has been collected in three-way contingency tables in which the crossed variables are perception evaluations, importance evaluations and dimensions. For each slice we computed the Odds Ratio. Thus a weighted version of log-Odds Ratio Analysis for three-way is proposed and analyzed by the Parafac/Candecomp algorithm. A case study on Patient Satisfaction (PS) survey that was carried out at a Neapolitan government hospital is presented in the last part of the paper in order to show the proposed methods

A multi-group higher-order factor analysis for studying the gender-effect in Teacher Job Satisfaction

Teachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and towhat extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order tomake inference on the parameters and on the validity of themodel. Moreover, a new multi-group test

Occurrence and spatial-temporal distribution of atrazine and its metabolites in the aquatic environment of the Volturno River estuary, southern Italy

The present study assesses the spatial distribution and temporal trends of the water dissolved phase (WDP), suspended particulate matter (SPM) and sediment partitioning of atrazine (ATR) and its metabolites in the Volturno River estuary. The load contribution of ATR and its metabolites in this river to the Central Mediterranean Sea was estimated. Samples were collected in 10 sampling sites during the four seasons. The total concentrations of ATR and DPs detected ranged from 18.1 to 105.5 ng L−1 in WDP, from 4.5 to 63.2 ng L−1 in SPM, and from 4.6 to 18.6 ng g-1 in sediment samples, indicating high levels of these pollutants. Structural equation model and the ratio study indicated that the relationship between sediment and WDP pollutants occurred through the SPM. The pollutants load at the Volturno River in its mouth was evaluated in about 30.4 kg year-1, showing that this river is an important source of these analytes through discharge into Central Mediterranean Sea. Principal component analysis indicated that ATR and its metabolites pollution moves from Volturno River mouth southward and increased in the rainy season. The desethylatrazine-to-atrazine ratio was higher than 0.5 for all samples analyzed, indicating an historical discharge and a long residence time of ATR in sediment about two decades after its ban, and classifying ATR as a nonpoint source contaminant. This study makes up the first record of ATR and its metabolites in superficial water of Southern Italy and provides helpful data as starting point for future studies

Estimation of polycyclic aromatic hydrocarbons pollution in mediterranean sea from volturno river, southern italy: Distribution, risk assessment and loads

This study reports the data on the contamination caused by polycyclic aromatic hydrocarbons (PAHs) drained from the Volturno River. The seasonal and spatial distribution of PAHs in water and sediment samples was assessed. The 16 PAHs were determined in the water dissolved phase (DP), suspended particulate matter (SPM), and sediments. A multidimensional statistical approach was used to identify three pollution composite indicators. Contaminant discharges of PAHs into the sea were calculated in about 3158.2 kg/year. Total concentrations of PAHs varied in ranges 434.8 to 872.1 ng g−1 and 256.7 to 1686.3 ng L−1 in sediment samples and in water (DP + SPM), respectively. The statistical results indicated that the PAHs mainly had a pyrolytic source. Considering the sediment quality guidelines (SQGs), the water environmental quality standards (USEPA EQS), and risk quotient (RQ), the Volturno River would be considered as an area in which the environmental integrity is possibly at risk

The use of mobile phone while driving: Behavior and determinant analysis in one of the largest metropolitan area of Italy

The use of mobile phones while driving is one of the main causes of road accidents and it is a phenomenon in continuous growth. The key aim of this study is to analyse simultaneously knowledge, attitudes, and behavior toward the use of mobile phones while driving in one of the largest and populous metropolitan areas of Italy, Naples. The data acquired from 774 questionnaires - administered to subjects evenly divided by gender and with an average age of 39 years - revealed that 69 % have used their mobile phone while driving at least once in their lifetime. Among those who used the phone, 63.6 % use it to make phone calls while 75.2 % only to answer them; 49.1 % read messages and only 33.3 % write them. It is also notable that 34.1 % do not stop to answer a call and only 10 % do not value the use of headsets while driving as fundamental. The results indicate that cell phone usage while driving is common in the study population, despite many having university-level education and satisfactory risks awareness. The multiple linear regression analysis shows how knowledge is not correlated to the behavior held. On the contrary, attitudes are strongly correlated to knowledge and behavior, meaning that good attitudes bring forth positive behavior. According to the collected data and statistical analysis, it is possible to identify factors that can greatly affect the use of mobile phone while driving and establish targeted prevention programs