Psychometric Properties Of The Geography Achievement Test, Geography Self Efficacy Scale, Usm Emotional Quotient Inventory And Their Relationships

To draw accurate conclusions about student achievement and its factors, it is very important to employ instruments with good psychometric properties. This study aimed to examine the psychometric properties of three instruments namely: Geography Self-Efficacy Scale (GSES), USM Emotional Quotient Inventory (USMEQ-i) and Geography Achievement Test (GAT). Additionally, this study aimed to examine the relationship among geography self-efficacy, emotional intelligence and geography achievement of 12th Grade students in Oman. Sample of the study consisted of 839 12th Grade students from two districts selected by cluster sampling from ten schools. Data were collected using three instruments: GSES, USMEQ-i and GAT. Data were analyzed by employing Rasch measurement model to examine dimensionality, fit statistics, gender DIF, response categories, reliability and construct validity of these instruments. Additionally, the structural equation modeling technique was used in order to examine the relationships among the geography self-efficacy, emotional intelligence and geography achievement. Findings showed that all scales in this study met the assumption of unidimensionality. All items in each instrument fit the expectation of Rasch model. The five response categories in GSES and USMEQ-i found to be adequate. Some items in each instrument showed gender DIF. Reliability indexes showed that the item reliability for all instruments and their sub-dimension was high, while the person reliability was good for over all instruments and low for some sub-dimensions such as Emotional Commitment from USMEQ-i and Higher Thinking Level from GAT. Person- item maps of these instruments did not show any significant gap in items distribution of GSES while it showed one significant gap in USMEQ-i and three in GAT. It also indicated that the items of GSES and USMEQ-i were easy and did not match the students’ abilities well. Findings from structural equation modeling demonstrated significant and positive direct relationships between emotional intelligence and geography self-efficacy as well as between geography self-efficacy and geography achievement. The direct relationship between emotional intelligence and geography achievement was found to be not significant. Additionally, the indirect relationship between emotional intelligence and geography achievement through geography self-efficacy was discovered. Based on these results, future research recommendations include reviewing these instruments in order to improve their psychometric properties, validating other instruments related to emotional intelligence and self efficacy in the context of Oman, and replicating this study in Oman with other grade level and different school subjects

Determinants of Efficiency of Tax’s Collection in Oman

This study examines the relationship between determinants of tax efficiency (tax awareness, electronic procedures and auditing procedures) and efficiency of tax collection in Oman. The research uses method of a quantitative method via survey 150 usable data based on tax inspectors of Tax Authority in Oman. The hypotheses of the present study utilized its variables via using Smart PLS and SPSS statistical tools. The findings revealed that a positive and significant link between tax awareness and efficiency.  As well as, the findings revealed other possible determinants (electronic procedures and auditing procedures) has a insignificant influence on efficiency of tax collection in Omani Tax Authority. The model of the current research might be beneficial to realize determinants of tax efficiency to growth the  effective of tax collection. Yet, practicing tax inspectors might understand tax awareness to improve firm effectiveness

Recent climate change over the Arabian Peninsula: trends and mechanisms

The global climate is changing. Compared with many parts of the world, especially North America and Europe, relatively little is known about how climate has changed over the Arabian Peninsula (AP) in recent decades. Quantifying the climate change in the mean and extreme temperature and precipitation variables and understanding the mechanisms behind these changes are essential for establishing adequate and proper adaptation strategies to ensure sustainability, reduce vulnerability and safeguard livelihoods. Four papers in this thesis contribute to that objective, utilising a combination of in situ high quality meteorological station data and high resolution regional climate model data. The first paper quantifies the trends in monthly, seasonal and annual mean, maximum, minimum temperatures and Diurnal Temperature Range (DTR) variables and total precipitation. The station dataseries are tested for quality control and homogeneity. A non-parametric test is used to calculate the trends and evaluate the trend significance for individual stations, subregions (Non-monsoonal and Monsoonal) and for the whole area average. There is a high significant increase in the temperature variables especially the minimum temperature (during 1980-2008 and over all the AP the trend of annual minimum temperature is 0.55 °C decade-1 while the annual maximum temperature trend is 0.32 °C decade-1) which leads to significant decrease in the DTR. The precipitation is decline but insignificantly. The non-monsoonal region located north of 20° N has experienced higher rates of warming than the monsoonal region. Spring and summer seasons witness the highest significant warming. The interannual variability of the AP temperature and precipitation shows marked negative association after 1998. The second paper utilises the AP daily data of maximum temperature, minimum temperature and precipitation to calculate climate extremes indices, evaluate the regional/subregional trends of these indices and assess the trend significance. There is a clear significant decrease of cold temperature extremes and a significant increase in the warm temperature extremes. The increase in the nighttime temperature extremes is remarkable in the last two decades (the rate of increase of the warm night frequency is 3.6% decade-1 during 1986-2008). The spatial trend patterns reveal a latitudinal distinction whereby the northern AP experiences an increase associated with day-time extremes while for the night-time extremes the trends are higher and significant for the southern region. Precipitation indices trends are weak and although they show general decrease in the last two decades they are insignificant. The changes in the Dew Point (Td) and the Mean Sea Level Pressure (MSLP) indicate possible changes in the regional dynamics. The third paper uses the Providing Regional Climates for Impact Studies (PRECIS) regional climate model forced by the European Centre for ERA-Interim re-analysis (ERA-Interim) to simulate the AP climate during 1990-2008. PRECIS simulation is validated based on climate mean and trends. The model simulation captures the mean climatic conditions and patterns, the increasing temperature tendency, as well as the decreasing precipitation observed in the last two decades. However, PRECIS has cold bias especially with the minimum temperature and it overestimates the precipitation over the high lands or regions close to them over the southwestern mountains and underestimates the precipitation over the southeastern mountains. The model products provide indications on the reasons behind the highest daytime spring warming (decrease of specific humidity) and significant nighttime summer warming (increase of Sea Surface Temperature (SST)). The model fails to simulate the recent increase of the nighttime temperature parameters over AP. The final paper addresses the possible local atmospheric circulations, SST and remote modes of variability associated with the recent AP climate extreme changes. Using the PRECIS simulation, composite difference maps for some surface, upper atmospheric circulation maps and SSTs between two period 1990-1997 and 1998-2008 have been calculated. The composite difference maps reveal significant local changes in these atmospheric and oceanic variables which possibly partly explain the recent regional warming and drying conditions during the last two decades. In addition, relationships of the regional/subregional extremes indices timeseries have been calculated with some known remote modes of variability. There is a clear, strong relation of El Niño Southern Oscillation (ENSO) with the AP climate in all the seasons except in winter. The North Atlantic Caspian Sea Pattern (NCP) influences the regional climate in winter especially the temperature variables

Recent climate change over the Arabian Peninsula: trends and mechanisms

The global climate is changing. Compared with many parts of the world, especially North America and Europe, relatively little is known about how climate has changed over the Arabian Peninsula (AP) in recent decades. Quantifying the climate change in the mean and extreme temperature and precipitation variables and understanding the mechanisms behind these changes are essential for establishing adequate and proper adaptation strategies to ensure sustainability, reduce vulnerability and safeguard livelihoods. Four papers in this thesis contribute to that objective, utilising a combination of in situ high quality meteorological station data and high resolution regional climate model data. The first paper quantifies the trends in monthly, seasonal and annual mean, maximum, minimum temperatures and Diurnal Temperature Range (DTR) variables and total precipitation. The station dataseries are tested for quality control and homogeneity. A non-parametric test is used to calculate the trends and evaluate the trend significance for individual stations, subregions (Non-monsoonal and Monsoonal) and for the whole area average. There is a high significant increase in the temperature variables especially the minimum temperature (during 1980-2008 and over all the AP the trend of annual minimum temperature is 0.55 °C decade-1 while the annual maximum temperature trend is 0.32 °C decade-1) which leads to significant decrease in the DTR. The precipitation is decline but insignificantly. The non-monsoonal region located north of 20° N has experienced higher rates of warming than the monsoonal region. Spring and summer seasons witness the highest significant warming. The interannual variability of the AP temperature and precipitation shows marked negative association after 1998. The second paper utilises the AP daily data of maximum temperature, minimum temperature and precipitation to calculate climate extremes indices, evaluate the regional/subregional trends of these indices and assess the trend significance. There is a clear significant decrease of cold temperature extremes and a significant increase in the warm temperature extremes. The increase in the nighttime temperature extremes is remarkable in the last two decades (the rate of increase of the warm night frequency is 3.6&amp;percnt; decade-1 during 1986-2008). The spatial trend patterns reveal a latitudinal distinction whereby the northern AP experiences an increase associated with day-time extremes while for the night-time extremes the trends are higher and significant for the southern region. Precipitation indices trends are weak and although they show general decrease in the last two decades they are insignificant. The changes in the Dew Point (Td) and the Mean Sea Level Pressure (MSLP) indicate possible changes in the regional dynamics. The third paper uses the Providing Regional Climates for Impact Studies (PRECIS) regional climate model forced by the European Centre for ERA-Interim re-analysis (ERA-Interim) to simulate the AP climate during 1990-2008. PRECIS simulation is validated based on climate mean and trends. The model simulation captures the mean climatic conditions and patterns, the increasing temperature tendency, as well as the decreasing precipitation observed in the last two decades. However, PRECIS has cold bias especially with the minimum temperature and it overestimates the precipitation over the high lands or regions close to them over the southwestern mountains and underestimates the precipitation over the southeastern mountains. The model products provide indications on the reasons behind the highest daytime spring warming (decrease of specific humidity) and significant nighttime summer warming (increase of Sea Surface Temperature (SST)). The model fails to simulate the recent increase of the nighttime temperature parameters over AP. The final paper addresses the possible local atmospheric circulations, SST and remote modes of variability associated with the recent AP climate extreme changes. Using the PRECIS simulation, composite difference maps for some surface, upper atmospheric circulation maps and SSTs between two period 1990-1997 and 1998-2008 have been calculated. The composite difference maps reveal significant local changes in these atmospheric and oceanic variables which possibly partly explain the recent regional warming and drying conditions during the last two decades. In addition, relationships of the regional/subregional extremes indices timeseries have been calculated with some known remote modes of variability. There is a clear, strong relation of El Niño Southern Oscillation (ENSO) with the AP climate in all the seasons except in winter. The North Atlantic Caspian Sea Pattern (NCP) influences the regional climate in winter especially the temperature variables.</p

Recent climate change over the Arabian Peninsula: trends and mechanisms

The global climate is changing. Compared with many parts of the world, especially North America and Europe, relatively little is known about how climate has changed over the Arabian Peninsula (AP) in recent decades. Quantifying the climate change in the mean and extreme temperature and precipitation variables and understanding the mechanisms behind these changes are essential for establishing adequate and proper adaptation strategies to ensure sustainability, reduce vulnerability and safeguard livelihoods. Four papers in this thesis contribute to that objective, utilising a combination of in situ high quality meteorological station data and high resolution regional climate model data. The first paper quantifies the trends in monthly, seasonal and annual mean, maximum, minimum temperatures and Diurnal Temperature Range (DTR) variables and total precipitation. The station dataseries are tested for quality control and homogeneity. A non-parametric test is used to calculate the trends and evaluate the trend significance for individual stations, subregions (Non-monsoonal and Monsoonal) and for the whole area average. There is a high significant increase in the temperature variables especially the minimum temperature (during 1980-2008 and over all the AP the trend of annual minimum temperature is 0.55 &deg;C decade-1 while the annual maximum temperature trend is 0.32 &deg;C decade-1) which leads to significant decrease in the DTR. The precipitation is decline but insignificantly. The non-monsoonal region located north of 20&deg; N has experienced higher rates of warming than the monsoonal region. Spring and summer seasons witness the highest significant warming. The interannual variability of the AP temperature and precipitation shows marked negative association after 1998. The second paper utilises the AP daily data of maximum temperature, minimum temperature and precipitation to calculate climate extremes indices, evaluate the regional/subregional trends of these indices and assess the trend significance. There is a clear significant decrease of cold temperature extremes and a significant increase in the warm temperature extremes. The increase in the nighttime temperature extremes is remarkable in the last two decades (the rate of increase of the warm night frequency is 3.6&percnt; decade-1 during 1986-2008). The spatial trend patterns reveal a latitudinal distinction whereby the northern AP experiences an increase associated with day-time extremes while for the night-time extremes the trends are higher and significant for the southern region. Precipitation indices trends are weak and although they show general decrease in the last two decades they are insignificant. The changes in the Dew Point (Td) and the Mean Sea Level Pressure (MSLP) indicate possible changes in the regional dynamics. The third paper uses the Providing Regional Climates for Impact Studies (PRECIS) regional climate model forced by the European Centre for ERA-Interim re-analysis (ERA-Interim) to simulate the AP climate during 1990-2008. PRECIS simulation is validated based on climate mean and trends. The model simulation captures the mean climatic conditions and patterns, the increasing temperature tendency, as well as the decreasing precipitation observed in the last two decades. However, PRECIS has cold bias especially with the minimum temperature and it overestimates the precipitation over the high lands or regions close to them over the southwestern mountains and underestimates the precipitation over the southeastern mountains. The model products provide indications on the reasons behind the highest daytime spring warming (decrease of specific humidity) and significant nighttime summer warming (increase of Sea Surface Temperature (SST)). The model fails to simulate the recent increase of the nighttime temperature parameters over AP. The final paper addresses the possible local atmospheric circulations, SST and remote modes of variability associated with the recent AP climate extreme changes. Using the PRECIS simulation, composite difference maps for some surface, upper atmospheric circulation maps and SSTs between two period 1990-1997 and 1998-2008 have been calculated. The composite difference maps reveal significant local changes in these atmospheric and oceanic variables which possibly partly explain the recent regional warming and drying conditions during the last two decades. In addition, relationships of the regional/subregional extremes indices timeseries have been calculated with some known remote modes of variability. There is a clear, strong relation of El Niño Southern Oscillation (ENSO) with the AP climate in all the seasons except in winter. The North Atlantic Caspian Sea Pattern (NCP) influences the regional climate in winter especially the temperature variables.This thesis is not currently available via ORA