The nature of solar radiation and the high penetration of photovoltaic (PV) systems in the smart electrical grid necessitate the development of models driven by historical operational data capable of precisely estimating the performance of PV systems. In this work, six proposed models are applied to predict the conversion efficiency of a 7.98 kWp rooftop on-grid PV system in Jordan. The dataset comprises 179 daily samples obtained during a single spring–summer period (17 March–24 September 2014). The efficiency modeled is the combined efficiency of the modules and inverter as a system. The proposed models are Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting (GB), Gaussian Process Regression (GPR), and Elastic Net (EN). The effectiveness of these proposed models is assessed by calculating four performance metrics, namely, the Mean Square Error, prediction accuracy, Coefficient of Determination (R2), and adjusted R2, and benchmarking the results with those of six prediction models discussed in our previous work. The results from the unweighted Decision-Making Matrix show that RF showed the best overall performance among the proposed and benchmark models considered. By contrast, the SVM, DT, and GB models exhibited moderate predictive behavior. However, Elastic Net is the worst-performing model among the 12 proposed and benchmark models discussed in this work. Moreover, the RF model’s consistently low prediction error supports its practical utility for PV system performance estimation, despite a slightly higher training cost than simpler models.

Solar energy is a sustainable substitute for fossil fuels that have an undesirable environmental impact in addition to the danger of depletion. Despite their potential, conventional solar air heaters (SAHs) are limited to thermal applications and suffer low efficiency due to heat loss and design constraints. Photovoltaic-thermal (PVT) systems, which simultaneously generate electricity and heat, offer a promising alternative. This study investigates the integration of bifacial photovoltaic (PV) minimodules into SAHs, with the aim of enhancing their performance and expanding their functionality. The objective of this work is to compare the optical and electrical performance of SAHs integrated with a bifacial PV mini-module in comparison to conventional SAHs with glass only. The methodology adopted is based on experimental optical and electrical characterizations in different wavelength ranges. The results reveal that 80.79% of the incoming irradiance reaches the absorber plate in conventional SAHs with glass only, while the rest is lost due to reflection and absorption. However, in SAHs with PV mini-module, 26.09% of the irradiance reaches the absorber plate, 54.53% of the total energy is absorbed in the PV cell contributing to electricity (10.53% is harnessed as electricity in the 300-1200 nm wavelength range) and heating (44.00%) generation, 10.11% of the total energy is absorbed in the surroundings of the PV cell, and the remaining 9.27% is lost due to reflection. These findings shed light on the intricate energy distribution and utilization within PV mini-modules when integrated into SAHs. More importantly, this study establishes a foundation for the design and optimization of efficient PVT-SAH systems in future research and development efforts.

This study systematically investigates the sensitivity of the Random Forest (RF) model to training dataset size in predicting photovoltaic (PV) system performance, a critical factor for smart grid stability and reliability. Using comprehensive operational data, including dust accumulation and ambient temperature, from a 7.98 kW grid-connected PV system in Jordan, the impact of varying training fractions on model accuracy, Coefficient of Determination (R2), Adjusted R2, and Mean Square Error (MSE) is assessed rigorously. Through Bayesian Optimization for hyperparameter tuning and multiple replicates, the findings consistently demonstrate that larger training datasets yield superior predictive performance and enhanced model stability. An optimal training fraction of 70% was identified, achieving high R2 and low MSE in addition to minimum computational time. While the prediction accuracy exhibited remarkable robustness even with reduced data, significant degradation in other metrics and increased variability were observed with training fractions below 30%. This research underscores the paramount importance of judicious training data selection for developing robust and reliable RF-based PV forecasting models, thereby facilitating more effective renewable energy integration.

In this study, the technical and economic feasibility of employing pumped hydroelectric energy storage (PHES) systems at potential locations in Jordan is investigated. In each location, a 1 MWp off-grid photovoltaic (PV) system was installed near the dam reservoir to drive pumps that transfer water up to an upper reservoir at a certain distance and elevation. PVsyst (Version 7.3.4) is implemented to simulate the water flow rate pumped to the upper reservoir at each location. The water in the upper reservoir is presumed to flow back into the dam reservoir through a turbine during peak hours at night to power a 1 MW load. Based on the water volume in the upper reservoir, the power generated through the turbine was estimated using HOMER Pro® (Version 3.15.3), and the power exported to the grid (when the power generated from the turbine is more than the power required by the driven load) was also determined. It is worth mentioning that scaling up the size of PV and hydropower systems is a straightforward approach considering the modular nature of such systems. However, the quantity of water in the dam reservoir that is allowed to be pumped is the main determinant for the size of a PHES system. The technical and economic results show that the potential of employing these locations to implement PHES systems is great. In addition, a study was conducted to estimate how much CO2 emissions were reduced by generating renewable energy compared to generating the same amount of energy from fossil fuels. These systems increase renewable energy in the energy mix in Jordan, stabilize the grid, and balance the loads, especially during peak periods. More importantly, PHES systems contribute to making the energy sector in Jordan more sustainable.

Solar energy is one of the sustainable energy sources, and Solar Air Heaters (SAHs) are among the key solar energy applications. SAHs are crucial for different applications due to their simplicity and minimal cost, with a wide variation in their performance based on the type and structure of the absorber plates and glass covers. This work aims to develop an extensive theoretical model to understand the heat transfer dynamics within SAHs and develop an empirical equation to find the optimal thermal efficiency of SAHs for various glass covers and the selectivity and structure of absorber plates. This is coupled with an attempt to quantitatively understand the correlation between different parameters and their effect on thermal efficiency through sensitivity analysis. Hence, employing the weather data for Amman, Jordan, for one year, this work investigates the performance of SAH under the simultaneous influence of selectivity and structure of absorber plates with the number of glass covers. The developed model utilises the energy balance equation and the isotropic diffuse model. The developed model and analysis show that the number of covers has an opposite effect on the performance of SAHs. Hence, the model converges to an optimal number of covers with the largest thermal efficiency. It is found that this optimal number is two covers for low-emittance absorber plates and three covers for high-emittance absorber plates. Moreover, the model shows that for flat SAHs, the highest efficiency is achieved with a combination of three covers and high-emittance absorber plates. In contrast, it is found that for corrugated SAHs, the efficiency is maximum with a combination of two glass covers and low-emittance absorber plates.

The inherent variability in solar Photovoltaic (PV) systems motivates developing dynamic and adaptive data-driven models capable of accurately predicting the systems’ performance. A dynamic/adaptive K-Nearest Neighbor (K-NN) model to estimate the conversion efficiency of a solar PV system is proposed in this work. The proposed model estimates the conversion efficiency of a test pattern based on three steps: (i) identifying the similar historical operational conditions experienced by the system, (ii) assigning a weight to each condition based on its similarity to the test pattern at hand, and (iii) computing the weighted average conversion efficiency of the test pattern. Thus, the proposed model is adaptive and dynamic as the nearest neighbors and the associated weights vary from one test pattern to another. The proposed model is applied to a 7.98 kWp rooftop grid-connected solar PV system at the Hashemite University in Jordan. Its effectiveness is evaluated by resorting to the Mean Square Error (MSE), Accuracy, Coefficient of Determination (R2), and Adjusted R2 (R2adjusted), and comparing the results with the traditional K-NN and other techniques adequately developed in the same context, such as Artificial Neural Network (ANN), Extreme Learning Machine (ELM), and Multiple Linear Regression (MLR). Results show that the proposed model exhibited superior performance across all metrics, with a performance gain reaching up to 45.2% and 6.8% for the MSE and R2adjusted, respectively, compared to the base MLR. Further, the simplicity and computational efficiency of the proposed model validate its practical deployment in predicting PV system performance.

In this study, the free and forced vibrations of a bi-directional functionally graded porous beam are investigated. The governing equations of motion are derived by Hamilton’s principle, and the reduced temporal equation of motion with cubic and quintic nonlinear terms is obtained using the Galerkin approach. Analytical solutions for the nonlinear natural frequencies in addition to the primary resonance response curves are established by the method of multiple scales. The effects of the axial and transverse functionally graded indexes, initial amplitude, porosity parameter, and the elastic and mass density ratios on the nonlinear frequencies and the forced responses are examined.

The article proposes the use of Artificial Intelligence (AI) models to predict the performance of a sun tracking Photovoltaic (PV) system built-in Zarqa City, Jordan.The system is off-grid with various Azimuth angles and tilt angles.The study involved taking various measurements over a 6-month period.The prediction models employed Artificial Neural Networks (ANN) with five different prediction classifiers, namely, random forest, forest tree, multilayer perceptron (MLP), BPF regression, and linear regression, to predict the performance of the sun-tracking PV system using experimental data.Different metrics are used to demonstrate and validate the accuracy of the proposed models.It is found that all proposed prediction models are of great accuracy.The best prediction classifier is found to be a forest tree classifier with an R2 value of 99.79% and a minimum absolute relative error of 2.36%.Moreover, the least accurate prediction classifier is found to be the linear regression with an R2 of 95.27% and an absolute relative error of 25.71%.

An electrostatic energy harvester is investigated where the reduced-order model is developed accounting for the electrical and mechanical nonlinearities. To overcome the difficulty of dealing with such a nonlinear model, an analytical approach based on the method of multiple scales is employed to create analytical solutions for displacement, electrical charge, and power of this harvester. The reduced-order model with the analytical solutions makes this approach novel and unique. The limits of applicability of this approach is determined by comparing the analytical solutions with solutions obtained using numerical integration. The results show that with estimating the effective nonlinearity as suggested in this approach, it is possible to interpret the behavior of harvester for a variety of operating conditions. The effective nonlinearity decreases more for a particular electrical load resistance as the electret voltage increases. However, the effective nonlinearity increases for a particular electret voltage as the electrical load resistance increases. When effective nonlinearity becomes very small, the behavior of the harvester turns into almost linear, and the matching of solutions of method of multiple scales with solutions of numerical integration is perfect. But, when the effective nonlinearity is significant, the deviation between solutions of method of multiple scales and solutions of numerical integration becomes noticeable. Moreover, increasing acceleration amplitude of the base excitation for cases of significant effective nonlinearity creates a bounded motion with softening behavior.

Two solar air heaters are experimentally investigated in outdoor conditions in Amman, Jordan. One heater is integrated with a selective-coated absorber plate, and the other is integrated with a black-painted absorber plate. The two types of absorber plates are obtained from local solar water heater manufacturers. The two air heaters are tested on a clear sunny day. Contrary to what is reported in the literature, the results show that the air heater with a black-painted absorber plate has a better thermal performance than the air heater with a selective-coated absorber plate. The daily average efficiencies are 45.7 % and 42.2 % for solar air heaters with black-painted and selective-coated absorber plates, respectively. This is attributed to the fact that the emissivity of black-painted surfaces is much larger than the emissivity of the top and bottom of the selective-coating system, resulting in higher efficiency and a higher amount of energy being transferred to moving air in the solar heater with black painting on the absorber plate. In addition, the black-painted absorber is painted from top (facing sun) and bottom (in contact with moving air) sides, while the selective-coated absorber has coating only on top side and the bottom side is left without coating.

In order to get on the path of sustainable development as a society as a whole, a great transformation is required. Universities are embedded in society and networked with it through various forms of interaction; they influence social discourses and often have a decisive influence on them. As educational institutions, universities have to take a critical stance on the state of our earth and actively fulfill their responsibility. The German Jordanian University (GJU), like any other university, produces solid and hazardous waste. A waste audit was done to identify the waste streams and the opportunities for reinforcing waste reduction, recycling, and composition while enhancing the comprehensive sustainability of a waste management program. The results showed that an average of 2,500 kg of waste was produced per week. The composition of the waste generated at the GJU main campus was 1,051 kg (41%) for paper and cardboard, 875 kg (35%) for plastics, 325 kg (13%) for biowaste, and 275 kg for other wastes. The performed UI GreenMetric showed high potential in the programs to reduce the use of paper and plastic on campus and the treatment of toxic waste with a score of 75 points. The results of this study indicate high potential in the recycling program for university waste, organic and inorganic waste treatment, and sewage disposal. The results for these indicators were moderate, a score of 75 points out of 300 points. Thus, more focus and actions should be placed on these indicators to enhance a sustainable green campus.

Massive open online courses (MOOCs) have slowly penetrated higher education as an easy-access low-cost auxiliary arm, with the possibility of transforming the roles of institutions, teachers and students in the new realm of Education 4.0. In fact, MOOCs may ultimately influence both continuing education of engineering graduates and degree-seeking students. Flipped MOOCs, on the other hand, have emerged as promising and engaging interactive learning media to both students and teachers. Introducing a lab component into a flipped-MOOC may extend its utilization to cover all levels of Bloom's taxonomy, and thus provide a learning model that is convenient to students at different levels of education. A flipped-MOOC. Lab on renewable energy is therefore presented as a sample for universities in the process of reform of teaching methodologies and pedagogies.

A theoretical study of the performance of flat- and corrugated-plate solar air heaters (SAHs) is conducted. This study focuses on the effect of the number of glass covers on SAHs behavior. The isotropic diffuse model is utilized to calculate the effective transmittance-absorptance product, while the energy balance equation is employed to estimate the thermal efficiency. The hourly and monthly meteorological data for Amman, Jordan is adopted to generate the results. Increasing the number of glass covers has a positive effect represented by decreasing the overall heat loss coefficient and a negative influence characterized by decreasing the effective transmittance-absorptance product. These opposite effects result in an optimal number of glass covers that achieves the highest heater performance. Based on the model in this work and operational conditions for Amman, the optimal number for glass covers is two.

The use of the concept of technology-enhanced learning is a design already applied in developed countries and incorporated as an active part of their educational models and curricular development. This is even more relevant in the case of eLearning, where these technologies correspond to remote/virtual laboratories. They are very useful in the fields of Science and Engineering. According to this, the current work shows the incorporation of this type of technology to traditional curricular schemes, with the aim of improving the effectiveness of learning. Another objective is to build reusable infrastructures among Universities, supported with public and private government resources. Specifically, this paper shows the development, implementation, and integration of remote renewable energy laboratories in Jordan, and how they have been used within the director plan of the Jordanian government for the promotion of renewable energies in that country. This plan includes not only the design of remote laboratories but also their integration into a curricular model. This integration is done at the level of online learning courses and pilot experiences in the development of these types of learning technologies. In a distance methodology environment, the instructors must design the course structure keeping in mind that students are online, but not face-to-face in the classroom. Additionally, they have to propose adapted resources (remote laboratories, guidelines, etc.) and content.The paper focuses on the incorporation of remote/virtual laboratories, showing how these labs were developed/integrated into online courses. To validate the incorporation of this type of resources in an environment usually not online, a set of surveys was designed to support a technology evaluation methodology (TAM, Technology Acceptance Model). This evaluation allows knowing the degree of satisfaction of the technology (remote and virtual laboratories as resources) using a structured experimental method (SEM, Structural Equation Models). As a result of the application of this experimental method, the calculated statistical data indicate that the use of remote and virtual laboratories improves the perception and use of virtual environments at a distance. Also, it can be indicated that these laboratories are presented as an essential resource to improve the quality of online teaching in engineering courses.

Abstract Background Right sided infective endocarditis (IE) accounts for 5-10% of IE cases, systemic embolization is uncommon and if present it is linked to the presence of shunt or concomitant left sided IE. Clinical presentation A 35-years old gentleman with history of heroin intravenous drug abuse (IV), presented with a history of unexplained fever for two weeks along with exertional dyspnea, productive cough, chest pain and severe left hypochondria pain. On examination he had a blood pressure of 130/80 mmHg, a heart rate of 130 bpm, a temperature of 40oC, elevated jugular venous pressure and a harsh pansystolic murmur over the lower left sternal border. Laboratory results revealed anaemia, leukocytosis elevated ESR and CRP and blood cultures were positive for methicillin-resistant staphylococcus aureus (MRSA), electrocardiography showed sinus tachycardia and abdomen computed tomography scan revealed multiple splenic infarctions. Methods and results 2D&3DTrans-Thoracic Echocardiography (TTE) revealed the presence of an echogenic elongated highly mobile mass measures 2.0 cm in maximum dimension attached to the atrial surface of the anterior tricuspid valve leaflet a long with severe valvular regurgitation. Patent foramen ovale (PFO) was visualized by Color Doppler and right to left shunt was confirmed by contrast study with a complete opacification of the left side. The left ventricle dimensions were normal , there was an evidence of hyokinesis of inter-ventricular septum (IVS) and inferior wall and function was reduced, estimated LVEF = 45%. Hence, coronary angiography was done and revealed normal coronaries. 3D Trans-esophageal Echocardiography(TEE) was done for better visualization of the interatrial septum (IAS), vegetation and to rule out complications. The study confirmed the presence of PFO, there was no concomitant IAS defects, the vegetation is highly mobile and facing the IAS. Accordingly, patient was diagnosed with tricuspid infective endocarditis complicated with paradoxical embolization, anti-biotics were commenced and patient underwent successful tricuspid valve replacement and PFO closure. Discussion Tricuspid valve endocarditis has been linked to IV drug abuse and staphylococcus aureus has been recognized as the most commonly implicated organism. While systemic emboli are rare in right sided IE, our patient represent this uncommon complication. He had multiple splenic infractions and TTE contrast study showed PFO with a high degree of right to left shunt. Coronary embolization was a suspect in our patient as well given the presence of regional wall motion abnormalities involving the left ventricle inferior wall and IVS. Conclusion Echocardiography is a crucial imaging modality in patient with long standing fever and history of IV drug abuse to rule out infective endocarditis. 3D-TEE is of added value along with TTE in better definition of vegetations and detection of infective endocarditis complication. Abstract P1299 Figure. Tricuspid valve infective endocarditis

Abstract Funding Acknowledgements Nothing to disclose Background Mitral valve aneurysm is an uncommon sequelae of infective endocarditis (IE), early diagnosis and timely intervention is of paramount importance to prevent aneurysm rupture and hemodynamic deterioration. Clinical presentation A 25-years old gentleman with no known past medical history, presented with a history of unexplained fever for the past month partially responding to antipyretics along with exertional dyspnea. On examination he had a blood pressure of 120/80 mmHg, a heart rate of 110 bpm, a temperature of 39oC, a harsh pansystolic murmur over the apex and early diastolic murmur over the second aortic area. Laboratory results revealed anaemia, leukocytosis elevated ESR and CRP and blood cultures were positive for streptococcus viridians. Electrocardiography showed sinus tachycardia. Methods and results Trans-Thoracic Echocardiography (TTE) revealed the presence of an echolucent cavity measured 1.6x1.6 cm overlying a perforation of the anterior mitral valve leaflet (AML) a long with two small vegetations attached to the AML at the perforation edge, largest measures 0.8cm. There was a severe mitral valve regurgitation. The aortic valve is thickened trileaflet with lack of diastolic cooptation and evidence of severe regurgitation. The left ventricle dimensions were dilated and function was reduced, estimated LVEF = 50%. 3DTrans-esophageal Echocardiography(TEE) was done for better visualization of the mitral valve. The cavity involved A2 scallop, it was perforated and communicating with the LA with an additional regurgitation jet. The aortic valve showed no detectable masses or abscesses. Accordingly, patient was diagnosed with infective enfocarditis complicated with AML perforation and aneurysm formation, anti-biotics were commenced and patient was referred for double valve replacement. Discussion Mitral valve aneurysm most commonly occurs secondary to infective endocarditis of the aortic valve, while our patient does not demonstrate evidence of vegetations at the aortic valve but he had an unhealthy valve with severe regurgitation jet that hits AML and might by a cause of hit lesion at the AML and eventually complicated by aneurysm formation. Discussion Echocardiography is a crucial imaging modality in patient with long standing fever and underlying valvular heart disease to rule out infective endocarditis. 3D-TEE is of added value along with TTE in better definition of vegetations, detection of infective endocarditis complication and it has a crucial role in proper diagnosis and surgical planning for better clinical outcomes. Abstract P1693 Figure. Mitral valve aneurysm

Abstract Funding Acknowledgements n/a Background Health care associated infective endocarditis (HAIE) accounted for u to 30% of infective endocarditis (IE) cases, it tends to affect patients with a poor clinical condition and represents a considerable in-hospital mortality. Case A 75-years old gentleman with end-stage renal failure secondary to polycystic kidney disease had commenced hemodialysis via a tunneled hemodialysis catheter 3 months ago, presented for pre-operative evaluation before vascular surgery for acute left lower limb ischemia, patient gave history of fever for the past month partially responding to antipyretics along with recent ischemic cerebrovascular stroke with no residual neurological deficits. On examination he had a blood pressure of 110/70 mmHg, a heart rate of 100 bpm, a temperature of 38oC, and a harsh pansystolic murmur over the apex. Laboratory results revealed leukocytosis elevated CRP and blood cultures were positive for staphylococcus aureus. Electrocardiography showed sinus tachycardia. Methods and Results 2D-Trans-Thoracic Echocardiography (TTE) revealed the presence of echogenic rounded mobile mass measured 2x2 cm attached to the atrial surface of the posterior mitral valve leaflet. There was a severe mitral valve regurgitation and the regurgitant jet was directed anteriorly swirling around the mass. The left ventricle dimensions and function were normal. 2D-Trans-esophageal Echocardiography(TEE) was done for better visualization of the mass and it"s attachment. The mass was overlying the atrial surface of the posterior leaflet middle P2 scallop with a small echo-lucent cavity (abscess formation) in the leaflet in addition to another smaller mass at the atrial surface of the anterior leaflet. The aortic, tricuspid and pulmonary valves were normal in structure and function Discussion Echocardiography is a crucial imaging modality in a patient with multiple systemic emboli to rule out cardio-embolic source of embolization. TEE is of added value along with TTE in better definition of masses and detection of IE related complication. While the patient was prepared for the vascular surgery to secure the ischemic limb his sensorium was disturbed and became unconscious immediate brain computed tomography showed severe intracranial hemorrhage and the patient died. Conclusions Patient with chronic kidney disease and on hemo-dialysis are highly vulnerable to health care related infective endocarditis and high clinical suspicion should be given in a situation of prolonged fever and embolic events. Mitral valve abscess is a rare complication of infective endocarditis and if occurs it leads to increase mortality. TEE should be an integral part of management of patients with IE to role out serious complications. Abstract P835 Figure. Mitral valve infective endocarditis

This work presents a technical and economic evaluation of the application of phase change material (PCM) in the cooling and thermal regulation of photovoltaic (PV) panels. The technical study is performed based on experimental tests carried out on two identical 3.99 kWp PV systems for one full year at the Hashemite University, Jordan. The backside of the first system was integrated with BioPCM. It is a safe, environmentally friendly, and economically sustainable product that is typically employed in the building industry to save energy in HVAC. This PCM has the potential to answer the many concerns associated with the traditional PCMs. The second PV system is used as a reference for performance comparison purposes. The actual performance results show there is an increase of 3.4% in the annual power production due to the application of BioPCM. The annual conversion efficiency is 12.50% for the PV/BioPCM system, while it is 12.08% for the reference PV system. The economic study investigates the viability of the inclusion of PCM in terms of the payback period, net present value, and internal rate of return. These parameters indicate that the PCM investment is economically unattractive at present. (C) 2020 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved

The emergence of information and communication technologies has paved the way for new online teaching methodologies to spread widely in recent years. Students have consequently moved into the heart of the learning process while instructors have acquired the role of facilitators in a new paradigm centered on students. Student-centered learning has therefore manifested itself as an opportunity for higher education institutions; particularly in developing countries, to meet many of the challenges posed by an increasingly changing landscape. A new renewable energy online course is described as a pilot to support the concept of student-centered learning at Hashemite University. Students in this course utilize study guides as the backbone of course delivery and implementation, interact with and navigate content, read and/or listen to explanation, watch videos, answer questions, uncover answers interactively. Several types of assessment tools are arranged weekly to ensure continuous monitoring and follow up. Three tools are utilized in order to evaluate the effectiveness and the quality of the course, including pre-survey, satisfaction survey and grades analysis. The correlation between students' grades and grade point average is then revealed to demonstrate the validity and effectiveness of course delivery and comprehension as well as the concept of student-centered learning. The results support the idea that online student-centered learning is promising in higher education institutions in Jordan, although there is still a great debate in the literature on its effectiveness.

A Model for Jordanian National Qualifications Framework Abdallah Al-Zoubi, Majed Abu Jaber, Adnan Atoum, Bashar Hammad, Mamoun Dmour Abstract A national qualifications framework (NQF) has become a necessity to support structural reform of the higher education system in Jordan at different institutional levels. The development and implementation of the Jordanian NQF focused on the needs of Jordanian higher education and its key stakeholders; will contribute to organizing the standards of Jordanian qualifications and other awards, and aid transparency of quality assurance at national and institutional levels. The framework also sought compatibility with international norms and expectations, including those of the European Higher Education Area (EHEA), thus assisting mobility, employability and internationalisation in Jordan and its international partners. Full Text: PDF DOI: 10.15640/jehd.v8n3a12