كتابة النص: الأستاذ الدكتور يوسف أبو العدوس - جامعة جرش قراءة النص: الدكتور أحمد أبو دلو - جامعة اليرموك مونتاج وإخراج : الدكتور محمد أبوشقير، حمزة الناطور، علي ميّاس تصوير : الأستاذ أحمد الصمادي الإشراف العام: الأستاذ الدكتور يوسف أبو العدوس
فيديو بمناسبة الإسراء والمعراج - إحتفال كلية الشريعة بجامعة جرش 2019 - 1440
فيديو بمناسبة ذكرى المولد النبوي الشريف- مونتاج وإخراج الدكتور محمد أبوشقير- كلية تكنولوجيا المعلومات
التميز في مجالات التعليم والبحث العلمي، وخدمة المجتمع، والارتقاء لمصاف الجامعات المرموقة محليا واقليميا وعالميا.
المساهمة في بناء مجتمع المعرفة وتطوره من خلال إيجاد بيئة جامعية، وشراكة مجتمعية محفزة للابداع، وحرية الفكر والتعبير، ومواكبة التطورات التقنية في مجال التعليم، ومن ثم رفد المجتمع بما يحتاجه من موارد بشرية مؤهلة وملائمة لاحتياجات سوق العمل.
تلتزم الجامعة بترسيخ القيم الجوهرية التالية: الإلتزام الإجتماعي والأخلاقي، الإنتماء،العدالة والمساواة، الإبداع، الجودة والتميّز، الشفافية والمحاسبة، الحرية المنظبطة والمستقبلية.
دكتوراة تخصص علم الحاسوب من جامعة برونيل سنة 2014
Phd in computer science , Brunle university,London , UK 2014
-2015 Assistant Professor Faculty of IT, Jerash University, Jordan
This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems.BB-BC is a product of an evolution theory of the universe in physicsand astronomy. Two main phases of BB-BC are big bang and bigcrunch. The big bang phase involves a creation of a population ofrandom initial solutions, while in the big crunch phase these solutionsare shrunk into one elite solution exhibited by a mass center. This studylooks into enhancing the BB-BC’s effectiveness in clustering data.Where, the inclusion of an elite pool alongside implicit solutionrecombination and local search method, contribute to suchenhancement. Such strategies resulted in a balanced search of goodquality population that is also diverse. The proposed elite pool-basedBB-BC was compared with the original BB-BC and other identicalmetaheuristics. Fourteen different clustering datasets were used to testBB-BC and the elite pool-based BB-BC showed better performancecompared to the original BB-BC. BB-BC was impacted more by theincorporated strategies. The experiments outcomes demonstrate the highquality solutions generated by elite pool-based BB-BC. Its performancein fact supersedes that of identical metaheuristics such as swarmintelligence and evolutionary algorithms.
Mobile learning applications utilise the advantages of mobile technologies to increase learning opportunities, mainly on an anytime, anywhere basis. The advancement of mobile technology has facilitated the development of numerous applications to improve students’ learning experience and performance. Successful implementation of m-learning is highlydependent on learning context and environment awareness. This work presents a multiphaseexploration of early phases responsible for defining and validating the m-learning context, andlater phases based on context validation results achieved from the previous phases, involving thedevelopment and evaluation of a new m-learning context prototype. This new prototype provedto provide context-aware and ubiquitous learning services fulfilling several diverse userinteraction levels and requirements.
Quality assurance is one major concern for the faculty of Computer Science and Information Technology (FCSIT) at Jerash University. It involves eight standards including the strategic planning. SWOT analysis is a method meant for assisting the formulation of strategy and planning. An application to strategic planning process formulation for the FCSIT is described. This research studies the SWOT analysis with a major concern of drawing more conclusions using machine learning methods. Data mining is a subfield of machine learning, which focuses on exploratory data analysis using supervised or unsupervised learning. Data mining techniques help fetching required knowledge from raw data to make decisions more confidently interpreted and automated. In this study, regression, classification, clustering, association rules, attributes selection techniques are used to mine data from the SWOT analysis. Using Weka workbench, results of each technique is obtained and interpreted with the favor of the factors that have impact on the success of the strategic plan. The outcome presents a high level of satisfaction regarding employee, and a vibrant level of satisfaction regarding students. Therefore, the developed quality assurance framework is stable but needs more improvements to overcome the dissatisfaction of many students regarding services, supervision, awards and activities.
Mobile learning (m-learning) has become an increasingly attractive solution for schools anduniversities that utilize new technologies in their teaching and learning settings. This study investigatesthe technical factors affecting the development of m-learning applications services from students’perspectives. It presents a model consisting of 12 technical factors, including content usefulness,scalability, security, functionality, accessibility, interface design, interactivity, reliability, availability,trust, responsiveness, and personalization. To evaluate the model, a questionnaire was designed anddistributed to 151 students in Jerash University, Jordan. The results indicate that all technical factorshave positive effects on learner satisfaction and overall m-learning applications service; however,the data mining analysis revealed that security and scalability factors exert a major impact on studentsatisfaction with m-learning applications services. This study gives insight into the future of developingand designing m-learning applications
During the Coronavirus Disease 2019 (COVID19) pandemic and the national lockdowns implemented incountries around the world, many universities worldwide made the transition from face to face delivery to onlinelearning using e learning systems. However, t he successful transition from traditional class based learning toonline learning depends greatly on understanding the challenges related to the implementation and use ofe learning systems, as well as the technical and management factors that need to be e nhanced. This study aimedto investigate the challenges related to the use of e learning systems in Jordanian universities and to explore thetechnical and management aspects that impacted the successful implementation and use of e learning systemsduring COVID 19. To achieve the study objectives, a questionnaire was developed by the researcher anddistributed online to lecturers working at Jordanian universities. A total of 184 lecturers participated in the study.Based on the findings, the study provides recommendations which will help higher education policy makers,university management teams, and software developers build strategies to ensure the successful implementationand use of e learning systems during the COVID 19 pandemic.
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