Enabling smart learning systems within smart cities using open data

Deploying ad-hoc learning environments to use and represent data from multiple sources and networks and to dynamically respond to user demands could be very expensive and ineffective in the long run. Moreover, most of the available data is wasted without extracting potentially useful information and knowledge because of the lack of established mechanisms and standards. It is preferable to focus on data availability to choose and develop interoperability strategies suitable for smart learning systems based on open standards and allowing seamless integration of third-party data and custom applications. This paper highlights the opportunity to take advantage of emerging technologies, like the linked open data platforms and automatic reasoning to effectively handle the vast amount of information and to use data linked queries in the domain of cognitive smart learning systems

Exploiting the knowledge engineering paradigms for designing smart learning systems

Knowledge engineering (KE) is a subarea of artificial intelligence (AI). Recently, KE paradigms have become more widespread within the fields of smart education and learning. Developing of Smart learning Systems (SLS) is very difficult from the technological perspective and a challenging task. In this paper, three KE paradigms, namely: case-based reasoning, data mining, and intelligent agents are discussed. This article demonstrates how SLS can take advantage of the innovative KE paradigms. Therefore, the paper addresses the pros of such smart computing approaches for the industry of SLS. Moreover, we concentrate our discussion on the challenges faced by knowledge engineers and software developers in developing and deploying efficient and robust SLS. Overall, this study introduces the reader the KE techniques, approaches and algorithms currently in use and the open research issues in designing the smart learning systems.Инженерия знаний (ИЗ) – это подобласть искусственного интеллекта (ИИ). В последнее время парадигмы ИЗ и умных вычислений получают все более широкое распространение в сфере умного образования и обучения. Разработка систем умного обучения (СУО) является очень трудной с технологической точки зрения и сложной задачей. В данной статье мы изучили три парадигмы ИЗ, а именно рассуждения на основе прецедентов, интеллектуальный анализ данных и интеллектуальные агенты. Наше исследование указывает на то, что такие парадигмы могут эффективно использоваться для СУОІнженерія знань (ІЗ) – це пiдобласть штучного інтелекту (ШІ). Останнім часом парадигми ШІ та розумних обчислень отримують все більш широке поширення в сферi розумної освіти i навчання. Розробка систем розумного навчання (СРН) є дуже важким з технологічної точки зору і складним завданням. У даній статті ми вивчили три парадигми ШІ, а саме міркування на основі прецедентів, інтелектуальний аналіз даних та інтелектуальні агенти. Наше дослідження вказує на те, що такі парадигми можуть ефективно використовуватися для СР

The Degree of Activation at Secondary School Principals in Ramallah and Al-Bireh Governorate for Technology in The Educational Process from The Point of View of Technology Teachers

The current study aimed to reveal the degree of activation of secondary school principals in Ramallah and Al-Bireh governorate for technology in the educational process from the point of view of technology teachers, and to achieve the objective of the study, a questionnaire was developed consisting of (20) items distributed over three areas, and its validity and stability were verified, and then distributed to the study sample consisting of (165) teachers. It was selected in a simple random way, and the descriptive analytical approach was used in this study, and the results showed that the degree of activation of secondary school principals in Ramallah and Al-Bireh governorate for technology in the educational process from the point of view of technology teachers came with an average degree, as the arithmetic average of the tool as a whole was (3.28), and the results of the study showed that there were no statistically significant differences between the average scores of respondents on the total degree attributed to the gender variable, and years of experience, and in light of the results of the study, The researcher recommended a number of recommendations

How important it is to use e-learning management systems in building smart university in Kuwait

The study aimed to investigate the importance of using e-learning management systems in the construction of smart universities in Kuwait, The results showed the importance of using e-learning management systems in building aa smart university in Kuwait to an average degree, and the averages ranged from (2.46to4.37) Between (The mathematical average of the instrument as a whole Associate Professor, Associate Professor aNot و  a (3.33). On the other hand, the differences came in favor of both associate professors and assistant professor, and the results showed statistically significant differences (= 0.05) between less than five years and more than15 years a and the differences came Between in favor of less than five (= 0.05) years

A DEEP LEARNING MODEL FOR EDUCATION ANALYTICS – A SHORT REVIEW

Integrating deep learning with learning management systems can result in intelligent course material and high accuracy without any manual intervention. This paper reviews factors that influence deep learning in education, and hence this article aims to achieve deep learning on a large scale in the smart education system with a deep learning model to predict. The proposed model can reduce development and maintenance costs, reduce risks, and facilitate communication between stakeholders. HIGHLIGHTS: The current review focus on deep learning as an important tool for Indian teachers