A research framework of smart education
TL;DR: A four-tier framework of smart pedagogies and ten key features of smart learning environments are proposed for foster smart learners who need master knowledge and skills of the 21st century learning.
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Abstract: The development of new technologies enables learners to learn more effectively, efficiently, flexibly and comfortably. Learners utilize smart devices to access digital resources through wireless network and to immerse in both personalized and seamless learning. Smart education, a concept that describes learning in digital age, has gained increased attention. This paper discusses the definition of smart education and presents a conceptual framework. A four-tier framework of smart pedagogies and ten key features of smart learning environments are proposed for foster smart learners who need master knowledge and skills of the 21st century learning. The smart pedagogy framework includes class-based differentiated instruction, group-based collaborative learning, individual-based personalized learning and mass-based generative learning. Furthermore, a technological architecture of smart education, which emphasizes the role of smart computing, is proposed. The tri-tier architecture and key functions are all presented. Finally, challenges of smart education are discussed.
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Citations
Role of Cloud Computing Technology in the Education Sector
Riddhi Thavi,Rujuta Jhaveri,Vaibhav Narwane,Bhaskar Gardas,Nima Jafari Navimipour +4 more
TL;DR: This literature review examines the role of cloud computing in education, identifying factors influencing adoption and its potential to enhance educational systems, particularly in developing countries, through remote/distance learning and cloud-based design and manufacturing.
Застосування смарт-комплексів у підготовці майбутніх вчителів
TL;DR: The article revealed the features of smart education as a leading concept for the development of professional training of prospective teachers and the main components, such as a smart student, smart pedagogy and smart environment, were characterized.
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TL;DR: In this study, a SLA dataset was explored and advanced ensemble techniques were applied for the classification task, and Bagging Tree and Stacking Classifiers have outperformed other classical techniques with an accuracy of 79% and 78% respectively.
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