Aims and Scope:

Today, engineering education organizations have been addressing new professional challenges, guided by general concerns, such as teamwork abilities, argumentation and persuasion abilities in multiple social contexts, creativity, complexity handling, and leadership or strong work ethics. The intelligent services have become a novel topic for interesting researchers and developers in academic area e-learning and engineering education. It is foreseeable that smart devices are deployed at the cloud-based services. The development of the educational system is fundamental for sustainable technological change using the smart devices and Internet of Things (IoT) applications. In other hand, machine learning methods can apply and improve the teaching practices in e-learning and education through many ways and that is the main reason that we need to further examine the involvement of intelligence techniques for education procedures in IoT environment. This special issue will be developing methods and applications of intelligent services for e-learning and education in some new challenges of cloud-based IoT applications. Also, This Special Issue focuses on machine learning methods in e-learning and education, regarding any type of cloud-based IoT applications to evaluation of healthcare education, education in smart city, e-learning and technical concepts of educational environments in IoT. This special issue invites researchers to publish selected original articles presenting intelligent trends and systems to solve new challenges of engineering education and learning problems. We also are interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research and new future issues.

Topics are as below but are not limited to:

Smart teaching in IoT platform
Evaluating IoT smart devices in engineering education
Intelligent services in e-learning and education
Mobile assessing for students in engineering education
Cloud-based architectures for e-learning and education in IoT
Data mining methods for educational management in IoT
Machine learning methods for public healthcare systems in IoT
Deep learning on industrial equipment in IoT
Intelligent evaluations on virtual reality in teaching environments
Data mining on learning-assisted environments in IoT
Machine learning method for educational healthcare systems in IoT
Knowledge-based system for evaluating educational IoT environments
Image processing and pattern recognition for educational IoT environments
Machine learning on customer relationship management in IoT environments
Soft computing techniques for educational IoT environments
Educational Big Data analytics for IoT systems
New innovations of educational systems for smart city in IoT
Fuzzy logic and methods for learning assisted systems in IoT applications
Security and privacy for e-learning and educational systems in IoT applications

Important Dates:

Deadline for submissions: 20 December, 2020
Notification of First Round: 20 February, 2021
Final Decision: 20 May, 2021
Tentative Publication Date: Q3, 2021

Fee:
Free of charge


Guest Editors:

Dr. Alireza Souri (Leading Guest Editor)
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Iran
Email: a.souri@srbiau.ac.ir

Prof. Giovanna Castellano
Department of Computer Science, University of Bari, Italy
Email: giovanna.castellano@uniba.it

Prof. Mu-Yen Chen
Department of Engineering Science, National Cheng Kung University, Taiwan
Email: z10908012@ncku.edu.tw

Dr. Gabriella Casalino
Department of Computer Science, University of Bari, Italy
Email: gabriella.casalino@uniba.it