Sustainable Higher Education: From E-learning to Smart Education

Dear Colleagues,

The impact of IT on a number of spheres of economic and social life has been strongly emphasized in recent years. Education is also seriously affected by digitalization processes. The past two COVID-19 pandemic years were a particularly impactful and stimulating factor for education. They were the reason that during this period, education took place in a completely remote electronically based environment. In these conditions, e-learning is quickly and extensively integrated into the practices of both secondary and higher schools. Currently, although the pandemic situation now remains in the past of humanity, trainers and learners continue to adapt their activities to the new realities and intensively apply a number of electronic methods and tools of learning and training.

Moreover, e-learning is increasingly influenced by the new paradigm associated with smart learning. The concept of “smart learning” at this stage does not have a single definition and many researchers contribute to its interpretation. Authors [1] especially emphasize that the understanding of smart education in individual countries of the world is quite different and a wide array of related subjects have been reported. They point out, for example, that in China, the term “smart education” is used, while in European countries, “digital education” is preferred. Some researchers consider it as “a high-end form of digital transformation in education”, as well as advanced digital education and associate it with educational behaviors and having the characteristics of a high learning experience, learning content adaptation, and teaching efficiency [1]. Other researchers [2] state that smart learning refers to learning in interactive, intelligent, and personalized learning environments that are designed with the basis of up-to-date technologies and services, for example, augmented reality, cloud computing, and social networking services. In addition, authors [3] emphasize the advantages of smart learning environments, providing just-in-time learning based on various levels of adaptation and precision of diversified learning conditions for the learners.

Authors such as [4] understand more narrowly the scope of smart education mainly in the context of providing personalized learning, anywhere and anytime, with the help of artificial intelligence techniques, and for its provision, it is important to determine the individual learning style of the learner.

In the last few years, attention has been paid to aspects and features of smartness in education with a wide range of possibilities, tools, technologies such as interactive education and technologies, artificial intelligence, virtual, augmented, and mixed realities, learning analytics, gamification, e-learning platforms, blended learning, mobile applications and smart classrooms. The aim of this Special Issue is to contribute to the scope of smart e- and smart learning with the perspectives of participating researchers, academics, and practitioners.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

• Artificial intelligence for smart learning.
• Blended learning for the creation of a new and smart learning environment for effective learning.
• Smart approach to teaching and learning based on mobile and smart devices and applications.
• Personalization of learning with learning analytics.
• Gamification and smart education.
• Virtual, augmented, and mixed reality-based learning environments.
• Social media tools in E-learning.
• The role of cloud computing for a successful transition to smart learning.

We look forward to receiving your contributions.

References

1. Smart Education in China and Central & Eastern European Countries; Zhuang, R., Liu, D., Sampson, D., Mandic, D., Zou, S., Huang, Y., Huang, R., Eds.; Lecture Notes in Educational Technology; Springer: Singapore, 2023; p. 335. https://doi.org/10.1007/978-981-19-7319-2.
2. Yu, Y.; Qi, A. Teaching System of Smart Learning Environment for Aerobics Course. Int. J. Emerg. Technol. Learn. (iJET) 2018, 13, 165–176. https://doi.org/10.3991/ijet.v13i05.8440.
3. Qin, X.; Zhang, Y.; Gu, P.; Lin, L. The Impact of Cooperative Learning Strategies on Pupils’ Learning Engagement in the Smart Classroom Environment. Blended Learning. Education in a Smart Learning Environment (Lecture Notes in Computer Science, 12218 LNCS); Springer Nature: Cham, Switzerland, 2020; pp. 365–377.
4. Bajaj, R.; Sharma, V. Smart Education with artificial intelligence based determination of learning styles. Procedia Comput. Sci. 2018, 132, 834–842. https://doi.org/10.1016/j.procs.2018.05.095.

Prof. Dr. Silvia Parusheva
Prof. Dr. Samo Bobek
Dr. Simona Sternad Zabukovsek
Guest Editors

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• smart education
• smart learning
• mobile-based smart education
• interactive education and technologies
• virtual, augmented, and mixed realities
• artificial intelligence

Title: Artificial Intelligence Paradigms in Smart Education and Learning
Authors: Abdel-Badeeh M. Salem
Affiliation: Faculty of Computer and Information sciences, Ain Shams University, Egypt

Title: Knowledge assessment patterns for distant education: the perceived impact on grading, motivation and satisfaction
Authors: Tina Beranič; Marjan Heričko; Luka Pavlič
Affiliation: Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia
Abstract: With the increase in remote learning, the efficient implementation of distant knowledge assessment has become an essential topic. New challenges arose that had to be adequately addressed and successfully solved. As a response, we introduced an assessment patterns catalog for distant education, handling various challenges by proposing possible solutions. The catalog presents a collection of proven practices targeting knowledge assessment in digital and distant environments. Validation research was done as the final step of the catalog creation to verify its suitability and expedite its use. The paper presents the survey results, focusing on several knowledge assessment aspects. We focused on the perceived assessment patterns’ impact on grading objectivity and consistency, and students’ motivation and satisfaction with an assessment session. The impacts from the students’ and teachers’ perspectives were explored. We gathered data using a uniform questionnaire distributed between students and teachers, both actively involved in distant knowledge assessment. A detailed data analysis highlighted the patterns with the highest perceived impact on the previously mentioned assessment aspects. Also, an analysis of the top-rated patterns within the catalog’s pattern groups was done. The results depict a high overlap between students’ and teachers’ perspectives, wherein patterns like Pentathlon, Statistical Validator, Game Rules and Bonus Points were perceived as the patterns with the highest impact on grading objectivity and consistency, as well as the patterns with the most significant impact on students’ motivation and satisfaction.

Title: Development of Virtual Learning Centers in High Educational Institutions
Authors: Vojko Potočan
Affiliation: University of Maribor

Title: Using ERP simulation game to increase smart education experience in higher education
Authors: Simona Sternad Zabukovšek; Silvia Parusheva; Samo Bobek
Affiliation: 1. University of Maribor, Maribor, Slovenia 2. University of Economics - Varna, Varna, Bulgaria

Title: Enhancing Learning Outcomes through Immersive Virtual Reality Education: A Meta-analysis
Authors: Ye ZHANG; Ziqun ZHANG; Shu SHEN; Xinrong CHEN
Affiliation: 1. Shanghai Polytechnic University, 201209 Shanghai, China 2. Fudan University, 200433 Shanghai, China 3. Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China