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Trends in Artificial Intelligence-Supported E-Learning
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Trends in Artificial Intelligence-Supported E-Learning

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 4845

Special Issue Editors

Dr. Todorka Glushkova

E-Mail Website1 Website2
Guest Editor
Computer Technologies, Plovdiv University, 4000 Plovdiv, Bulgaria
Interests: AI in education; context modeling; adaptive e-learning; CPSS educational platforms
Prof. Dr. Lyubka Doukovska

E-Mail Website
Guest Editor
Intelligent Systems Department, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Interests: computational intelligence; prediction; neural networks; e-learning systems; predicative modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern AI technologies have significant potential to support and develop education. Through them, it is possible to significantly facilitate the achievement of educational goals and the development of the digital competencies necessary for the modern person. In addition, these technologies have the potential to increase the activity and motivation of all participants in the educational process. This Special Issue focuses on the creation of new educational strategies related to the application of AI technologies in the creation of educational platforms for distance and e-learning.

Topics of interest include, but are not limited to, the following:

  • AI technologies for personalization of learning;
  • Semantic modeling and ontologies;
  • Contextual modeling;
  • Predicative modeling;
  • Innovative use of technology in the classroom, from primary to higher education;
  • Computer and web-based software and mobile applications for distance and blended learning;
  • Augmented reality and metaverse for education;
  • Creating cyber-physical platforms for lifelong learning.

Dr. Todorka Glushkova
Prof. Dr. Lyubka Doukovska
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AI in education
  • human–computer interaction
  • adaptive e-learning
  • inclusive teaching
  • extended reality
  • cyber-physical educational platforms
  • lifelong learning

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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28 pages, 4157 KiB  
Article
Integrating Quantitative Analyses of Historical and Contemporary Apparel with Educational Applications
by Zlatina Kazlacheva, Daniela Orozova, Nadezhda Angelova, Elena Zurleva, Julieta Ilieva and Zlatin Zlatev
Information 2025, 16(2), 144; https://doi.org/10.3390/info16020144 - 15 Feb 2025
Viewed by 610
Abstract
In this paper, a comparative analysis of historical and contemporary fashion designs was conducted using quantitative methods and indices. Elements such as silhouettes, color palettes, and structural characteristics were analyzed in order to identify models for reinterpretation of classic fashion costume. Clothing from [...] Read more.
In this paper, a comparative analysis of historical and contemporary fashion designs was conducted using quantitative methods and indices. Elements such as silhouettes, color palettes, and structural characteristics were analyzed in order to identify models for reinterpretation of classic fashion costume. Clothing from four historical periods was studied: Empire, Romanticism, the Victorian era, and Art Nouveau. An image processing algorithm was proposed, through which data on the shapes and colors of historical and contemporary clothing were obtained from digital color images. The most informative of the shape and color indices of contemporary and historical clothing were selected using the RReliefF, FSRNCA, and SFCPP methods. The feature vectors were reduced using the latent variable and t-SNE methods. The obtained data were used to group the clothing according to historical periods. Using Euclidean distances, the relationship between clothing by contemporary designers and the elements of the historical costume used by them was determined. These results were used to create an educational and methodological framework for practical training of students in the field of fashion design. The results of this work can help contemporary designers in interpreting and integrating elements of historical fashion into their collections, adapting them to the needs and preferences of consumers. Full article
(This article belongs to the Special Issue Trends in Artificial Intelligence-Supported E-Learning)
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18 pages, 1638 KiB  
Article
Decoding Success: The Role of E-Learning Readiness in Linking Technological Skills and Employability in Hospitality Management Graduates
by Ibrahim A. Elshaer, Alaa M. S. Azazz, Abuelkassem A. A. Mohammad and Sameh Fayyad
Information 2025, 16(1), 47; https://doi.org/10.3390/info16010047 - 14 Jan 2025
Viewed by 1007
Abstract
Technological advancement alongside global epidemics stimulated the widescale implementation of e-learning. However, it is reported that e-learning is in the experimental phase and still requires fundamental improvements, particularly in disciplines that go beyond theoretical knowledge. The current study examines the nexus between e-learning [...] Read more.
Technological advancement alongside global epidemics stimulated the widescale implementation of e-learning. However, it is reported that e-learning is in the experimental phase and still requires fundamental improvements, particularly in disciplines that go beyond theoretical knowledge. The current study examines the nexus between e-learning readiness, psychological motivation, technological skills, and employability skills among hospitality management undergraduates. It also explores the moderating effects of student engagement on the linkages among these variables. To that end, this study adopted a quantitative approach and used a self-administered questionnaire survey to collect primary data. The sample included a total of 428 participants who were recruited from undergraduates of hospitality management programs in Egyptian universities using the convenience sampling technique. Data analysis included performing PLS-SEM using Smart PLS 3.0 software. The results confirm the positive effects of psychological motivation and technological skills on both e-learning readiness and the employability skills of hospitality management undergraduates. The study also underscores the mediated role of e-learning readiness in the linkages between study predictors and outcomes. Additionally, the findings highlight the moderating effect of student engagement in supporting e-learning readiness and eventually employability skills. This study adds to the hospitality management body of knowledge and provides valuable insights for education institutions and policymakers to optimize e-learning experiences. Full article
(This article belongs to the Special Issue Trends in Artificial Intelligence-Supported E-Learning)
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Review

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28 pages, 404 KiB  
Review
Methodological and Technological Advancements in E-Learning
by Elias Dritsas and Maria Trigka
Information 2025, 16(1), 56; https://doi.org/10.3390/info16010056 - 15 Jan 2025
Cited by 1 | Viewed by 2442
Abstract
The present survey examines the intersection of methodological advancements and technological innovations in e-learning, emphasizing their transformative impact on modern education. It systematically explores instructional design frameworks, adaptive learning systems, immersive technologies, and data-driven analytics, highlighting their role in fostering personalized, scalable, and [...] Read more.
The present survey examines the intersection of methodological advancements and technological innovations in e-learning, emphasizing their transformative impact on modern education. It systematically explores instructional design frameworks, adaptive learning systems, immersive technologies, and data-driven analytics, highlighting their role in fostering personalized, scalable, and inclusive learning environments. Through the integration of pedagogical theories with advanced tools like artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and mixed reality (MR), this study demonstrates how e-learning systems enhance engagement, retention, and accessibility. The survey addresses critical challenges such as the digital divide, data privacy, and resistance to adoption, offering evidence-based strategies to mitigate these issues. It underscores the importance of bridging equity gaps while maintaining scalability and sustainability, particularly in underserved regions. By synthesizing state-of-the-art research and practical applications, this work provides actionable insights into the future of e-learning, advocating for a balanced approach to innovation that aligns technological capabilities with the diverse needs of global learners. The findings contribute to the broader discourse on sustainable, inclusive, and effective digital education ecosystems. Full article
(This article belongs to the Special Issue Trends in Artificial Intelligence-Supported E-Learning)
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