Application of Data Management and Semantic Technologies in Education
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 March 2026 | Viewed by 5
Special Issue Editors
Interests: data management in education; automated programming assessment systems; personalized and adaptive learning systems
Special Issues, Collections and Topics in MDPI journals
Interests: ICT in higher education; educational data management; personalized and adaptive learning; educational data mining and learning analytics and generative AI in education
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the transformative role of semantic technologies, AI, and data-driven methods in modern education. As learning increasingly shifts to digital and hybrid environments, the integration of ontologies, linked data, and knowledge graphs enables more intelligent, structured, and interoperable learning systems. At the same time, the rise of learning analytics, educational data mining, and machine learning has paved the way for personalized and adaptive education.
We welcome contributions to explore how data management practices and semantic enrichment can enhance educational content, delivery, and assessment. Of particular interest are applications of automated programming assessment systems, e-learning and m-learning platforms, and technologies aimed at ensuring academic integrity and preventing plagiarism.
By fostering collaboration across disciplines such as computer science, education, and data science, this Special Issue aims to highlight cutting-edge solutions that are reshaping how we teach, learn, and evaluate knowledge in the digital age.
- Semantic technologies and ontologies in learning systems
- Data management in education
- Learning analytics and educational data mining
- AI and machine learning in education
- e-Learning and m-Learning
- Automated programming assessment systems
- Technologies for academic integrity and plagiarism detection
- Personalized and adaptive learning systems
- Linked data and knowledge graphs in education
Prof. Dr. Ljiljana Brkić
Dr. Maria João Ferreira
Guest Editors
Manuscript Submission Information
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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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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
- semantic technologies
- data management
- data mining
- learning systems
- education
- artificial intelligence
- machine learning
- knowledge graphs
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