Learning Analytics, Educational Data Science, and Artificial Intelligence in Technology-Enhanced Education
A Special Issue of Applied Sciences (ISSN 2076-3417) belonging to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 January 2027 | Viewed by 185
Editors
Interests: artificial intelligence in education; learning analytics; educational data science; digital competence; teacher education; technology-enhanced learning; educational innovation; generative AI in education; educational assessment; higher education; digital transformation; educational research methods
Interests: artificial intelligence in education; learning analytics; educational data science; digital competence; teacher education; technology-enhanced learning; educational innovation; generative AI in education
Interests: human-computer interaction; computer supported collaborative learning; ICT on education
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid expansion of digital technologies, artificial intelligence, learning analytics, and educational data mining is transforming teaching, learning, and assessment across educational contexts. Technology-enhanced education generates large volumes of multimodal data that can provide valuable insights into learner behaviors, engagement, performance, self-regulation, and learning trajectories. The analysis of these data offers opportunities to improve educational decision-making, personalize learning experiences, support student success, and optimize institutional processes.
This Special Issue aims to bring together recent advances in learning analytics, educational data science, artificial intelligence, machine learning, and technology-enhanced learning. It seeks contributions that explore innovative methods, models, frameworks, and applications for collecting, processing, analyzing, visualizing, and interpreting educational data in formal, non-formal, and lifelong learning environments.
We welcome original research, systematic reviews, meta-analyses, case studies, and methodological contributions addressing the design, implementation, and evaluation of data-driven educational technologies. Particular attention will be given to studies that demonstrate practical implications for improving learning outcomes, educational quality, learner support, digital competence development, and evidence-based educational innovation.
Prof. Dr. Odiel Estrada Molina
Prof. Dr. Alién García Hernández
Prof. Dr. César A. Collazos
Guest Editors
Manuscript Submission Information
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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
- learning analytics
- artificial intelligence in education
- educational data mining
- higher education
- teacher education
- digital competence
- generative artificial intelligence
- technology-enhanced learning
- learning technologies
- educational innovation
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