Big Data and E-learning
A special issue of Data (ISSN 2306-5729). This special issue belongs to the section "Information Systems and Data Management".
Deadline for manuscript submissions: closed (30 October 2021) | Viewed by 16665
Special Issue Editors
Interests: machine learning; artificial intelligence; e-learning; programming languages
Special Issues, Collections and Topics in MDPI journals
Interests: learning engineering; e-learning; collaborative learning; artificial intelligence; distributed computing; software engineering
Interests: e-learning; artificial intelligence; educational technology; computational linguistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the last decade, the Big Data phenomenon has facilitated access to enormous amounts of data on various areas of knowledge. In particular, in the field of eLearning, it is possible to access a wide variety of data on the interactions that occur in the learning process, such as data about accesses to learning management systems (activities, courses, resources, etc.), contents most visited by students, most valued resources, paths of navigation carried out by a student, etc. All this information can be exploited using machine learning techniques or artificial intelligence to obtain valuable information such as behavior patterns, predictions about grades, adaptive learning paths to students, etc. In this sense, data analysis techniques applied to the field of eLearning constitute a critical area to improve the learning–teaching process and the interactions that take place in eLearning environments.
In this Special Issue, we are interested in receiving contributions on descriptions of data sets of the eLearning area that can be exploited, analysis of data on large datasets related to eLearning, applications of artificial intelligence or machine learning techniques that use data from the field of eLearning, and other experiences that are related to the field of Big Data applied to eLearning.
Dr. Antonio Sarasa-Cabezuelo
Dr. Santi Caballé Llobet
Dr. Ana Fernández-Pampillón Cesteros
Dr. Joaquín Gayoso Cabada
Guest Editors
Manuscript Submission Information
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Keywords
- eLearning datasets
- Machine learning for eLearning
- Learning analytics and educational data mining
- Personalized learning paths
- Adaptive learning
- Deep learning for eLearning
- Artificial intelligence, knowledge management in eLearning and real-time streaming processes
- Data acquisition, integration, cleaning, and best practices
- Computational modeling, data integration, and cloud computing
- Algorithms and systems for big data search
- Visualization analytics for big data
- Analysis of data from MOOCs
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