Educational data mining and learning analytics for 21st century higher education: A review and synthesis
By Hanan Aldowah, Hosam Al-Samarraie, Wan Mohamad Fauzy. Telematics and informatics, 2019
402 citations recorded by the source corpus.
Abstract The potential influence of data mining analytics on the students’ learning processes and outcomes has been realized in higher education. Hence, a comprehensive review of educational data mining (EDM) and learning analytics (LA) in higher education was conducted. This review covered the most relevant studies related to four main dimensions: computer-supported learning analytics (CSLA), computer-supported predictive analytics (CSPA), computer-supported behavioral analytics (CSBA), and computer-supported visualization analytics (CSVA) from 2000 till 2017. The relevant EDM and LA techniques were identified and compared across these dimensions. Based on the results of 402 studies, it was found that specific EDM and LA techniques could offer the best means of solving certain learning problems. Applying EDM and LA in higher education can be useful in developing a student-focused strategy and providing the required tools that institutions will be able to use for the purposes of continuous improvement.
Subfields: Computer Science Applications, Health Information Management, Organizational Behavior and Human Resource Management
View Paper: https://www.semanticscholar.org/paper/6f715e8bbdc69840eb6fe40357b092739da02f12
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In Computer Science Applications
Citations in the corpus
- Challenges and Future Directions of Big Data and Artificial Intelligence in Education (2020, background): “34), are often implemented to analyze these huge amounts of data (Aldowah et al., 2019).”
- Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century (2021, background): “Trigg ring the developments in educational data mining and learning analytics, the use of de p learning and machine learning enabled evaluation, assessment, and monitorin of students’ learning [49,50].”