Thesis supervisor: Edit Laufer
Location of studies (in Hungarian): Óbuda University - Donát Bánki Faculty of Mechanical and Safety Engeneering - 1081 Budapest, Népszínház str. 8. Abbreviation of location of studies: ÓEBGK
Description of the research topic:
Due to the rapid development of technology, significant improvements in educational technology have also begun. The main question is how can we maximize the learning effectiveness, support differentiated instruction, raise the limits of endurance, and maintain the motivation. Big Data analysis ensures a great opportunity. In the system, the interaction, activity, response and time data of all students with each curriculum are recorded (log files), which databases (big data) can be used as a basis for the further development of adaptive learning support systems. To exploit the potential of learning analytics new methods are required combining the advantages of conventional and computational intelligence-based approaches taking into account the security issues.
Research purposes:
1. Application possibilities and dangers of big data in adaptive learning
2. Development and improvement of learning analytics methods
3. Development of computational intelligence-based methods to improve predictability
4. Addressing security issues
5. Performance evaluation
Required language skills: english B2
Deadline for application: 2022-08-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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