Identification of Students' Professional Competence Based on Big Data and Digital Footprints Based on Big Data Analytics and E-proctoring System
2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022
; : 277-280, 2022.
Article
in English
| Scopus | ID: covidwho-1961429
ABSTRACT
In the age of the digital society formation in countries of the post-industrial development stage, digital transformations take place in all spheres of public life. Such social institution as education witnesses especially drastic changes. New learning formats are emerging, including Online learning, E-learning, Smart-learning, Smart Education and other distance learning forms. However, during the COVID-19 pandemic, the scientific and educational community updated a number of issues regarding the identification of works, assessing the level of comprehensibility of the discipline and the independence of completing individual tasks of distance learning students. The present research is intended to complement the range of relevant studies in this area as it is devoted to the methodology of Big Data Analytics and e-proctoring at higher education institutions. The results of this study will help to improve the understanding of the algorithm for the final certification of students. In addition, the subjects of the educational process will be able to improve their skills in solving the problems of conducting final and intermediate certification in the format of distance learning and optimize this process in educational institutions of various levels. © 2022 IEEE.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022
Year:
2022
Document Type:
Article
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