Co-occurrence patterns of issues and guidelines related to ethics and privacy of learning analytics in higher education—literature review (CROSBI ID 716184)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Šlibar, Barbara ; Gusić Munđar, Jelena ; Rako, Sabina ; Šimić, Diana
engleski
Co-occurrence patterns of issues and guidelines related to ethics and privacy of learning analytics in higher education—literature review
Ethics and privacy issues have been recognized as important factors for acceptance and trustworthy implementation of learning analytics. A large number of different issues has been recognized in the literature. Guidelines related to these issues are continuously being developed and discussed in research literature. The aim of this research was to identify patterns of co-occurrence of issues and guidelines in research papers discussing ethics and privacy issues, to gain better understanding of relationships between different ethics and privacy issues arising during implementation of learning analytics in higher education. A total of 93 papers published between 2010 and 2021 were qualitatively analyzed, and nine categories of issues and respective guidelines related to ethics and privacy in learning analytics were identified. Association rules mining Apriori algorithm was applied, where 93 papers represented transactions, and 18 categories of issues or guidelines (nine each) represented items. Two clusters of issues co- occurring in papers were identified, corresponding to deontology ethics (related to rules and duties), and consequentialism ethics (related to consequences of unethical behavior).
Learning analytics ; Ethics ; Higher education ; Apriori algorithm
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
577-582.
2022.
objavljeno
10.1145/3506860.3506974
Podaci o matičnoj publikaciji
LAK22 Conference Proceedings Learning Analytics for Transition, Disruption and Social Change
Wise, Alyssa F. ; Martinez-Maldonado, Roberto ; Hilliger, Isabel
New York (NY): Association for Computing Machinery (ACM)
978-1-4503-9573-1
Podaci o skupu
LAK22: 12th International Learning Analytics and Knowledge Conference
predavanje
21.03.2022-25.03.2022
Sjedinjene Američke Države