TY - JOUR
T1 - Privacidad, seguridad y legalidad en soluciones educativas basadas en Blockchain
T2 - Una Revisión Sistemática de la Literatura
AU - Filvà, Daniel Amo
AU - Alier, Marc
AU - García-Peñalvo, Francisco José
AU - Fonseca, David
AU - Casañ, María José
N1 - Publisher Copyright:
© 2020, Ibero-American Association for Distance Higher Education (AIESAD). All rights reserved.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Learning Analytics processes student data, even for students under 18. The analytical cycle consists of collecting data, storing it for long periods and using it for analysis and visualization. The more data, the better the analysis. This analysis can be descriptive, predictive and, even, prescriptive, which involves the management, processing and use of personal data. The educational context is, thus, very sensitive, unlike individual contexts where analysis is used at will. It is not clear how student data are being used by technology companies serving education and who is actually benefiting, how this will affect students in the short and long-term future, or what level of privacy or security is applied to protect student data. Therefore, and in relation to the above, analyzing educational data implies a sensitive and fragile context in the management and analysis of personal data of students, including minors, in which precautions must be maximized. This systematic review of the literature explores the importance of personal data protection and security in the field of education through the emerging promises of those interested in using blockchain technology. The results show that it is important to understand the implications and risks derived from the use of emerging technologies in education, their relationship with society and the current legislation.
AB - Learning Analytics processes student data, even for students under 18. The analytical cycle consists of collecting data, storing it for long periods and using it for analysis and visualization. The more data, the better the analysis. This analysis can be descriptive, predictive and, even, prescriptive, which involves the management, processing and use of personal data. The educational context is, thus, very sensitive, unlike individual contexts where analysis is used at will. It is not clear how student data are being used by technology companies serving education and who is actually benefiting, how this will affect students in the short and long-term future, or what level of privacy or security is applied to protect student data. Therefore, and in relation to the above, analyzing educational data implies a sensitive and fragile context in the management and analysis of personal data of students, including minors, in which precautions must be maximized. This systematic review of the literature explores the importance of personal data protection and security in the field of education through the emerging promises of those interested in using blockchain technology. The results show that it is important to understand the implications and risks derived from the use of emerging technologies in education, their relationship with society and the current legislation.
KW - confidentiality
KW - data protection laws
KW - education technology
KW - privacy and security for personal and educational data
UR - http://www.scopus.com/inward/record.url?scp=85095846852&partnerID=8YFLogxK
U2 - 10.5944/ried.23.2.26388
DO - 10.5944/ried.23.2.26388
M3 - Artículo
AN - SCOPUS:85095846852
SN - 1138-2783
VL - 23
SP - 213
EP - 236
JO - RIED-Revista Iberoamericana de Educacion a Distancia
JF - RIED-Revista Iberoamericana de Educacion a Distancia
IS - 2
ER -