TY - JOUR
T1 - The influence of conception paradigms on data protection in E-Learning platforms:
T2 - a case study
AU - Kiennert, Christophe
AU - De Vos, Nathan
AU - Knockaert, Manon
AU - Garcia-Alfaro, Joaquin
N1 - Funding Information:
Our analysis will be illustrated with an e-assessment system called TeSLA (Adaptative Trust-based e-assessment System for Learning), designed through a H2020 project funded by the European Commission. This system relies on several anti-cheating countermeasures which consist in the real-time gathering of several biometric samples to ensure the authentication of the learner during the whole remote assessment session. This process allows the university instructors to be convinced of the learner’s identity when grading the assessment. However, biometric samples are regarded as highly
Funding Information:
This work was supported in part by the H2020-ICT-2015/H2020-ICT-2015 TeSLA Project An Adaptive Trust-based e-assessment System for Learning under Grant 688520, and in part by the European Commission (H2020 SPARTA Project) under Grant 830892.
Publisher Copyright:
© 2013 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - The wide adoption of virtual learning environments such as Moodle in numerous universities illustrate the growing trend of e-learning development and diffusion. These e-learning environments alter the relationship between the students and academic knowledge and learning processes considerably stimulating the students' autonomy by making most of the course material freely available at any time while inducing a progressive reduction of physical student-teacher interactions with virtual ones. Recent advances, as proposed in the TeSLA project, even introduces an e-assessment environment. This entire virtual learning framework raises new concerns in terms of privacy, given that such environments are potentially able to track the students, profile their habits, and retrieve personal data. In this paper, we analyze the influence of conception paradigms of e-learning platforms on personal data protection, based on a classification of these platforms in two antagonistic approaches. We illustrate our analysis with a case study of the TeSLA project and examine how the design choices impact the efficiency and legal compliance of personal data protection means. We finally propose alternative designs that could lead to significant improvements in this matter.
AB - The wide adoption of virtual learning environments such as Moodle in numerous universities illustrate the growing trend of e-learning development and diffusion. These e-learning environments alter the relationship between the students and academic knowledge and learning processes considerably stimulating the students' autonomy by making most of the course material freely available at any time while inducing a progressive reduction of physical student-teacher interactions with virtual ones. Recent advances, as proposed in the TeSLA project, even introduces an e-assessment environment. This entire virtual learning framework raises new concerns in terms of privacy, given that such environments are potentially able to track the students, profile their habits, and retrieve personal data. In this paper, we analyze the influence of conception paradigms of e-learning platforms on personal data protection, based on a classification of these platforms in two antagonistic approaches. We illustrate our analysis with a case study of the TeSLA project and examine how the design choices impact the efficiency and legal compliance of personal data protection means. We finally propose alternative designs that could lead to significant improvements in this matter.
KW - E-learning
KW - data protection
KW - privacy
UR - http://www.scopus.com/inward/record.url?scp=85066429459&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2915275
DO - 10.1109/ACCESS.2019.2915275
M3 - Article
VL - 7
SP - 64110
EP - 64119
JO - IEEE Access
JF - IEEE Access
M1 - 8708177
ER -