TY - GEN
T1 - TRUSTID
T2 - 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2023
AU - Constantinides, Argyris
AU - Faria, José
AU - Sousak, Taoufik
AU - Martins, Pedro
AU - Portugal, David
AU - Belk, Marios
AU - Pitsillides, Andreas
AU - Fidas, Christos
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/6/26
Y1 - 2023/6/26
N2 - Online learning and remote assessment of students within Higher Education Institutions (HEIs) have shown significant growth over the last few years since the COVID-19 outbreak. In this context, the shift of various HEIs to online teaching and evaluation introduced several challenges, especially with relation to student identification and interaction behavior within critical online academic activities (e.g., examinations). To overcome these challenges, existing solutions relied on a combination of an online examination through a learning management system (LMS) with a basic user authentication method for identification of students, and video conference tools for manual monitoring of students. However, such solutions fall short in dealing with various threat scenarios, and cannot be easily integrated and modified by HEIs. In this paper, we present the development and initial usability and user experience evaluation of the proof of concept of a multi-tier continuous user identification framework, bootstrapped to HEI contexts, that consists of state-of-the-art intelligent image and voice biometrics. The suggested solution is currently being implemented and evaluated by the European Commission as part of the actions of ERASMUS+ 2020 and in particular the Call "Strategic Partnerships in Response to the COVID-19 Situation: Partnerships for Digital Education Readiness in the field of Higher Education (KA226)".
AB - Online learning and remote assessment of students within Higher Education Institutions (HEIs) have shown significant growth over the last few years since the COVID-19 outbreak. In this context, the shift of various HEIs to online teaching and evaluation introduced several challenges, especially with relation to student identification and interaction behavior within critical online academic activities (e.g., examinations). To overcome these challenges, existing solutions relied on a combination of an online examination through a learning management system (LMS) with a basic user authentication method for identification of students, and video conference tools for manual monitoring of students. However, such solutions fall short in dealing with various threat scenarios, and cannot be easily integrated and modified by HEIs. In this paper, we present the development and initial usability and user experience evaluation of the proof of concept of a multi-tier continuous user identification framework, bootstrapped to HEI contexts, that consists of state-of-the-art intelligent image and voice biometrics. The suggested solution is currently being implemented and evaluated by the European Commission as part of the actions of ERASMUS+ 2020 and in particular the Call "Strategic Partnerships in Response to the COVID-19 Situation: Partnerships for Digital Education Readiness in the field of Higher Education (KA226)".
KW - Biometric Recognition
KW - Learning Management Systems
KW - Online Academic Activities
KW - Usability and User Experience Evaluation.
UR - http://www.scopus.com/inward/record.url?scp=85163726829&partnerID=8YFLogxK
U2 - 10.1145/3563359.3597410
DO - 10.1145/3563359.3597410
M3 - Conference contribution
AN - SCOPUS:85163726829
T3 - UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
SP - 110
EP - 114
BT - UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
PB - Association for Computing Machinery, Inc
Y2 - 26 June 2023 through 30 June 2023
ER -
