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Continuous user identification in distance learning: a recent technology perspective

delete2023-07-26
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OA
AI
D
David Portugal *
J
José N. Faria
M
Marios Belk
P
Pedro Martins
A
Argyris Constantinides
A
Anna Maria Pietron
A
Andreas Pitsillides
N
Nikolaos Avouris
C
Christos Fidas
DOI:10.1186/s40561-023-00255-9delete
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Abstract

Abstract

En 中文
The worldwide shift to distance learning at Higher Education Institutions (HEIs) during the COVID-19 global pandemic has raised several concerns about the credibility of online academic activities, especially regarding student identity management. Traditional online frameworks cannot guarantee the authenticity of the enrolled student, which requires instructors to manually verify their identities, a time-consuming task that compromises academic quality. This article presents a comprehensive review of existing efforts around continuous user identification, focusing on intelligent proctoring systems and automatic identification methods, as well as their applicability in this domain. We conclude that there is a clear need for continuous user identification technology by HEIs, but existing systems lack agile system integration models that combine many inputs, such as face, voice and behavioural data in a practical manner, and encounter numerous barriers related to data protection during implementation.
Keywords:
Continuous user identification
Distance learning
Intelligent proctoring systems
Image-based identification
Voice-based identification
Biometrics
Data privacy-preservation

Journal

S
Smart Learning Environments
IF:
12.1
Papers:
360
Citations:
2.4K

Organization

U
University of Cyprus
Scholars:
4.3K
Papers: 5.0K
Citations: 3
U
universidade de coimbra
Scholars:
1.9W
Papers: 1.6W
Citations: 16
U
University of Patras
Scholars:
1.2W
Papers: 9.6K
Citations: 8.4K
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