Article: Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments Journal: International Journal of Technology Enhanced Learning (IJTEL) 2020 Vol.12 No.2 pp.218 - 244 Abstract: Authentication plays a significant role in security during the non-venue-based examination, as it verifies the identity of online students. Existing authentication techniques have not yet provided an optimal cheating-free, non-venue-based assessment. This research proposes an emerging biometrics technology model of facial recognition and keystroke dynamics (FRAKD) to minimise the problems of malpractice during examinations significantly. Detailed experiments conducted on the Moodle learning management system (LMS), using a client-server platform of 100 diverse students who were captured as a positive data set, produced an average recognition rate (RR) of 85%, while for 20 imposter students, an average rejection rate of 90% was realised. When benchmarked with related solutions, this result shows that using the FRAKD biometrics model in non-venue-based assessment demonstrates reliable security and minimises impersonation more than state-of-the-art practices such as portfolio-based distance assessment without supervision. This improved solution will obviously have great value for ODeL institutions and examination bodies. Inderscience Publishers - linking academia, business and industry through research

Title: Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments

Authors: Prince Yaw Owusu Amoako; Isaac Olusegun Osunmakinde

Addresses: School of Computing, College of Science, Engineering and Technology, University of South Africa, Unisa 0003, Pretoria, South Africa ' School of Computing, College of Science, Engineering and Technology, University of South Africa, Unisa 0003, Pretoria, South Africa

Abstract: Authentication plays a significant role in security during the non-venue-based examination, as it verifies the identity of online students. Existing authentication techniques have not yet provided an optimal cheating-free, non-venue-based assessment. This research proposes an emerging biometrics technology model of facial recognition and keystroke dynamics (FRAKD) to minimise the problems of malpractice during examinations significantly. Detailed experiments conducted on the Moodle learning management system (LMS), using a client-server platform of 100 diverse students who were captured as a positive data set, produced an average recognition rate (RR) of 85%, while for 20 imposter students, an average rejection rate of 90% was realised. When benchmarked with related solutions, this result shows that using the FRAKD biometrics model in non-venue-based assessment demonstrates reliable security and minimises impersonation more than state-of-the-art practices such as portfolio-based distance assessment without supervision. This improved solution will obviously have great value for ODeL institutions and examination bodies.

Keywords: emerging technology; distance learning; agent; authentication; biometrics; learning management system; security; assessment.

DOI: 10.1504/IJTEL.2020.106287

International Journal of Technology Enhanced Learning, 2020 Vol.12 No.2, pp.218 - 244

Received: 10 Apr 2018
Accepted: 12 Nov 2018
Published online: 02 Apr 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments

Keep up-to-date