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Dergiler / Turkish Online Journal of Distance Education / 2020 / Cilt: 21 - Sayı: Special Issue-IODL

EFFICIENCY OF BIOMETRIC RECOGNITION TECHNOLOGY BASED ON TYPING DYNAMICS IN MOOC

Manuel MEDINA-LABRADOR
Marcela Georgina GOMEZ-ZERMENO
Lorena Aleman DE LA GARZA
Sayfa
79–87
Yayın Tarihi
2020-07-17
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The results show that the keystroke is independent of the analyzed variables, and it is reliable to identify the students in qualitative tests with extension answers.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:One of the problems that require a solution in Massive Open Online Courses (MOOC) is the lack of identification and authentication of the students.
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Temel Bulgular & Veri:Different investigations have been carried out through several navigation, physiological and behavioral methods, achieving different recognition scales.
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Sonuç & Katkı:The results show that the keystroke is independent of the analyzed variables, and it is reliable to identify the students in qualitative tests with extension answers.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Biometrics · identification · MOOC

Abstract

One of the problems that require a solution in Massive Open Online Courses (MOOC) is the lack of identification and authentication of the students. Different investigations have been carried out through several navigation, physiological and behavioral methods, achieving different recognition scales. Biometric authentication by keystroke patterns (Ups&Downs) has been implemented in several MOOCs for the ease of the digital platforms of the offeror to solve the identification problem. The objective of this research is to analyze the independence of the keystroke tool of the other demographic, sociographic and behavioral variables within a MOOC, establishing an initial pattern, and two authentication measurements throughout the course. The results show that the keystroke is independent of the analyzed variables, and it is reliable to identify the students in qualitative tests with extension answers.

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Bu Makaleye Atıf Yap

MEDINA-LABRADOR, M., GOMEZ-ZERMENO, M. G., GARZA, L. A. D. L. (2020). EFFICIENCY OF BIOMETRIC RECOGNITION TECHNOLOGY BASED ON TYPING DYNAMICS IN MOOC. Turkish Online Journal of Distance Education, Cilt: 21 - Sayı: Special Issue-IODL, 79–87. https://ajindex.com/articles/137591

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Kaynakça (9)

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