Abstract:

Online education is gaining more popularity in adult learning and training in the recent years. This phenomenon is not surprising given that online learning allows education institutes to operate at a lower cost and with greater reach-out to more students. Each year, more and more educational institutions are offering courses online to leverage on the benefits of online learning. However, challenges appear with the implementation of online learning.

Identity verification of online learners is one of the key challenges to online learning today. Especially for online certification and accreditation, the training organisations need to verify that the online learners who completed the learning process and received the academic credits are the ones who registered for the courses. Inadequate methods of identity verification affect the credibility of credentials and certification earned online. Without certainty of the authenticity of the online learner’s identity, the aspiration towards fully online education is stymied and the evaluation of the knowledge and skills obtained by the online learner is unreliable. In order to prevent from compromising the credibility of online accreditation, validation must be done in a constant or continuous manner. At same time, validation should be non-invasive and non-disruptive to not distract from the learning process.

There have been several authentication technologies based on biometric features for some years. These technologies can be divided into two categories: those that are based on physical characteristics and those that are based on behaviour characteristics. Among others, the former includes face recognition, fingerprint scanners, irises scanners and vein matching. The latter includes voice recognition, handwriting recognition, keystroke dynamics, and so on. These biometric verification technologies have been widely used for various purposes, and they have become more and more common in our daily lives. However, very few of them have been successfully adopted for online learning validation due to various challenges.

This paper examines all these biometric technologies and analyzes the challenges of adopting these for online learning validation. With these, we present a new system called Smowl based on web applications with authentication ability. This system offers a continuous identity authentication service of online learners through a constant face recognition technology. The reliable authentication of the system allows online courses to gain values which in turn benefit both institutions and students. This solution is based on an accurate face recognition algorithm. It is contactless and only needs a low level of users' collaboration. As biometric traits cannot be lost, stolen, or recreated, this system can be used to continuously authenticate the learners, either throughout the entire learning process, or only at certain sensitive stages of e-learning. In addition, the whole system is based on cloud computing technologies, which overcomes geographical and technological barriers.

Smowl has been experienced in a Moodle virtual room of the Master Degree in Education and New Technologies of the Madrid Open University. In this work, 67 students were surveyed about the suitability of this technology. Among other questions, they were asked whether Smowl is appropriate to verify the identity of students while learning in Moodle, which obtained an average of 6.01 in a seven-point Likert scale.

Keywords:

e-learning, face recognition, certification, biometrics, student identification.