Advertisement

Facial Authentication before and after Applying the Smowl Tool in Moodle

  • Francisco D. Guillén-GámezEmail author
  • Iván García-Magariño
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 290)

Abstract

In this work, a facial authentication system has been included examined, deployed and evaluated for students who study in distance higher education. Until today, there was hardly any technology that verified whether the students are themselves the ones in the realization of their activities within a LMS (Learning Management System) as Moodle. Currently, there are different technologies that identify people. One of them is biometrical facial authentication, which permits the authentication and verification of users based on facial features. Thanks to the new technologies’ contribution within the educational community, there is a possibility to verify that there are not frauds and to avoid the identity theft while the students do their activities in the platform; in order to demonstrate that e-learning is as accepted and recognized as any other kind of education. The main objective is to check the functionality degree of facial authentication of the Smowl tool in Moodle platform, to identify the attention degree and opinions in the students’ understanding, as well as to determine which kinds of activities have more acceptance before and after using the tool. In this work, 100 Master students were audited for the survey and the conclusions reached indicate a high acceptance of facial authentication as a technique to improve distance education, and that this perception of students improves even more after experiencing facial authentication when learning through Moodle rooms.

Keywords

Facial Recognition Distance Education Learn Management System Identity Theft Educational Data Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bliuc, A.M., Ellis, R.A., Goodyear, P., Piggott, L.: A blended learning Approach to teaching foreign policy: Student experiences of learning through face-to-face and online discussion and their relationship to academic performance. Computers & Education 56(3), 856–864 (2011)CrossRefGoogle Scholar
  2. 2.
    Race, P.: Open learning handbook: promoting quality in designing and delivering flexible learning. Kogan Page, London (1994)Google Scholar
  3. 3.
    Ong, C., Yu Lai, J., Wang, Y.: Factors affecting engineers’ acceptance of asynchronous elearning system in high tech companies. Information & Management 41, 795–804 (2004)CrossRefGoogle Scholar
  4. 4.
    Cotton, D., Gresty, K.: Reflecting on the think aloud method for evaluating elearning. British Journal of Educational Technology 37(1), 45–54 (2006)CrossRefGoogle Scholar
  5. 5.
    Merisotis, J.P., Phipps, R.A.: What’s the Difference?: Outcomes of Distance vs. Traditional Classroom-Based Learning. Change: The Magazine of Higher Learning 31(3), 12–17 (1999)CrossRefGoogle Scholar
  6. 6.
    Dougiamas, M., Taylor, P.: Moodle: Using learning communities to create an open source course management system. In: World Conference on Educational Multimedia, Hypermedia and Telecommunications, vol. 2003(1), pp. 171–178 (2003)Google Scholar
  7. 7.
    Smowl (2014) Smowl website, http://smowltech.com/es (last accessed April 03, 2014)
  8. 8.
    Dehnavi, M.K., Fard, N.P.: Presenting a multimodal biometric model for tracking the students in virtual classes. Procedia-Social and Behavioral Sciences 15, 3456–3462 (2011)CrossRefGoogle Scholar
  9. 9.
    Ullah, A., Xiao, H., Lilley, M.: Profile based student authentication in online examination. In: 2012 International Conference on Information Society (i-Society), pp. 109–113. IEEE (2012)Google Scholar
  10. 10.
    Pattanasethanon, P., Savithi, C.: Human Face Detection and Recognition using Web-Cam. Journal of Computer Science 8(9), 1585 (2012)CrossRefGoogle Scholar
  11. 11.
    Agulla, E.G., Rifón, L.A., Castro, J.L.A., Mateo, C.G.: Is My Student at the Other Side? Applying Biometric Web Authentication to E-Learning Environments. In: Eighth IEEE International Conference on Advanced Learning Technologies, ICALT 2008, pp. 551–553. IEEE (July 2008)Google Scholar
  12. 12.
    Grafsgaard, J.F., Wiggins, J.B., Boyer, K.E., Wiebe, E.N., Lester, J.C.: Automatically Recognizing Facial Expression: Predicting Engagement and Frustration. In: Proceedings of the 6th International Conference on Educational Data Mining (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Francisco D. Guillén-Gámez
    • 1
    Email author
  • Iván García-Magariño
    • 1
  1. 1.Department of Computer Engineering and Industrial Organization, Faculty of Technical SciencesOpen University of Madrid (UDIMA)Collado Villalba MadridSpain

Personalised recommendations