An Open Learning Environment for the Diagnosis, Assistance and Evaluation of Students Based on Artificial Intelligence

Authors

  • Maria Samarakou Department of Energy Technology, Technological Educational Institute (T.E.I.) of Athens, Ag. Spyridonos, 12210, Aegaleo, Greece
  • Andreas Papadakis Department of Electronic Engineering Educators, School of Pedagogical and Technological Education (ASPETE), Athens, Greece
  • Emmanouil D Fylladitakis Electronic & Computer Engineering, Brunel University London, UK
  • Antonios Hatziapostolou Department of Electronic Engineering Educators, School of Pedagogical and Technological Education (ASPETE), Athens, Greece
  • Grammatiki Tsaganou Department of Informatics and Telecommunications, University of Athens, Greece
  • Wolf Gerrit Früh School of Engineering and Physical Sciences, Heriot Watt University, Riccarton, Edinburgh EH14 4AS, UK

DOI:

https://doi.org/10.3991/ijet.v9i3.3367

Keywords:

Learning Environments (OLEs), Diagnosis, Evaluation, Artificial Intelligence (A.I.) assisted learning, elearning

Abstract


The personalized diagnosis, assistance and evaluation of students in open learning environments can be a challenging task, especially in cases that the processes need to be taking place in real-time, classroom conditions. This paper describes the design of an open learning environment under development, designed to monitor the comprehension of students, assess their prior knowledge, build individual learner profiles, provide personalized assistance and, finally, evaluate their performance by using artificial intelligence. A trial test has been performed, with the participation of 20 students, which displayed promising results.

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Published

2014-05-10

How to Cite

Samarakou, M., Papadakis, A., Fylladitakis, E. D., Hatziapostolou, A., Tsaganou, G., & Früh, W. G. (2014). An Open Learning Environment for the Diagnosis, Assistance and Evaluation of Students Based on Artificial Intelligence. International Journal of Emerging Technologies in Learning (iJET), 9(3), pp. 36–44. https://doi.org/10.3991/ijet.v9i3.3367

Issue

Vol. 9 No. 3 (2014)

Section

Papers

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