International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Intelligent Automated Cognitive-Maturity Recognition System for Confidence Based E-Learning

  • Usman, Imran (College of Computing and Informatics, Saudi Electronic University) ;
  • Alhomoud, Adeeb M. (College of Science and Theoretical Studies, Saudi Electronic University)
  • Received : 2021.04.05
  • Published : 2021.04.30
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Abstract

As a consequence of sudden outbreak of COVID-19 pandemic worldwide, educational institutes around the globe are forced to switch from traditional learning systems to e-learning systems. This has led to a variety of technology-driven pedagogies in e-teaching as well as e-learning. In order to take the best advantage, an appropriate understanding of the cognitive capability is of prime importance. This paper presents an intelligent cognitive maturity recognition system for confidence-based e-learning. We gather the data from actual test environment by involving a number of students and academicians to act as experts. Then a Genetic Programming based simulation and modeling is applied to generate a generalized classifier in the form of a mathematical expression. The simulation is derived towards an optimal space by carefully designed fitness function and assigning a range to each of the class labels. Experimental results validate that the proposed method yields comparative and superior results which makes it feasible to be used in real world scenarios.

Keywords

Acknowledgement

The authors highly extend their appreciation and acknowledgement to the Deanship of Scientific Research (DSR) at Saudi Electronic University, Riyadh, Saudi Arabia, for funding this work through the grant for the project titled "Intelligent automated Cognitive-maturity recognition system for confidence based e-learning".

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