International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 7, Issue 11 (November 2020), Pages: 10-24

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 Original Research Paper

 Title: Employing artificial intelligence techniques for student performance evaluation and teaching strategy enrichment: An innovative approach

 Author(s): Lalbihari Barik *, Omar Barukab, Adel Ali Ahmed

 Affiliation(s):

 Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Rabigh 21911, Jeddah, Saudi Arabia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-5977-6319

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2020.11.002

 Abstract:

An intelligent tutoring system is an excellent Artificial Intelligence (AI) alternative for the haunting problems of the teaching and evaluation system in university education. It evinces a paradigm shift in the current system by employing AI techniques to evaluate students’ performance and enrich the myriad teaching strategies. Unlike in regular classes where a teacher has to control 30 to 50 students, a teacher has to monitor hundreds of students, which is quite difficult and mentally exhausting. In such circumstances, mentors or teachers alone are not enough for monitoring the students and offering each student’s optimum attention and care. A new and original approach is needed to facilitate reliable and flexible methods of university student monitoring systems. The system should be able to evaluate the performance of many students, predict the final grade, and formulate intelligent decisions in real-time. Several computer-based models of AI are progressively performing an important role in teaching and performance evaluation of students. This paper proposes a new strategy to illustrate the advantages of applying AI techniques to predict the final grade of students. The validation process was carried out with the real-time 1000 students’ dataset of 12 core and 18 elective courses in Bachelor of Computer Science during the academic year 2018-2019. In this paper, hybrid SVM with a Fuzzy Expert System is proposed to show the techniques proficiency for teaching and students’ final grade prediction and the possibility of future work. 

 © 2020 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Intelligent tutoring systems, Student performance, Teaching strategies, AI techniques

 Article History: Received 9 February 2020, Received in revised form 12 May 2020, Accepted 27 June 2020

 Acknowledgment:

This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. G-446-830-34. The authors, therefore, acknowledge with DSR technical and financial support.

 Compliance with ethical standards

 Conflict of interest: The authors declare that they have no conflict of interest.

 Citation:

 Barik L, Barukab O, and Ahmed AA (2020). Employing artificial intelligence techniques for student performance evaluation and teaching strategy enrichment: An innovative approach. International Journal of Advanced and Applied Sciences, 7(11): 10-24

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10 Table 11 Table 12 Table 13 

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