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DOI: 10.14569/IJACSA.2022.0130772
PDF

Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization

Author 1: Ayman E. khedr
Author 2: Abdulwahab Ali Almazroi
Author 3: Amira M. Idrees

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 7, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: In education sector, personalization is an evolutionary term that gained a high attention due to its effectiveness in raising the enterprise competence level. This research aims at proposing a novel model for effective smart testing, which considers the student’s Facebook activities in determining the students’ personality and constructing his suitable exam. The aim of this examination perspectives to ensure the reliable student evaluation according to his gained knowledge to ensure that no other factor interferes which may negatively affect the reliable evaluation. The research also applies text analytics techniques to ensure the exam balance. The proposed model has been applied and evaluated with professors’ percentage equal to 96.5 % and successfully reach students satisfaction percentage with average equal to 96.63%.

Keywords: Personalization; data mining; sentiment analysis; social networks; e-learning

Ayman E. khedr, Abdulwahab Ali Almazroi and Amira M. Idrees, “Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization” International Journal of Advanced Computer Science and Applications(IJACSA), 13(7), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130772

@article{khedr2022,
title = {Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130772},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130772},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {7},
author = {Ayman E. khedr and Abdulwahab Ali Almazroi and Amira M. Idrees}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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