Acta Scientific Computer Sciences

Research Article Volume 4 Issue 5

An Intuitive Implementation of Course Recommendation System Based on Learner's Personality

Asad Jatoi, Memoona Sami*, Muzamil Nawaz and Junaid Baloch

Department of Software Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan

*Corresponding Author: Memoona Sami, Department of Software Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan.

Received: March 16, 2022; Published: April 20, 2022

Abstract

The work covered in this study concerns learner classification; a learner can be divided into numerous groups based on how comfortable he or she is with the course. In a broader sense, a learner can be theoretical, practical, or hybrid: a mix of the two. The research will use the Nave Bayes method to determine the degree of excellence of learners in their recognized learning style in a particular competency once the learner's type has been determined. The level of quality is divided into four categories: exceptional, good, medium, and fair. Recommendation will be given to the student for further improvements within the skillset or for newer skills once the classification of the learner in a category has been determined, as well as his or her level of proficiency in the area. The study places a greater emphasis on determining a learner's learning style because it is so important to the study. The research's main building block is the identification of learning styles, as the second portion of the research's recommendation is entirely based on superior categorization results.


Keywords: Classification; Algorithm; Recommendation System; Naïve Bayes; Learning Style

References

  1. Yu Haixia., et al. "Artificial Intelligence-Based Quality Management and Detection System for Personalized Learning”. Journal of Interconnection Networks (2021): 2143004.
  2. “Types of Learners in a college” 2021).
  3. “Working of Naive Bayes Algorithm?” (2021).
  4. Sáiz-Manzanares María Consuelo., et al. "Teaching and learning styles on moodle: An analysis of the effectiveness of using stem and non-stem qualifications from a gender perspective”. Sustainability3 (2021): 1166.
  5. “Top 6 Regression Algorithms” (2021).
  6. Monsalve-Pulido Julián., et al. "Autonomous recommender system architecture for virtual learning environments”. Applied Computing and Informatics (2020).
  7. Bourkoukou Outmane., et al. "A personalized e-learning based on recommender system”. International Journal of Learning and Teaching2 (2016): 99-103.
  8. AK Milićević. “E-Learning personalization based on hybrid recommendation strategy and learning style identification”. Computers and Education3 (2011): 885-899.
  9. Dascalu Maria-Iuliana., et al. "A recommender agent based on learning styles for better virtual collaborative learning experiences”. Computers in Human Behavior 45 (2015): 243-253.
  10. Monsalve-Pulido Julián., et al. "Autonomous recommender system architecture for virtual learning environments”. Applied Computing and Informatics (2020).
  11. Dorça Fabiano A., et al. "An Automatic and Dynamic Approach for Personalized Recommendation of Learning Objects Considering Students Learning Styles: An Experimental Analysis”. Informatics in Education1 (2016): 45-62.
  12. Noor Rizwana and Farman Ali Khan. "Personalized recommendation strategies in mobile educational systems”. 2016 Sixth International Conference on Innovative Computing Technology (INTECH). IEEE, (2016).
  13. Laksitowening K A., et al. "E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education”. Journal of Physics: Conference Series 1 (2017).
  14. TA Syed and V Palade. “A Personalized Learning Recommendation System Architecture for Learning Management System” (2017).
  15. Ramya Sree, P., et al. "Personalized e-learning system based on user’s performance and knowledge: an adaptive technique”. International Journal of Recent Technology and Engineering4 (2019): 8695.
  16. Sami Memoona., et al. “LERNEN, Connecting Professionals and Students”. In the 14th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2019), Beijing, China, June 2019.
  17. Wei Xin., et al. "Personalized Online Learning Resource Recommendation Based on Artificial Intelligence and Educational Psychology”. Frontiers in Psychology 12 (2021): 767837-767837.
  18. Bulger Monica. "Personalized learning: The conversations we’re not having”. Data and Society1 (2016): 1-29.
  19. Zhou Yuwen., et al. "Personalized learning full-path recommendation model based on LSTM neural networks”. Information Sciences 444 (2018): 135-152.
  20. SAddAR SALAHuddin., et al. "Evaluating Performance of Hibernate ORM based Applications using HQL Query Optimization”. Oriental Journal of Computer Science and Technology2 (2018): 115-125.
  21. Qureshi Umair Mujtaba., et al. "Indoor localization using wireless fidelity (WiFi) and bluetooth low energy (BLE) signals”. 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE). IEEE, (2019).

Citation

Citation: Memoona Sami., et al. “An Intuitive Implementation of Course Recommendation System Based on Learner's Personality". Acta Scientific Computer Sciences 4.5 (2022): 37-42.

Copyright

Copyright: © 2022 Memoona Sami., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days

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