Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

  • Received : 2023.05.18
  • Accepted : 2023.10.03
  • Published : 2023.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study proposed an SCA advice system. It is an ontology-based recommender that provides advice on appropriate computer curricula based on the behavior of high school students. The three computer curricula at Chiang Mai Rajabhat University include computer science (CS), information technology (IT), and web programming and security (WEB). This study aims to design the ontology framework for an SCA advice system. The system considers three core ontologies: student, computer-curriculum, and advice. After analyzing student behaviors, the behavior types of CS, IT, and WEB were determined to be SB-2, SB-1, and SB-5, respectively. All subjects in these three curricula were analyzed and grouped into seven groups. Their curricula were synthesized in terms of basic skills, basic knowledge, and characteristics. Finally, advice results can be obtained by consolidating the curriculum nature of the CS, IT, and WEB curricula.

Keywords

References

  1. P. Melville and V. Sindhwani, Recommender Systems. IBM T.J. Watson Research Center, Yorktown Heights, USA, 2010, [Internet], Available: http://www.vikas.sindhwani.org/recommender.pdf.
  2. T. De Pessemier, S. Dooms, and L. Martens, "Design and evaluation of a group recommender system," in Proceedings of the Sixth ACM Conference on Recommender Systems (RecSys '12). ACM, Dublin, Ireland, pp. 225-228, 2012. DOI: 10.1145/2365952 .2366000.
  3. S. Maneeroj and A. Takasu, "Hybrid Recommender System Using Latent Features," in Proceedings. IEEE International Symposium on Mining and Web (MAW09), Bradford, UK, pp. 661-666, 2009. DOI: 10.1109/WAINA.2009.122.
  4. S. Napat, M. Buranarach, T. Supnithi, and N. Phornrhudee, "Ontology Development for Personalized Food and Nutrition Recommender System," 2010, [Internet], Available: http://text. hlt.nectec.or.th/marut/papers/foodontologyace2010cr.pdf.
  5. S. Tyagi and K. K. Bharadwaj, "A Hybrid Recommender System Using Rule-Based and Case-Based Reasoning," International Journal of Information and Electronics Engineering, vol. 2, no.4, pp. 586-590, Jul. 2012. [Online], Available: http://www. ijiee.org/papers/166-A10086.pdf. 10086.pdf
  6. G. Adomavicius, N. Manouselis, and Y. Kwon, "Multi-Criteria Recommender Systems," Recommender systems handbook, pp. 769-803, Oct. 2010. DOI: 10.1007/978-0-387-85820-3_24.
  7. G. Adomavicius and Y. Kwon, "New Recommendation Techniques for Multi-Criteria Rating Systems," IEEE Intelligent Systems, vol. 22, no. 3, pp. 48-55, May 2007. DOI: 10.1109/MIS.2007.58.
  8. F. Otaki, N. Matsatsinis, and A. Tsoukias, "Multi-Criteria User Modeling in Recommender Systems," 2010, [Internet], Available: http://www.lamsade.dauphine.fr/~tsoukias/papers/Lakiotakietal.pdf.
  9. K. Palanivel and R. Sivakumar, "Fuzzy multicriteria decision-making approach for Collaborative recommender systems," International Journal of Computer Theory and Engineering, vol. 2, no.1, pp. 1793-8201, Feb. 2010, [Online], Available: http:// www.ijcte.org/papers/117-G607.pdf.
  10. A. Akhtarzada, C. S. Calude, and J. Hosking, "A Multi-Criteria Metric Algorithm for Recommender Systems," 2011, [Internet], Available: http://www.cs.auckland.ac.nz/CDMTCS/researchre ports/400ali.pdf.
  11. M. Buranarach, T. Supnithi, Y. Thein, T. Ruangrajitpakorn, T. Rattanasawad, K. Wongpatikaseree, A. Lim, Y. Tan, and A. Assawamakin, "OAM: An Ontology Application Management Framework for Simplifying Ontology-Based Semantic Web Application Development," International Journal of Software Engineering and Knowledge Engineering, vol. 26, no. 01, pp. 115-145, Feb. 2016. DOI: 10.1142/S0218194016500066.
  12. E. Hurrell and A. F. Smeaton, "Context ontologies for recommending from the social web," in Proceedings of the 3rd Workshop on Context-awareness in Retrieval and Recommendation (CaRR '13). ACM, New York: NY, pp. 26-32, 2013. DOI: 10.1145/2442670.2442676.
  13. A. Sriprasert, "Knowledge Management System to Basic Machine Tools Using Ontology Technology," M.S. An Independent Study Report, King Mongkut's University of Technology, North Bangkok, Bangkok: TH, 2011.
  14. M. Fumagalli, G. Bella, S. Conti, and F. Giunchiglia, "Ontology-Driven Cross-Domain Transfer Learning," Formal Ontology in Information Systems, vol. 330, pp. 249-263, Oct. 2020. DOI: 10.3233/FAIA200676.
  15. C. Srimontree, "Personalize Information Discovery of E-Tourism Using Ontology-Base Metadata," M.S. An Independent Study Report, Khonkean University, Khonkean: TH 2011.
  16. W. Chotirat, P. Boonrawd, and S. NaWichian, "Developing an Ontology Knowledge Based for Automatic Online News Analysis," 2011, [Online], Available: http://suanpalm3.kmutnb. ac.th/journal/pdf/vol14/ch03.pdf.
  17. M. Oprea, "On Design of a Collaborative Ontology Development Methodology for Educational Systems," in Proceedings of the 7th Balkan Conference on Informatics Conference (BCI '15). ACM, New York: NY, pp. 1-7, 2015. DOI: 10.1145/2801081.2801103.
  18. Y. Terziev, M. Wickner, T. Bruckmann, and V. Gruhn, "Ontology-based recommender system for information support in knowledge-intensive processes," in Proceedings of the 15th International Conference on Knowledge Technologies and Data Driven Business (i-KNOW '15). ACM, New York: NY, pp. 1-8, 2015. DOI: 10.1145/2809563.2809600.
  19. A. Elbadrawy and G. Karypis, "Domain-Aware Grade Prediction and Top-n Course Recommendation," in Proceedings of the 10th ACM Conference on Recommender Systems (RecSys '16). ACM, New York: NY, pp.183-190, 2016. DOI: 10.1145/2959100.29591 33.
  20. B. Lerdsakooljinda and N. Utakrit, "Academic Degree Recommender System Case Study: Bangalore and Mysore District Karnataka and Delhi State of India By Content-Based Filtering Technique," 2011, [Online], Available: http://202.44.34.144/nccitedoc/nccit_files/NCCIT-20110806030216.pdf.
  21. L. Butthijak and S. Nuchitprasitchai, "Further Education, Decision Support System in Australian Universities," 2009, [Online], Available: http://202.44.34.144/nccitedoc/admin/nccit_files/NCCIT-20111404174747.pdf.
  22. C. Obeid, L. Inaya, H. Khoury, and P. Champin, "Ontology-based Recommender System in Higher Education," in Proceedings of The Web Conference, Lyon, France, pp. 1031-1034, 2018. DOI: 10.1145/3184558.3191533.
  23. M. Ibrahim, Y. Yanyan, and D. Ndzi, "Using ontology for personalised course recommendation applications," in International Conference on Computational Science and Its Applications-ICCSA 2017, vol. 10404, pp. 426-438, 2017. DOI: 10.1007/978-3-319-62392-4_31.
  24. M. E. Ibrahim, Y. Yang, D. L. Ndzi, G. Yang, and M. Al-Maliki, "Ontology-Based Personalized Course Recommendation Framework," IEEE Access, vol. 7, pp. 5180-5199, 2019. DOI: 10.1109/ACCESS.2018.2889635.
  25. A. M. Abdellah, A. M. Karim, and S. Hamid,, "Career Recommendation System for Scientific Students Based on Ontologies," Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 29-41, 2019. DOI: 10.25046/aj040404.
  26. S. Shishehchi and S. Y. Banihashem, "JRDP: A Job Recommender System Based on Ontology for Disabled People," International Journal of Technology and Human Interaction (IJTHI), vol. 15, no. 1, pp. 85-99, 2019. DOI: 10.4018/IJTHI.2019010106.
  27. A. Joury, "How Ontology and Data Go Hand-in-Hand," 2023, [Online], Available: https://builtin.com/data-science/ontology.
  28. J. Douceur, "Digital Twins Definition Language (DTDL)," 2023, [Online], Available: https://github.com/Azure/opendigitaltwins-dtdl/blob/master/DTDL/v3/DTDL.v3.md.
  29. Q. Bao, G. Zhao, Y. Yu, S. Dai, and W. Wang, "The ontology-based modeling and evolution of digital twin for assembly work shop," The International Journal of Advanced Manufacturing Technology, vol. 117, no. 1-2, pp. 395-411, Jul. 2021. DOI: 10.1007/s00170-021-07773-1.
  30. J. Yanchinda and F. Xu, "Ontology Creation based on Digital Transformation for Supply Chain Resilience," in Conference:2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), Phuket, Thailand, pp. 165-170. 2023. DOI:10.1109/ECTIDAMTNCON57770.2023.1013 9616.
  31. F. Zaoui and N. Souissi, "Onto-Digital: An Ontology-Based Model for Digital Transformation's Knowledge," International Journal of Information Technology and Computer Science (IJITCS), vol. 10, no. 12, pp. 1-12, Dec. 2018. DOI: 10.5815/ijitcs.2018.12.01.
  32. S. B. Gomes, F. M. Santoro, and M. Mira da Silva, "An Ontology for BPM in Digital Transformation and Innovation," International Journal of Information System Modeling and Design, vol. 11, no. 2, pp. 52-77, Apr. 2020. DOI: 10.4018/IJISMD.2020040103.
  33. S. Bowers and B. Ludascher, "An ontology-driven framework for data trans formation in scientific workflows," 2018, [Online] Available: https://www.slideshare.net/ludaesch/an-ontologydriven-framework-for-data-transformation-in-scientific-workflows.
  34. Y. Wu and E. Wu, "AI-based College Course Selection Recommendation System: Performance Prediction and Curriculum Suggestion," in International Symposium on Computer, Consumer and Control (IS3C), Taichung City, Taiwan, pp. 79-82, 2020. DOI: 10.1109/IS3C50286.2020.00028.
  35. G. George and A. M. Lal, "Review of ontology-based recommender systems in e-learning," Computers and Education, vol. 142, p. 103642. 2019. DOI: 10.1016/j.compedu.2019.103642.
  36. M. Guffaz, J. Deslis, and J. Moissinac, "Curriculum data enrichment with ontologies," In Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14) (WIMS '14). ACM, New York: NY, vol. 44, 6 pages, 2014, DOI: 10.1145/2611040.2611070.
  37. N. D. Rodriguez, M. P. Cuellar, J. Lilius, and M. D. Calvo-Flores, "A survey on ontologies for human behavior recognition," ACM Computing Surveys, vol. 46, no. 4, pp. 1-33, Mar. 2014. DOI: 10.1145/2523819.
  38. A. Ameen, K. U. R. Khan, and B. P. Rani, "Ontological student profile," in Proceedings of the Second International Conference on Computational Science, Engineering and Information (CCSEIT '12), Coimbatore UNK, India, pp. 466-471, 2012. DOI: 10.1145/2393216.2393294.
  39. M. Sharma and L. Ahuja, "A Novel and Integrated Semantic Recommendation System for E-Learning using Ontology," in Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies (ICTC '16). ACM, New York: NY, pp. 1-5, 2016. DOI: 10.1145/2905055.2905110.
  40. R. Chen, H. Shih, Y. Lin, and Hendry, "Video Recommendation System Based on Personalized Ontology and Social Network," in Proceedings of the ASE Big Data & Social Informatics 2015 (ASE BD&SI '15). ACM, New York: NY, pp. 1-5, 2015. DOI: 10.1145/2818869.2818921.
  41. E. Djuana, Y. Xu, and Y. Li, "Learning personalized tag ontology from user tagging information," in Proceedings of the Tenth Australasian Data Mining Conference-Volume13 (AusDM '12), Australia, pp. 183-189, 2012.
  42. M. O'Mahony and B. Smyth, "A Recommender System for On-line Course Enrollment an Initial Study," 2007, [Online], Available: https://www.macs.hw.ac.uk/~dwcorne/ACMRecSys 07/p133omahony.pdf.
  43. C. Hung, R. Chen, and L. Chen, "Course-recommendation system based on ontology," in International Conference on Machine Learning and Cybernetics, Tianjin, China, pp. 1168-1173, 2013. DOI: 10.1109/ICMLC.2013.6890767.
  44. M. Branarach, Y. M. Thein, and T. Supnithi, "A Community-Driven Approach to Development of an Ontology-Based Application Management Framework," Semantic Technology, vol. 7774, pp. 306-312, 2013. DOI: 10.1007/978-3-642-37996-3_21.
  45. P. Wongchomphu and C. Beokhaimook, "Analyze Learner Characteristic Groups by Factor Analysis to Learner Profile Ontology," 2017, [Online], Available: http://www.isainlp.org/pdf/iSAINLP%20Proceedings2.pdf.