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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| Intelligent Tutoring System (ITS) is computer software designed to simulate or imitate a human tutor’s behavior and guidance. By having the capability to interpret complex students’ responses and to estimate the students’ degree of mastery, ITS adeptly tailor their tutoring behavior. Despite its intelligent capability, there remains a need for improvement in the ITS concerning performance measurement, predictive accuracy, and adept handling of uncertainty in student interactions. Motivated by these considerations and the recognition that ITS can further enhance their effectiveness in guiding students toward a comprehensive understanding of specific topics, this study introduces a novel mechanism within the student module. The primary objective is to present innovative criteria and approaches for measuring a student’s degree of mastery through meticulous data pre-processing. The study involved pre-processing data files to extract more meaningful information, aligning with its overarching aim. Several criteria analyzed during assessments, following pre-processing, were utilized as inputs for an evaluation function designed to evaluate students’ performance, specifically their degree of mastery. The results obtained demonstrated the efficiency of this proposed approach in accurately measuring students’ degree of mastery. This development carries meaningful implications, allowing ITS to serve as personalized tutors designed to match each student’s capabilities, ultimately enhancing the learning experience.
Keywords: intelligent tutoring system, mastery level, pre-processing, evaluation criteria, evaluation function. |
| References |
Ahuja, N. J., Dutt, S., Choudhary, S. L., & Kumar, M. (2022). Intelligent tutoring system in education for disabled learners using human–computer interaction and augmented reality. International Journal of Human–Computer Interaction, 1-13. https://doi.org/10.1080/10447318.2022.2124359 Aleven, V., Sewall, J., Popescu, O., Xhakaj, F., Chand, D., Baker, R., Wang, Y., Siemens, G., Rosé, C., & Gasevic, D. (2015). The beginning of a beautiful friendship? Intelligent tutoring systems and MOOCs. In C. Conati, N. Heffernan, A. Mitrovic, & M. Verdejo. (Eds.), Lecture notes in computer science: Vol. 9112. Artificial intelligence in education. AIED 2015. (pp. 525-528). Springer. https://doi.org/10.1007/978-3-319-19773-9_53 Anderson, J. R., Boyle, C. F., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228(4698), 456-462. https://doi.org/10.1126/science.228.4698.456 Benedikt, O., Módos, I., & Hanzálek, Z. (2020). Power of pre-processing: Production scheduling with variable energy pricing and power-saving states. Constraints, 25, 300-318. https://doi.org/10.1007/s10601-020-09317-y Bhagat, K. K., Rodrigo, M. T., & Chang, C. Y. (2018). Current status, challenges, and opportunities of the intelligent tutoring systems (ITS) in developing countries in Asia. In K. J. Kennedy & J. C. K. Lee (Eds.), Routledge international handbook of schools and schooling in Asia (pp. 382-395). Taylor & Francis. Bloom, B. S. (1968). Learning for Mastery. Instruction and curriculum. Regional Education Laboratory for the Carolinas and Virginia (ED053419). ERIC. http://files.eric.ed.gov/fulltext/ED053419.pdf Chango, W., Cerezo, R., Sanchez-Santillan, M., Azevedo, R., & Romero, C. (2021). Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources. Journal of Computing in Higher Education, 33, 614-634. https://doi.org/10.1007/s12528-021-09298-8 Chanthiran, M., Ibrahim, A. B., Abdul Rahman, M. H., & Mariappan, P. (2022). Artificial intelligence in education: A systematic mapping study using Scopus and Web of Science. Journal of ICT in Education, 9(2), 61–70. https://doi.org/10.37134/jictie.vol9.2.5.2022 Cuéllar-Rojas, O. A., Hincapié-Montoya, M., Contero, M., & Güemes-Castorena, D. (2022, December). Bibliometric analysis and systematic literature review of the intelligent tutoring systems. Frontiers in Education, 7, Article 1047853. https://doi.org/10.3389/feduc.2022.1047853 Deane, S., Avdelidis, N. P., Ibarra-Castanedo, C., Zhang, H., Yazdani Nezhad, H., Williamson, A. A., Mackley, T., Maldague, X., Tsourdos, A, & Nooralishahi, P. (2020). Comparison of cooled and uncooled IR sensors by means of signal-to-noise ratio for NDT diagnostics of aerospace grade composites. Sensors, 20(12), Article 3381. https://doi.org/10.3390/s20123381 Fang, Y., Lippert, A., Cai, Z., Chen, S., Frijters, J. C., Greenberg, D., & Graesser, A. C. (2022). Patterns of adults with low literacy skills interacting with an intelligent tutoring system. International Journal of Artificial Intelligence in Education, 32, 297-322. https://doi.org/10.1007/s40593-021-00266-y Ferster, B. (2022). Intelligent tutoring systems. Routledge. https://doi.org/10.4324/9781138609877-REE6-1 Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, research issues and applications of artificial intelligence in language education. Educational Technology and Society, 26(1), 112-131. https://doi.org/10.30191/ETS.202301_26(1).0009 Huang, Y., Brusilovsky, P., Guerra, J., Koedinger, K., & Schunn, C. (2023). Supporting skill integration in an intelligent tutoring system for code tracing. Journal of Computer Assisted Learning, 39(2), 477-500. https://doi.org/10.1111/jcal.12757 Karpouzis, K. (2023). Explainable AI for intelligent tutoring systems. OSF Preprints. https://doi.org/10.31219/osf.io/4ds7q Khazanchi, R., Di Mitri, D., & Drachsler, H. (2022). Impact of intelligent tutoring systems on mathematics achievement of underachieving students. In E. Langran (Ed.), Proceedings of society for information technology & teacher education international conference (pp. 1524-1534). https://www.learntechlib.org/primary/p/220916/ Koedinger, K., & Tanner, M. (2013, July 9). 7 Things you should know about intelligent tutoring systems. EDUCAUSE Publications. https://library.educause.edu/resources/2013/7/7-things-you-should-know-about-intelligent-tutoring-systems Kochmar, E., Vu, D. D., Belfer, R., Gupta, V., Serban, I. V., & Pineau, J. (2022). Automated data-driven generation of personalized pedagogical interventions in intelligent tutoring systems. International Journal of Artificial Intelligence in Education, 32(2), 323-349. https://doi.org/10.1007/s40593-021-00267-x Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research, 86(1), 42-78. https://doi.org/10.3102/0034654315581420 Kurni, M., Mohammed, M. S., & Srinivasa, K. G. (2023). A beginner's guide to introduce artificial intelligence in teaching and learning. Springer. https://doi.org/10.1007/978-3-031-32653-0 Lin, C. C., Huang, A. Y., & Lu, O. H. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10, Article 41, https://doi.org/10.1186/s40561-023-00260-y Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901-918. https://doi.org/10.1037/a0037123 Mahdi, A. O., Alhabbash, M. I., & Naser, S. S. A. (2016). An intelligent tutoring system for teaching advanced topics in information security. World Wide Journal of Multidisciplinary Research and Development, 2(12), 1-19. http://wwjmrd.com/upload/1507795088.pdf Nwana, H. S. (1990). Intelligent tutoring systems: An overview. Artificial Intelligence Review, 4, 251-277. https://doi.org/10.1007/BF00168958 Nye, B. D. (2015). Intelligent tutoring systems by and for the developing world: A review of trends and approaches for educational technology in a global context. International Journal of Artificial Intelligence in Education, 25, 177-203. https://doi.org/10.1007/s40593-014-0028-6 Psotka, J., Massey, L. D., & Mutter, S. A. (Eds.). (1988). Intelligent tutoring systems: Lessons learned. Psychology Press. Saidong, L., Guohua, T., Yaowen, X., & Yu, S. (2013). The research and implementation of a personalized intelligent tutoring system. Proceedings of the 2nd International Conference On Computer Science And Electronics Engineering, China, 1302-1304. https://doi.org/10.2991/iccsee.2013.326 Šarić-Grgić, I., Grubišić, A., Šerić, L., & Robinson, T. J. (2023). Student clustering based on learning behavior data in the intelligent tutoring system. International Journal of Distance Education Technologies, 18(2), 73-89, https://doi.org/10.4018/IJDET.2020040105 Sudin, I. A. A., Rahmatullah, B., Abdullah, M. F. W., Tamrin, K. F., Khairudin, M., & Yahya, S. R. (2022). A systematic literature review study on university students’ exposure to 3D printing as preparation for industry. Journal of ICT in Education, 9(1), 48–60. https://doi.org/10.37134/jictie.vol9.1.5.2022 VanLehn, K. (2006). The behavior of tutoring systems. International Journal Of Artificial Intelligence In Education, 16(3), 227-265. https://dl.acm.org/doi/10.5555/1435351.1435353 Vimal, K. R., Sowmya, V., & Soman, K. P. (2020). Effect of data pre-processing on brain tumor classification using Capsulenet. In V. Gunjan, V. Garcia Diaz, M. Cardona, V. Solanki, & K. Sunitha (Eds.), ICICCT 2019 – System reliability, quality control, safety, maintenance and management (pp. 110-119). Springer. https://doi.org/10.1007/978-981-13-8461-5_13 Wang, H., Tlili, A., Huang, R., Cai, Z., Li, M., Cheng, Z., ... & Fei, C. (2023). Examining the applications of intelligent tutoring systems in real educational contexts: A systematic literature review from the social experiment perspective. Education and Information Technologies, 28, 9113-9148. https://doi.org/10.1007/s10639-022-11555-x Wasilewska, A., & Menasalvas, E. (2023). A granular model for data mining. In T. Y. Lin, C. J. Liau, & J. Kacprzyk. (Eds.), Encyclopedia of complexity and systems science series: Granular, fuzzy, and soft computing (pp. 251-264). Springer. https://doi.org/10.1007/978-1-0716-2628-3_260 Yaratan, H. (2003). Intelligent tutoring system: A tool for testing the research curiosities of artificial intelligence researchers. Turkish Online Journal of Educational Technology, 2(3), 41-47. http://www.tojet.net/articles/v2i3/236.pdf Yilmaz, R., Yurdugül, H., Yilmaz, F. G. K., Şahi̇n, M., Sulak, S., Aydin, F., Tepgeç, M., Müftüoğlu, C. T., & Oral, O. O. O. (2022). Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal. Computers and Education: Artificial Intelligence, 3, Article 100092. https://doi.org/10.1016/j.caeai.2022.100092 Zhang, L., Pan, M., Yu, S., Chen, L., & Zhang, J. (2023). Evaluation of a student-centered online one-to-one tutoring system. Interactive Learning Environments, 31(7), 4251-4269. https://doi.org/10.1080/10494820.2021.1958234 |
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