Designing Intelligent Language Tutoring Systems Using Fuzzy Logic

Authors

  • Suleiman Ibrahim Shelash Mohammad

    Department of Electronic Marketing and Social Media, Faculty of Economic and Administrative Sciences, Zarqa University, Zarqa 13110, Jordan

    Department of Business and Communications , INTI International University, Persiaran Perdana BBN, Putra Nilai, Negeri Sembilan 71800, Malaysia
  • N. Yogeesh

    Department of Mathematics, Government First Grade College, Tumkur, Karnataka 572102, India
  • Khaleel Ibrahim Al-Daoud

    Department of Accounting, Faculty of Business, Al-Ahliyya Amman University, Al Salt Road, Amman 19328, Jordan
  • N. Raja

    Department of Visual Communication, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai, Tamil Nadu 600119, India
  • Aravinda Reddy N

    Department of English, Government College for Women, Chintamani, Chikkaballapur, Karnataka 563125, India
  • Rayeesul Hassan S

    Department of English, Government College for Women, Kolar, Karnataka 563101, India
  • Asokan Vasudevan

    Faculty of Business and Communications, INTI International University, Persiaran Perdana BBN, Putra Nilai, Negeri Sembilan 71800, Malaysia
  • Nawaf Alshdaifat

    Faculty of Information Technology, Applied Science Private University, Shafa Badran, Amman 11931, Jordan
  • Mohammad Faleh Ahmmad Hunitie

    Department of Public Administration, School of Business, University of Jordan, Amman 11942, Jordan

DOI:

https://doi.org/10.30564/fls.v7i5.9443
Received: 11 April 2025 | Revised: 27 April 2025 | Accepted: 29 April 2025 | Published Online: 8 May 2025

Abstract

This study investigates the integration of fuzzy logic into intelligent language tutoring systems to address the inherent uncertainties in language learning. By employing continuous membership functions, fuzzy inference mechanisms, and defuzzification techniques, the proposed system adapts instructional content and provides personalized feedback in real time. An experimental case study involving 25 intermediate-level language learners over a 16-week academic semester was conducted. Baseline assessments measured initial proficiency, followed by a tutoring intervention where fuzzy logic dynamically adjusted content based on learner performance, and concluding with post-intervention evaluations. Quantitative analysis showed an overall increase of 12.24 points on the pre-test and post-test while qualitative feedback highlighted more engagement, confidence as learner and satisfaction from the adaptive feedback technique. The fuzzy logic system proved to be significantly more effective in managing linguistic vague phenomena (like pronunciation, grammar, etc.) than with the control group (comparative with traditional tutoring). These results not only demonstrate the mathematical strength of fuzzy logic in education, but also suggest its use in improving individualized language learning. Future research will examine sustainable impacts, synergies with other Al technologies, and approaches to scaling the system to different educational settings. In addition, the study also includes rigorous mathematical modelling and sensitivity analysis to demonstrate the stability of fuzzy membership functions and the inference mechanism. A rigorous statistical significance test rigorously affirms the significant effectiveness of the system, validating its merit as a trusted device for customized language education.

Keywords:

Fuzzy Logic; Intelligent Tutoring Systems; Language Learning; Adaptive Feedback; Experimental Case Study; Personalized Instruction; Mathematical Modeling; Educational Technology

References

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How to Cite

Shelash Mohammad, S. I., N. Yogeesh, Al-Daoud, K. I., N. Raja, N, A. R., Rayeesul Hassan S, Vasudevan, A., Alshdaifat, N., & Ahmmad Hunitie, M. F. (2025). Designing Intelligent Language Tutoring Systems Using Fuzzy Logic. Forum for Linguistic Studies, 7(5), 697–711. https://doi.org/10.30564/fls.v7i5.9443

Issue

Vol. 7 , Iss. 5 (May 2025)

Article Type

Article

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Copyright © 2025 Suleiman Ibrahim Shelash Mohammad, N. Yogeesh, Khaleel Ibrahim Al-Daoud, N. Raja, Aravinda Reddy N, Rayeesul Hassan S, Asokan Vasudevan, Nawaf Alshdaifat, Mohammad Faleh Ahmmad Hunitie

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.