Expert system based chatbot for enhancing learning outcomes in kebaya analysis among vocational students

Journal of Educational and Learning Studies June 30, 2026 Volume 9, Number 1 6 authors

Abstract

This study aimed to determine the validity and effectiveness of an expert system-based chatbot as a learning medium for improving students' learning outcomes in kebaya garment analysis at a vocational high school. A quasi-experimental study employing a nonequivalent control group pretest–posttest design was conducted with 60 Grade XI Fashion Design students, divided equally into experimental and control groups. Data were collected using expert validation sheets, cognitive achievement tests, and perception questionnaires, and analyzed using Aiken's V, classical mastery, Normalized Gain (N-Gain), and an Independent Samples t-test. The chatbot demonstrated good validity (Aiken's V = 0.84). The experimental group achieved 100% classical mastery, a moderate N-Gain (0.57), and significantly higher posttest scores than the control group (p < 0.001). Teachers and students also reported positive perceptions (87.27% and 86.20%, respectively). The expert system-based chatbot is a valid and effective instructional medium that enhances learning outcomes and supports independent learning in vocational fashion education

Authors

  1. Alifah Biggum Nabila

    Universitas Negeri Padang

  2. Rahmiati Rahmiati

    Universitas Negeri Padang

  3. Weni Nelmira

    Universitas Negeri Padang

  4. M. Giatman

    Universitas Negeri Padang

  5. Beni Haposan Sianipar

    Universitas Negeri Padang

  6. Armina Sari Harahap

    Universitas Negeri Padang

Keywords

Expert SystemChatbotLearning OutcomesVocational Fashion Education

References

  1. Abarkan, F. Z., Wijen, A. M. A., van Eijden, R. M. G., Struijs, F., Dennis, P., Ritskes-Hoitinga, M., & Visseren-Hamakers, I. (2022). Identifying Key Factors for Accelerating the Transition to Animal-Testing-Free Medical Science through Co-Creative, Interdisciplinary Learning between Students and Teachers. Animals, 12(20). https://doi.org/10.3390/ani12202757
  2. Ahmad, S., Ahmad, F., Nawab, Y., & Azam, F. (2026). Hydrogels and Aerogels for Functional Textiles: From Sustainable Syntheses to Applications. In Hydrogels and Aerogels for Functional Textiles: From Sustainable Syntheses to Applications. https://doi.org/10.1002/9783527851416
  3. Ahn, Y. A., Önal Ertuğrul, I., Chow, S.-M., Cohn, J. F., & Messinger, D. S. (2023). Automated measurement of infant and mother Duchenne facial expressions in the Face-to-Face/Still-Face. Infancy, 28(5), 910–929. https://doi.org/10.1111/infa.12556
  4. Alvarez, S. J. A., Pencheva, B., Westfall, E., Mwalija, C., Parsell, M., Greenleaf, M., Porter, C. C., Lam, W. A., Mannino, R. G., & Mitchell, S. G. (2023). A novel mobile health application to support cancer surveillance needs of patients and families with cancer predisposition syndromes. Pediatric Blood and Cancer, 70(10). https://doi.org/10.1002/pbc.30537
  5. Bakar, S. S. A., Ahmad, W. N. W., Zubir, N. A. M., Rui, T. J., & Ahmad, W. M. W. (2024). Automatic Thread Insertion Kit Sewing (ATIKs) Device for Vocational Fashion Design Student: Practical Sewing Application. Journal of Advanced Research in Applied Sciences and Engineering Technology, 34(1), 238–248. https://doi.org/10.37934/ARASET.34.1.238248
  6. Burvenich, R., Heytens, S., De Sutter, A., Struyf, T., Toelen, J., & Verbakel, J. Y. (2023). Towards an international consensus on safety netting advice for acutely ill children presenting to ambulatory care: a modified e-Delphi procedure. Archives of Disease in Childhood, 109(2), 93–99. https://doi.org/10.1136/archdischild-2023-326370
  7. Covvey, J. R., Blakely, M. L., Singh, R., Peckham, A. M., & Evoy, K. E. (2023). Pharmacist, prescriber, and drug policy expert opinions on gabapentinoid misuse. Research in Social and Administrative Pharmacy, 19(4), 599–609. https://doi.org/10.1016/j.sapharm.2022.12.001
  8. Fu, A., Saini, R., Koornneef, R., Van Der Meer, A., Palensky, P., & Cvetkovic, M. (2023). The Illuminator: An Open Source Energy System Integration Development Kit. 2023 IEEE Belgrade PowerTech, PowerTech 2023. https://doi.org/10.1109/PowerTech55446.2023.10202816
  9. Gosavi, C. S., Bhutkar, G., Banubakode, A., & Eilu, E. (2024). Interactive Media with Next-Gen Technologies and Their Usability Evaluation. In Interactive Media with Next-Gen Technologies and Their Usability Evaluation. https://doi.org/10.1201/9781032664828
  10. Gowri, R. (2025). OMACS Based Adaptive Intelligent Tutoring System Development. 2025 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2025. https://doi.org/10.1109/ICDSAAI65575.2025.11011745
  11. Jena, B. B., Saha, G., Mohapatra, L., & Rani, H. (2026). Farm to Fashion Model & Other Sustainable Development Practices of National Institute of Fashion Technology, Bhubaneswar: A Case Study from India. World Sustainability Series, Part F1458, 1371–1389. https://doi.org/10.1007/978-3-032-00361-4_74
  12. Juliantika, T., Giatman, M., Mardizal, J., & Yuliarma, Y. (2026). The Role of Artificial Intelligence and Digital Technology in Learning Management in Vocational High Schools: A Systematic Literature Review. El-Idare: Journal of Islamic Education Management, 12(1), 301–308.
  13. Krutphong, K., Leelawat, N., Tang, J., Ota, E., Suzuki, R. M., Taoka, Y., & Punyabukkana, P. (2023). Ideation of Engineering Solutions for Sustainable Development Goals: A Collaborative Course Between Thai and Japanese Students. IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21–24. https://doi.org/10.1109/TENCON58879.2023.10322379
  14. Kurnaedi, D. (2025). AI Integration in E-Learning for Vocational Education Effectiveness. Bit-Tech, 8(2), 2880–2889.
  15. Liu, S., Yan, J., Wang, X., Jiang, Y., Chen, L., Fan, T., Chen, K., & Yang, Q. (2025). Federated Financial Reasoning Distillation: Training A Small Financial Expert by Learning from Multiple Teachers. ICAIF 2025 - 6th ACM International Conference on AI in Finance, 623–631. https://doi.org/10.1145/3768292.3770339
  16. Maula, P. I., Sari, H. V., Hamdan, A., Tjiptady, B. C., & Maghfiro, A. W. (2025). AI as a Tool to Enhance Vocational Learning through Integration with LMS. 2025 9th International Conference On Electrical, Electronics And Information Engineering (ICEEIE), 1–6.
  17. Moreland-Head, L. N., Ausman, S. E., Rivera, C. G., Abu Saleh, O. M., Jannetto, P. J., Wessel, R. J., & Barreto, E. F. (2026). Spaced learning versus traditional learning for pharmacists implementing β-lactam therapeutic drug monitoring. American Journal of Health-System Pharmacy, 83(6), 294–302. https://doi.org/10.1093/ajhp/zxaf227
  18. Munro, M., Balen, A., Cho, S., Critchley, H., Díaz, I., Ferriani, R., Henry, L., Mocanu, E., & VAN DER SPUY, Z. (2023). The FIGO Ovulatory Disorders Classification System. Russian Journal of Human Reproduction, 29(1), 1–20. https://doi.org/10.17116/repro2023290110
  19. Munro, M. G., Balen, A. H., Cho, S., Critchley, H. O. D., Díaz, I., Ferriani, R., Henry, L., Mocanu, E., & der Spuy, Z. M. (2023). The FIGO Ovulatory Disorders Classification System*. Russian Journal of Human Reproduction, 29(1), 116–136. https://doi.org/10.17116/repro202329011116
  20. Munro, M. G., Balen, A. H., Cho, S., Critchley, H. O. D., Díaz, I., Ferriani, R., Henry, L., Mocanu, E., & van der Spuy, Z. M. (2022a). The FIGO Ovulatory Disorders Classification System†. Human Reproduction, 37(10), 2446–2464. https://doi.org/10.1093/humrep/deac180
  21. Munro, M. G., Balen, A. H., Cho, S., Critchley, H. O. D., Díaz, I., Ferriani, R., Henry, L., Mocanu, E., & van der Spuy, Z. M. (2022b). The FIGO ovulatory disorders classification system. International Journal of Gynecology and Obstetrics, 159(1), 1–20. https://doi.org/10.1002/ijgo.14331
  22. Munro, M. G., Balen, A. H., Cho, S., Critchley, H. O. D., Díaz, I., Ferriani, R., Henry, L., Mocanu, E., & van der Spuy, Z. M. (2022c). The FIGO Ovulatory Disorders Classification System. Fertility and Sterility, 118(4), 768–786. https://doi.org/10.1016/j.fertnstert.2022.07.009
  23. Palma, C. D., & Cabello-Avilez, P. (2025). Towards a Circular Fashion Future: A Textile Revalorization Model Combining Public and Expert Insights from Chile. Sustainability (Switzerland), 17(19). https://doi.org/10.3390/su17198670
  24. Park, K. M., Gesbeck, M. M., Alseidi, A. A., Park, Y. S., Sullivan, M. E., Salcedo, E. S., Blair, P. G., Liscum, K., Sachdeva, A. K., AbdelFattah, K. R., Alam, H. B., Brown, C. V. R., Choi, J. N., Cochran, A., Delman, K. A., Demetriades, D., Dort, J. M., Frey, E. S., Gauvin, J., … Yang, S. C. (2022). Resident Readiness for Senior Level Decision Making: Identifying the Domains for Formative Assessment and Feedback. Journal of Surgical Education, 79(5), 1124–1131. https://doi.org/10.1016/j.jsurg.2022.04.011
  25. Rakhmawati, E. (2025). Analysis of the effectiveness of ai-based chatbot as a learning assistant for students with visual learning style. Journal of Multidisciplinary Sustainability Asean, 2(2), 76–86.
  26. Rosyanto, R., Wahyudin, D., & Hernawan, A. H. (2025). ADDIE-based AI training using open-source LMS for vocational teachers. Curricula: Journal of Curriculum Development, 4(2), 979–992.
  27. Setyaningsih, F. A., Surjono, H. D., & Andayani, S. (2025). A Systematic Review: Employing Ai In Adaptive Learning Recommendation System For Vocational Education. Journal Of Theoretical And Applied Information Technology, 103, 16.
  28. Shima, R., Matsumura, R., & Kitakaze, H. (2025). VR-Based System for Pyrotechnics Skill Transfer and CNN-Based Determination of Gunpowder Mixing Ratios to Achieve Target Firework Colors. 2025 1st International Conference on Consumer Technology, ICCT-Pacific 2025. https://doi.org/10.1109/ICCT-Pacific63901.2025.11012823
  29. Wang, W. (2025). Vocational Education Needs and Skill Cultivation Paths of Chinese Silk Culture and Fashion Designs. Textile and Leather Review, 8, 454–477. https://doi.org/10.31881/TLR.2025.015
  30. Wieczorek, M., Utterberg Modén, M., Bergviken Rensfeldt, A., & Hillman, T. (2026). Beyond data extraction: alternative models for the governance of educational data. Learning, Media and Technology. https://doi.org/10.1080/17439884.2026.2678187
  31. Yu, X., Xiong, Y., & Tian, M. (2025). Performance Comparison Between Unaided Generation and Human-in-the-Loop Approaches in AI-Driven Fashion Design; [AI 驱动服装设计中无人工干预生成与人工辅助方法性能比较]. Journal of Beijing Institute of Fashion Technology (Natural Science Edition), 45(4), 64–73. https://doi.org/10.16454/j.cnki.issn.1001-0564.2025.04.008
  32. Yuniati, M., Hidayati, L., & Rahayu, I. A. T. (2025). International class teaching materials based on blended learning through the SIDIA learning management system. AIP Conference Proceedings, 3354. https://doi.org/10.1063/5.0292260
  33. Yusro, M., Misin, R., & Mauludin, M. A. (2024). Vocational education development strategy in the use of artificial intelligence in the digital Era. 5th Vocational Education International Conference (VEIC-5 2023), 734–741.