Development of M.E.G.A: A self-assessment expert system to improve English correspondence skills for job-seeking university students

Merti Megawaty; Urip Sulistiyo; Sri Wachyuni; Sofyan

doi:10.59672/ijed.v6i2.5099

Authors

Merti Megawaty Universitas Jambi
Urip Sulistiyo Universitas Jambi
Sri Wachyuni Universitas Jambi
Sofyan Universitas Jambi

DOI:

https://doi.org/10.59672/ijed.v6i2.5099

Keywords:

English correspondence, Expert system, Information Systems, Self-assessment, Writing and speaking skills

Abstract

This study highlights the low English writing and speaking skills of students of the Information Systems Study Program at Nurdin Hamzah University. To address this challenge, a rule-based expert system application named M.E.G.A for Job Seekers was developed using the ADDIE model approach (Analysis, Design, Development, Implementation, and Evaluation). This application functions as a self-assessment tool to improve students' professional communication readiness, especially in compiling CVs, job application letters, and interview preparation. The sampling technique used was purposive sampling, with subjects consisting of language experts, instructional media experts, and educational technology experts to validate the product. Meanwhile, 100 second-semester students of the Information Systems Study Program at Nurdin Hamzah University were used as the sample for testing the practicality, attractiveness, and effectiveness of the application. This study used quantitative data from questionnaires and tests, as well as qualitative data from open-ended responses by experts and students. The quantitative data were analyzed descriptively, while the qualitative data were validated through triangulation and content analysis to support the development of the application. The results showed high scores in the aspects of functionality, attractiveness of appearance, and improvement of learning outcomes. Pre-test and post-test analysis showed significant improvements, while statistical analysis supported the pedagogical reliability of this system. The application has proven effective in supporting independent learning that is relevant to the needs of the world of work and has the potential to be adopted by other study programs. This study contributes to the development of digital learning through the integration of AI-based expert systems for the development of 21st-century skills.

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References

Al-Mahrooqi, R. , & D. C. (2023). Language assessment in the digital era: Pedagogical and technological integration. Language Testing in Asia, 13(1).

Alrasheedi, M. , C. L. F. , & R. A. (2022). Quality assurance in educational media design: Insights from expert validation practices. . Education and Information Technologies, 27(4), 5423-5442.

Alshahrani, F. , A. M. , & A. A. (2023). The effect of ai-based formative assessment on students’ language acquisition and motivation. International Journal of Emerging Technologies in Learning (IJET), 18(3), 101–116.

Alshammari, M. T. , A. N. A. , & A. O. (2023). Digital learning environments: impact of interactive feedback on learner engagement. Education and Information Technologies, 28(2), 2511–2532.

Asafo-adjie R, M. R. Klu. E. S.-I. E. (2023). Social media and English language writing performances of a Ghanaian ESL class. The nexus.

Badger, R. , & Y. M. (2023). Developing academic writing through higher order thinking tasks. Journal of English for Academic Purposes.

Chan, K. H. , & W. C. W. (2023a). E-portfolio simulation for enhancing english professional writing skills: An experimental study. Computer Assisted Language Learning.

Chan, K. H. , & W. C. W. (2023b). E-portfolio simulation for enhancing English professional writing skills: An experimental study. . Advance online publication. .

Clarke, E. (2023). Motivational shifts in higher education efl learners in career-aligned language programs. . Language Teaching Research, 27(2), 198–215.

Deng, L. , & Z. Y. (2022). Effects of automated writing evaluation on efl learners’ writing development: A longitudinal study. Computers & Education.

Dolcet, G. , K. H. , & L. Y. (2023). Evaluating efl speaking performance: A multi-aspect analysis. System,.

Egger, M., Florack, A., & Hübel, C. (2022). How placement affects brand preferences in advergames: A test of inhibition and facilitation processes during search. Computers in Human Behavior, 134, 107328. https://doi.org/10.1016/j.chb.2022.107328

Feng, J. , & S. T. (2023). Information technology, according to the ADDIE model on English subject teaching enhances learning achievement: A quasy-experimental study. Turkish Online Journal of Educational Technology, 22(4), 121-130.

García, F. J. , R. J. , & S. J. L. (2022). Gamified adaptive learning systems and user engagement: A quasi-experimental study. Interactive Learning Environments, 30(1), 108–127.

Geng, F., Yu, S., & Yuan, R. (Eric). (2023). Exploring l2 writing teachers’ feeling rules, emotional labor and regulation strategies. System, 119, 103160. https://doi.org/10.1016/j.system.2023.103160

Getie, A. S. (2020). Factors affecting the attitudes of students towards learning english as a foreign language. Cogent Education, 7(1). https://doi.org/10.1080/2331186X.2020.1738184

Hutchinson, T. , & W. A. (1987). English for specific purposes: A learning-centred approach. Cambridge University Press.

Jaya, S., Hamzah, S. ., & Yunita, W. . (2025). Needs analysis for critical reading e-book based on problem-based learning: Perspectives from EFL students, lecturers, and stakeholders. Indonesian Journal of Educational Development (IJED), 6(1), 55-67. https://doi.org/10.59672/ijed.v6i1.4682

Karami, S., Sadighi, F., Bagheri, M. S., & Riasati, M. J. (2018a). The potential impact of the application of electronic portfolio on iranian efl learners’ writing performance seeking their gender role. Cogent Social Sciences, 4(1), 1562509. https://doi.org/10.1080/23311886.2018.1562509

Karami, S., Sadighi, F., Bagheri, M. S., & Riasati, M. J. (2018b). The potential impact of the application of electronic portfolio on iranian efl learners’ writing performance seeking their gender role. Cogent Social Sciences, 4(1), 1562509. https://doi.org/10.1080/23311886.2018.1562509

Lee, S. , & C. T. (2023). AI-supported self-assessment tools and student efficacy in efl contexts. Journal of Computer-Assisted Learning, 39(7), 1290–1304.

Liu, M. , & Z. W. (2022). Feedback absence and speaking stagnation among efl learners. Computers & Education.

Ma, R. , L. Y. , & C. Z. (2025). Mobile-assisted speaking instruction for efl learners: A usability and learning outcome study. Language Learning & Technology, 29(1), 45–64.

Masruria W, A. S. (2021). Exploring Self-Assessment of Speaking Skill by EFL High School Students.

Mohammadi, A., Koerich, A. L., Moro-Velazquez, L., & Cardinal, P. (2025). Automatic Proficiency Assessment in L2 English Learners.

Mulyadi, D. , S. E. , & A. F. (2023). Designing contextual mobile learning systems: A student-centered approach. Journal of Educational Multimedia and Hypermedia, 32(1), 66–85.

Nguyen, P. , T. D. , & L. M. (2025). Microlearning and mobile-assisted language learning engagement among Gen Z university students. Interactive Learning Environments, 33(5), 1023–1039.

Nurhasanah, R. , F. T. N. , & S. M. (2024). ). Evaluating user experience in educational technology: A UX-based approach to digital media validation. Interactive Learning Environments. .

Oliveira, F. , S. A. , & M. R. (2023). GPT 3 automated writing feedback in efl classes: A controlled study. Language Learning & Technology, 27(1), 45–62.

Park, Y. , & L. J. (2022). Learner-centered design in e-learning: Enhancing usability and motivation. . Educational Technology Research and Development, 70(3), 723–743.

Patel, A. , & K. S. (2024). Foreign language proficiency and employability outcomes in global it graduates. Higher Education, 88(3), 321–338.

Prensky, M. (2001). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816

Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in chinese efl context. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1255594

Roe, J., Perkins, M., & Tregubova, Y. (2024). The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes.

Saleh, M. , K. Z. , & M. M. (2022). HOTS-based digital module to foster efl learners’ critical writing skill. Asian EFL Journal, 29(4), 65–91.

Serdyukov, P. , & H. P. (2022). Evaluating interactive features in adaptive learning systems. Learning Environments, 30(5), 1248–1264.

Sisman, B., Kucuk, S., & Ozcan, N. (2022). Collaborative behavioural patterns of elementary school students working on a robotics project. Journal of Computer Assisted Learning, 38(4), 1018–1032. https://doi.org/10.1111/jcal.12659

Soh, X. , L. Y. , & T. J. (2024). Comprehensive evaluation of ai self-assessment tools in language learning. Interactive Learning Environments, 32(2), 185–202.

Spatioti, A. G. , K. I. , & P. J. (2024). A comparative study of the addie instructional design model in distance education: A meta-analysis of 23 studies. Education Sciences. .

Takarroucht, K. (2022). The effect of self-assessment on the development of efl writing self-efficacy: A case of algerian higher education. International Journal of Language Education, 6(2), 157. https://doi.org/10.26858/ijole.v6i2.22065

Tomlinson, B. (Ed. ). (2007). Language acquisition and development: Studies of first and other language learners. Continuum.

Tripathi, K. P. (2011). A review on knowledge-based expert system: Concept and architecture. In Artificial Intelligence Techniques-Novel Approaches & Practical Applications.

Wang, X., Zhong, Y., Huang, C., & Huang, X. (2023). ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT.

Widana, I. W. (2020). The effect of digital literacy on the ability of teachers to develop HOTS-based assessment. Journal of Physics: Conference Series 1503 (2020) 012045. https://doi.org/10.1088/1742-6596/1503/1/012045

Xu, Q. , Z. M. , & L. H. (2023a). Designing engaging digital learning environments in higher education: User interface and user experience perspectives. Computers & Education.

Xu, Q. , Z. M. , & L. H. (2023b). Designing engaging digital learning environments in higher education: User interface and user experience perspectives. Computers & Education.

Zhang, L., Carter, R. A., Qian, X., Yang, S., Rujimora, J., & Wen, S. (2022a). Academia’s responses to crisis: A bibliometric analysis of literature on online learning in higher education during COVID‐19. British Journal of Educational Technology, 53(3), 620–646. https://doi.org/10.1111/bjet.13191

Zhang, L., Carter, R. A., Qian, X., Yang, S., Rujimora, J., & Wen, S. (2022b). Academia’s responses to crisis: A bibliometric analysis of literature on online learning in higher education during COVID‐19. British Journal of Educational Technology, 53(3), 620–646. https://doi.org/10.1111/bjet.13191

Zhang, W. , T. C. , & L. Y. (2023). Expert-based validation of multimedia learning environments in higher education: Impacts on learner engagement and performance. Australasian Journal of Educational Technology, , 39(1), 113–130.