UTILIZING ARTIFICIAL INTELLIGENCE (AI) FOR AUTOMATED FEEDBACK ON THE ENGLISH ESSAY WRITING SKILLS OF INDONESIAN UNIVERSITY STUDENTS
Downloads
Academic writing proficiency is crucial for Indonesian university students navigating global careers, yet the high student-to-teacher ratio severely limits the provision of timely, quality feedback. This constraint impedes skill acquisition and necessitates the exploration of scalable technological solutions. This study aimed to evaluate the validity and causal efficacy of a specialized, localized AI-powered Automated Essay Scoring (AES) system in accelerating students’ writing skill development over one academic semester. A quasi-experimental, pretest-posttest control group design (N=120) was used. The experimental group received continuous AI feedback, while the control group received traditional manual feedback. ANCOVA was applied to measure skill gain, supported by qualitative data on faculty workload and user acceptance. Findings showed the AI group achieved superior learning gains (13.5 vs. 5.5 raw gain) with a statistically significant main effect (F=22.45, p < 0.001). The system demonstrated high scoring reliability (r=0.88) and reduced lecturer routine grading time by 65%, successfully driving improvement in higher-order skills like Structural Coherence. The research confirms that the customized AI-Feedback Model is a pedagogically transformative tool that provides a sustainable solution to structural constraints in EFL education. It establishes a new paradigm for instructional practice by positioning localized AI as a highly consistent and effective mechanism for mass academic skill development in resource-constrained educational environments.
Andewi, W., Waziana, W., Wibisono, D., Putra, K. A., Hastomo, T., & Oktarin, I. B. (2025). From Prompting to Proficiency: A Mixed-Methods Analysis of Prompting with ChatGPT Versus Lecturer Interaction in an EFL Classroom. Journal of Studies in the English Language, 20(2), 210–238. Scopus. https://doi.org/10.64731/jsel.v20i2.282318
Juanda, n., & Afandi, I. (2024). Assessing text comprehension proficiency: Indonesian higher education students vs ChatGPT. XLinguae, 17(1), 49–68. Scopus. https://doi.org/10.18355/XL.2024.17.01.04
Oktarin, I. B., Saputri, M. E. E., Magdalena, B., Hastomo, T., & Maximilian, A. (2024). Leveraging ChatGPT to enhance students’ writing skills, engagement, and feedback literacy. Edelweiss Applied Science and Technology, 8(4), 2306–2319. Scopus. https://doi.org/10.55214/25768484.v8i4.1600
Pratama, R. D., Widiati, U., & Hakim, L. N. (2025). Effects of human-AI collaborative writing strategy on EFL students’ argumentative writing skills. Computer Assisted Language Learning. Scopus. https://doi.org/10.1080/09588221.2025.2503900
Rahayu, A., Tarihoran, N., Rahmawati, E., Muslihah, E., & Ma’mur, I. (2025). Navigating the Digital Writing Landscape: EFL Students’ Perspectives on ChatGPT Utilization. International Journal of Learning, Teaching and Educational Research, 24(5), 727–752. Scopus. https://doi.org/10.26803/ijlter.24.5.37
Virdee, B., Correia, S. D., Bedi, P., & Swaroop, A. (Eds.). (2025). International Conference on Artificial Intelligence and Networks, ICAIN 2024. Lecture Notes in Networks and Systems, 1269 LNNS. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105019535267&partnerID=40&md5=4db167bf5766a3eb4ce16a679f87e2af
Zubaidi, A., Munip, A., Widodo, S. A., & Zerrouki, T. (2025). Enhancing Arabic writing skills using Chat GPT-based AI learning models: A tridimensional human-AI collaboration framework. Indonesian Journal of Applied Linguistics, 15(1), 87–101. Scopus. https://doi.org/10.17509/ijal.v15i1.75378
Copyright (c) 2025 Nicodemus Rahanra, Ahmed Hossam, James Scott, Nurhayati
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
