The Impact of HAINC-Integrated NotebookLM AI Feedback on EFL Students’ Writing Performance at IAIN Parepare

Authors

  • Winny Junianty Imradiyah English Education Department, Tarbiyah Faculty, Institut Agama Islam Negeri Parepare, Indonesia
  • Nurul Hasanah English Education Department, Tarbiyah Faculty, Institut Agama Islam Negeri Parepare, Indonesia
  • Zulfah Fakhruddin English Education Department, Tarbiyah Faculty, Institut Agama Islam Negeri Parepare, Indonesia

DOI:

https://doi.org/10.24256/ideas.v14i1.10716

Keywords:

AI-based feedback, academic writing, HAINC protocol, NotebookLM, technology acceptance

Abstract

This study investigated the impact of HAINC-Integrated NotebookLM AI feedback on EFL students’ writing performance at IAIN Parepare. The study employed a quantitative pre-experimental design using a one-group pre-test and post-test method combined with a Technology Acceptance Model (TAM) questionnaire. The participants consisted of 23 students from the English Education Study Program selected through purposive sampling. The instruments used in this study were a writing test and a TAM-based questionnaire. The writing assessment focused on four components: content and ideas, organization and structure, language and style, and grammar and punctuation. The treatment was conducted using NotebookLM integrated with the Human-AI Interactive Negotiation Competence (HAINC) protocol, which applied Socratic interaction, progressive prompting, and the “Three-Try Rule” to encourage active learner engagement during revision activities. The collected data were analyzed using descriptive statistics and a paired sample t-test. The findings revealed a significant improvement in students’ writing performance after the implementation of the AI feedback system, as indicated by the significance value of 0.003 (<0.05). Furthermore, the TAM questionnaire results showed that students demonstrated a high level of technology acceptance toward NotebookLM AI feedback in terms of perceived usefulness, perceived ease of use, attitude toward using AI, and behavioral intention to use the technology. The study concludes that HAINC-Integrated NotebookLM AI feedback effectively improves students’ writing performance and positively supports AI-assisted learning in EFL writing instruction

References

Ahmed, M. R., & Uddin, M. M. (2025). Multimedia Integration to Enhance Interactivity: A Cognitive Load Theoretical Approach in American Poetry Instruction. International Journal of Humanities Education, 23(1), 125–148. https://doi.org/10.18848/2327-0063/CGP/v23i01/125-148

Al-Kadi, A. (2025). Fostering a ‘Human AI’ Approach for Evaluating Students’ Writing in English. Studies in Linguistics, Culture and FLT, 13(1), 140–159. https://doi.org/10.46687/VFBZ9792

Alghannam, M. S. M. (2025). Artificial Intelligence as a Provider of Feedback on EFL Student Compositions. World Journal of English Language, 15(2), 161–173. https://doi.org/10.5430/wjel.v15n2p161

Alnemrat, A., Aldamen, H., Almashour, M., Al-Deaibes, M., & AlSharefeen, R. (2025). AI vs. Teacher Feedback on EFL Argumentative Writing: a Quantitative Study. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1614673

Bahari, A. (2026). Evaluating the Effectiveness of AI-Driven Approaches on EFL Learners’ Expository Writing Skills. TESOL Journal, 17(1). https://doi.org/10.1002/tesj.70099

Burner, T., Lindvig, Y., & Wærness, J. I. (2025). “We Should Not Be Like a Dinosaur”—Using AI Technologies to Provide Formative Feedback to Students. Education Sciences, 15(1). https://doi.org/10.3390/educsci15010058

Chen, Q. (2025). Students ’ Perceptions of AI-Powered Feedback in English Writing : Benefits and Challenges in Higher Education. 00(June), 1–11. https://doi.org/10.47852/bonviewIJCE52025580

Davis, F. D., & Granić, A. (2024). Evolution of TAM. In The Technology Acceptance Model: 30 Years of TAM (pp. 19–57). Springer.

Fleckenstein, J., Liebenow, L. W., & Meyer, J. (2023). Automated Feedback and Writing: A Multi-Level Meta-Analysis of Effects on Students’ Performance. Frontiers in Artificial Intelligence, 6. https://doi.org/10.3389/frai.2023.1162454

Hyland, K. (2019). Second Language Writing. Cambridge University Press.

Johnson, R. B., & Christensen, L. B. (2024). Handbook. Sage Publications.

Khojasteh, L., Karimian, Z., Nasiri, E., Kafipour, R., & Farahmandi, A. Y. (2025). Artificial Intelligence and Academic Writing Questionnaire (AI-AWQ): Development and Validation among Medical Students’ Experiences Using Exploratory Factor Analysis. BMC Medical Education, 25(1). https://doi.org/10.1186/s12909-025-08288-z

Lo, N., Chan, S., & Wong, A. (2025). Evaluating Teacher, AI, and Hybrid Feedback in English Language Learning: Impact on Student Motivation, Quality, and Performance in Hong Kong. SAGE Open, 15(3). https://doi.org/10.1177/21582440251352907

Noviasmy, Y., Dalle, A., & Hasanah, N. (2023). Applying Quizizz Application as an Assessment Tool for EFL Students. Inspiring: English Education Journal, 6(1), 12–22. https://doi.org/10.35905/inspiring.v6i1.4835

Pertiwi, P. C., Segoh, D., & Rohmadhani, A. (2025). Artificial Intelligence in Academic Environments : Reducing or Increasing Foreign Language Anxiety ? Inspiring: English Education Journal, 8(1), 100–131. https://doi.org/10.35905/inspiring.v8i1.13009

Rozaimee, F., & Mumin, M. A. (2025). ChatGPT Integration in Writing Development: Student Experiences and Perspectives. World Journal of English Language, 15(8), 74–83. https://doi.org/10.5430/wjel.v15n8p74

Santos, É. M. B., Hirayama, D., & Costa, T. B. (2025). Artificial Intelligence in Engineering Learning : How Do Engineering Students Use It? 163–170. https://doi.org/10.5281/zenodo.15850339

Soori, A., Khojasteh, L., & Javed, F. (2025). Comparing Teacher E-Feedback, AI Feedback, and Hybrid Feedback in Enhancing EFL Writing Skills. Technology in Language Teaching and Learning, 7(3). https://doi.org/10.29140/tltl.v7n3.102626

Tufino, E. (2025). NotebookLM as a Socratic Physics Tutor: Design and Preliminary Observations of a RAG-based Tool. https://doi.org/10.48550/arXiv.2504.09720

Usman, U., Fakhruddin, Z., Hardiyanti, H., Adam, Z., Kadaruddin, K., & Rahmani, B. (2023). Developing EFL Teachers’ Competence in Designing Learning Materials through Electronic English Book Design Training. Jurnal Inovasi Pembelajaran, 2(9), 140–153.

Zhu, M., Liu, O. L., & Lee, H.-S. (2020). The Effect of Automated Feedback on Revision Behavior and Learning Gains in Formative Assessment of Scientific Argument Writing. Computers and Education, 143. https://doi.org/10.1016/j.compedu.2019.103668

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Published

2026-06-10

Issue

Vol. 14 No. 1 (2026): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature

Section

Articles

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Copyright (c) 2026 Winny Junianty Imradiyah, Nurul Hasanah, Zulfah Fakhruddin

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