Enhancing EFL Reading Comprehension via an AI-Chatbot-Guided Toulmin Mapping in Viat-Map

Banni Satria   Andoko; Dian Hanafudin  Subhi; Naufal Falah   Wafiuddin; Xia   Wang; Tsukasa   Hirashima

doi:10.31849/9nwj8r52

Authors

Banni Satria Andoko Politeknik Negeri Malang, Malang, Indonesia
Dian Hanafudin Subhi Politeknik Negeri Malang, Malang, Indonesia
Naufal Falah Wafiuddin
Xia Wang DFKI, Berlin, Germany
Tsukasa Hirashima Hiroshima University, Hiroshima, Japan

DOI:

https://doi.org/10.31849/9nwj8r52

Keywords:

AI in education , EFL , Intelligent tutoring systems, Reading comprehension, Toulmin argument, Viat-map

Abstract

The growing demand for English as a Foreign Language (EFL) proficiency necessitates innovative approaches that go beyond conventional reading practices, which often emphasize translation and literal comprehension without fostering critical thinking. Although the Toulmin Argumentation Model has proven effective in enhancing logical structuring skills, it remains insufficient in supporting higher-order thinking without additional scaffolding. This study bridges that gap by embedding an AI-powered chatbot, driven by a Large Language Model (LLM), into the Viat-Map system to promote reflective engagement and argument construction during reading tasks. Using a quantitative pre-test and post-test design, 16 university students engaged with the AI-enhanced system over two weeks. Findings reveal a significant improvement in comprehension performance (p < 0.01), with the number of interaction steps emerging as the strongest predictor of learning gain (r = 0.482, p < 0.05). Time alone did not significantly affect outcomes, yet its combination with active interaction produced a moderate synergistic effect (p = 0.041, η² = 0.16). These results underscore that active learner engagement, rather than mere exposure time, is the critical factor for meaningful comprehension improvement. The study contributes to the literature by demonstrating how AI-driven Toulmin mapping effectively cultivates deeper comprehension and critical reasoning. In a larger perspective, this research signals the possibility of reimagining global language education through intelligent systems that foster autonomy, equity, and inclusivity in diverse learning environments.

Author Biographies

Banni Satria Andoko, Politeknik Negeri Malang, Malang, Indonesia

Banni Satria Andoko is a Lecturer at Politeknik Negeri Malang specializing in Technology-Enhanced Learning. His research combines computing, data analytics, and human-centred design to create innovative solutions that improve learning experiences. With expertise in experimental studies and multimodal learning analytics, including EEG, eye-tracking, and video, he explores learner behaviour and engagement.
Dian Hanafudin Subhi, Politeknik Negeri Malang, Malang, Indonesia

Dian Hanafudin Subhi is a Lecturer at Politeknik Negeri Malang with expertise in information technology, decision support systems, and applied computing. His research covers sentiment analysis, cloud computing, and optimisation methods applied to public services, logistics, and social media analytics. He develops practical systems and applications that bridge academic research with real-world solutions to improve efficiency and decision-making.
Naufal Falah Wafiuddin

Naufal Falah Wafiuddin is a student at Politeknik Negeri Malang with a strong interest in information technology and its applications. He is developing skills in software development, data analysis, and emerging technologies, while engaging in collaborative projects that link theory to practice. Passionate about solving real-world problems, he is committed to continuous learning and innovation.
Xia Wang, DFKI, Berlin, Germany

Xia Wang is a Senior Researcher at the Educational Technology Lab, German Research Center for Artificial Intelligence (DFKI), Berlin. Her work integrates AI, big data, and semantic technologies to create adaptive learning environments. With expertise in ontology mapping, intelligent tutoring, and Industry 4.0 competence development, she drives innovations that make education more personalised and impactful
Tsukasa Hirashima, Hiroshima University, Hiroshima, Japan

Tsukasa Hirashima is a Professor at the Graduate School of Advanced Science and Engineering, Hiroshima University, where he leads the Learning Engineering Laboratory. His research spans technology-enhanced learning, concept mapping, problem-posing, and intelligent tutoring systems. Widely published, he develops AI-driven tools and frameworks that support active learning, personalised feedback, and adaptive educational environments in international contexts.

References

Alhamad, K., Manches, A., & McGeown, S. (2024). Augmented reality books: In-depth insights into children’s reading engagement. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1423163

Andini, M., Chandra, C., & Syam, S. (2025). Strategi berpikir kreatif untuk meningkatkan kemampuan membaca pemahaman siswa kelas V sekolah dasar. Semantik, 3(2), 161–173. https://doi.org/10.61132/semantik.v3i2.1632

Andoko, B. S., Amalia, E. L., Asmara, R. A., Lestari, V. A., Zahri, R. S., & Hirashima, T. (2023). Investigating VIAT-Map from the viewpoint of ease of use, perceived usefulness, and acceptance of IT using the Technology Acceptance Model (TAM). In 2023 International Conference on Educational Technology, e-Learning, and Industry 4.0 (ICET59790) (pp. 999–1004). IEEE. https://doi.org/10.1109/ICET59790.2023.10435078

Andoko, B. S., Asmara, R. A., Lestari, V. A., Ikawati, D. S. E., Prasetyo, A., Hirashima, T., & Hayashi, Y. (2023). Experimental comparison of promotion effect for EFL reading comprehension between conventional summarization and Toulmin argument reconstruction. In Proceedings of the 31st International Conference on Computers in Education (Vol. 1, pp. 732–741). ICCE. https://doi.org/10.58459/icce.2023.1064

Andoko, B. S., Hayashi, Y., Hirashima, T., & Asri, A. N. (2020). Improving English reading for EFL readers with reviewing kit-build concept map. Research and Practice in Technology Enhanced Learning, 15(1). https://doi.org/10.1186/s41039-020-00126-8

Andoko, B. S., Lestari, V. A., Pramudhita, A. N., Nuraini, A., Nisak, I. K., & Hirashima, T. (2024). Analyzing Student Behavior in Viat-map: Steps and Time as Performance Indicators. International Conference on Computers in Education. ICCE 2024. https://doi.org/10.58459/icce.2024.4849

Andoko, B. S., Mubarok, F. U., Hirashima, T., & Arhandi, P. P. (2022). Constructing Toulmin’s logical structure through Viat-Map application for reading comprehension of EFL students. In 2022 5th International Conference on Vocational Education and Electrical Engineering (ICVEE) (pp. 196–200). IEEE. https://doi.org/10.1109/ICVEE57061.2022.9930471

Aprilia, D., Izdihara, S., & Apoko, T. (2024). An evaluation of the implementation of merdeka curriculum policy in English lesson. Journal of English Teaching Literature and Applied Linguistics, 8(2), Aprilia, D., Izdihara, S. I. S., & Apoko, T. W. (2024). An Evaluation of the Implementation of Merdeka Curriculum Policy in English Lesson: A qualitative study in upper secondary school. Journal of English Teaching, Literature, and Applied Linguistics, 8(2), 193-198. https://doi.org/10.30587/jetlal.v8i2.7852

Ariani, D. (2020). Gamifikasi untuk pembelajaran. Jurnal Pembelajaran Inovatif, 3(2), 144–149. https://doi.org/10.21009/jpi.032.09

Azizah, S., & Soraya, S. (2023). A closer look at Indonesian EFL students’ writing process: The application of cognitive and metacognitive strategies. REiLA: Journal of Research and Innovation in Language, 5(2), 128–143. https://doi.org/10.31849/reila.v5i2.10687

Biancarosa, G., Kennedy, P., Carlson, S., Seipel, B., & Davison, M. (2025). Diagnostic and Instructionally Relevant Measurement of Reading Comprehension. Intervention in School and Clinic, 61(1), 19-28. https://doi.org/10.1177/10534512251327734

Bråten, I., Latini, N., & Haverkamp, Y. (2021). Predictors and outcomes of behavioral engagement in the context of text comprehension: When quantity means quality. Reading and Writing, 35(3), 687–711. https://doi.org/10.1007/s11145-021-10205-x

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901. https://arxiv.org/abs/2005.14165

Fraidan, A. A. (2025). AI and uncertain motivation: Hidden allies that impact EFL argumentative essays using the Toulmin model. Acta Psychologica, Acta Psychologica, 252, 104684. https://doi.org/10.1016/j.actpsy.2024.104684

Fryer, L. K. (2014). Emerging technologies. Bots as language learning tools. Language Learning & Technology, 10(3), 8-14.

Giawa, N. (2024). English teachers’ views on curriculum transformation in Indonesia. Student Research Journal, 2(1), 114–120. https://doi.org/10.55606/srjyappi.v2i1.999

Hamarashid, H. K., Karim, L. T., & Muhammed, D. A. (2023). ChatGPT and large language models: Unraveling multifaceted applications, hallucinations, and knowledge extraction. Indonesian Journal of Curriculum and Educational Technology Studies, 11(2), 60-70.

Hariyanti, R., Sukma, E., & Damanik, D. (2024). Improving Students’ Reading Comprehension Through Powtoon Application. Didaktika: Jurnal Kependidikan, 13(2), 2759-2766.

Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning: Are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237–257. https://doi.org/10.1111/jcal.12610

Kalantzis, M., & Cope, B. (2025). Literacy in the time of artificial intelligence. Reading Research Quarterly, 60(1), 123–138. https://doi.org/10.1002/rrq.591

Khadka, B. (2025). Assessing reading strategies and abilities of humanities and social sciences undergraduates in English fiction and non-fiction texts. Spectrum Humanities & Social Sciences, 1(1), 43–58. https://doi.org/10.3126/shss.v1i1.79797

Liando, N. V. F., Tatipang, D. P. T., & Wuntu, C. N. (2023). First language interference in EFL classes: Revealing students’ perspectives and teachers’ reasons in ELL. Journal of Research and Innovation in Language, 5(1), 77–88. https://doi.org/10.31849/reila.v5i1.10654

Maharani, W., Qamariah, Z., & Mirza, A. (2023). The history of ’90s English curriculum in Indonesia. JFLLT, 3(1), 8–19. https://doi.org/10.23971/jfllt.v3i1.6889

MATLATIPOVA, M. (2025). Ingliz tili o‘qitishda ovoz chiqarib o‘qish metodining lingvistik va psixolingvistik asoslari. NUUz, 1(1.3.1), 102–104. https://doi.org/10.69617/nuuz.v1i1.3.1.7079

Mohamed, R. (2023). Reciprocal teaching as a cognitive and metacognitive strategy in promoting Saudi university students’ reading comprehension. Open Education Studies, 5(1), 1-18. https://doi.org/10.1515/edu-2022-0200

Mubarok, & Sofiana, N. (2022, September). An evaluation of English language teaching in Indonesian schools. In Proceedings of the 4th International Conference on Education and Social Science Research (ICESRE) (KnE Social Sciences, 2022), 12–25. https://doi.org/10.18502/kss.v7i14.11947

Mubaroq, S., & Qamariah, Z. (2024). Curriculum approaches in English language teaching in Indonesia. JIPNAS, 2(1), 01–06. https://doi.org/10.59435/jipnas.v2i1.105

Nur, R. (2021). Implementing Cooperative Integrated Reading and Composition (CIRC) method to enhance the reading comprehension of Indonesian EFL learner. Journal of English Language Teaching and Applied Linguistics, 3(11), 52–64. https://doi.org/10.32996/jeltal.2021.3.11.7

Nuraeni, C., Priadi, A., & Lengkanawati, N. (2024). English Curricula in ASEAN Selected Countries: A Comparative Study. Scope: Journal of English Language Teaching, 8(2), 323-334.. https://doi.org/10.30998/scope.v8i2.18038

Perkasa, A. (2021). Developing and validating EFL reading test. Education of English as a Foreign Language, 4(1), 9–18. https://doi.org/10.21776/ub.educafl.2021.004.01.02

Qizi, M. (2024). Developing reading competence in a foreign language: Strategies, definitions, and modern perspectives. International Journal of Pedagogics, 4(11), 278–283. https://doi.org/10.37547/ijp/volume04issue11-54

Que, Y., & Hu, X. (2025). Enhancing learners' reading comprehension with preferred background music: An eye-tracking, EEG, and heart rate study. Reading Research Quarterly, 60(2). https://doi.org/10.1002/rrq.70004

Ramadhianti, A., & Somba, S. (2023). Reading comprehension difficulties in Indonesian EFL students. Journal of ELT Research, 6(1), 45–59.

Rismanto, R., Andoko, B. S., Asri, A. N., Hirashima, T., & Leonanta, A. A. (2021). A preliminary study: Toulmin arguments in English reading comprehension for English as foreign language students. 2021 IEEE 14th International Conference on Information Technology (ICIT), 1–6. https://doi.org/10.1109/ICIT53149.2021.9587398

Rizqie, Q., Afifah, N., & Bardadi, A. (2023). Eksplorasi penggunaan large language model (LLM) dalam pembangunan permainan Minesweeper dengan Python programming. Jurnal NCA, 3(1), 25–33.

Sofyan Siregar, W., & Harida, E. S. (2021). Students’ reading comprehension in descriptive text. English Education: English Journal for Teaching and Learning, 9(1), 1–12.

Toulmin, S. (1999). The uses of argument (updated ed.). Cambridge University Press.

Tran, S., & Fernandes, M. (2024). Which encoding techniques facilitate comprehension? Experimental Psychology (Formerly Zeitschrift für Experimentelle Psychologie), 71(2), 111–121. https://doi.org/10.1027/1618-3169/a000620

Tsai, S., Wang, S., & Lai, H. (2022). Evaluating learning effectiveness towards online learning: Application of design thinking and reading comprehension for case reading on economic issues during COVID-19. International Journal of Education and Practice, 10(3), 287–299. https://doi.org/10.18488/61.v10i3.3143

Wang, X., Duong-Trung, N., Bhoyar, R. R., & Jose, A. M. (2025). LLM-based literature recommender system in higher education: A case study of supervising students’ term papers. Computers & Education: Artificial Intelligence, 10, Article 100500. https://doi.org/10.1016/j.caeai.2024.100500

Wilang, J., Seepho, S., & Kitjaroonchai, N. (2025). Exploring the relationship of reading fluency and accuracy in L2 learning: Insights from a reading assistant software. Education Sciences, 15(4), 1-13. https://doi.org/10.3390/educsci15040488