AI INTERAKTIF DALAM PEMBELAJARAN ISTIMA : STUDI KASUS DI MTS ALIF LAAM MIIM SURABAYA

Authors

  • Malik Ja'far Al Farizi UIN Sunan Ampel Surabaya
  • Ahmad Shofiyyul Mubarok UIN Sunan Ampel Surabaya
  • Ida Miftahul Jannah UIN Sunan Ampel Surabaya

DOI:

https://doi.org/10.23969/jp.v10i04.36184

Keywords:

Interactive AI, Arabic listening skills (istimā‘), Google AI Studio, Pipit AI

Abstract

This study explores the implementation of interactive Artificial Intelligence (AI) in enhancing Arabic listening skills (maharah istimā‘) among students at MTs Alif Laam Miim Surabaya. Using a qualitative case study approach, the research investigates how Google AI Studio and Pipit AI support the development of students’ auditory comprehension through multimodal learning experiences. Data were collected through classroom observations, in-depth interviews with teachers and students, and documentation of learning activities. The findings show that AI integration significantly improves students’ motivation, engagement, and listening comprehension. Google AI Studio provides clear and repetitive Arabic audio with near-native pronunciation, while Pipit AI generates contextualized video avatars that strengthen semantic understanding through visual cues. These multimodal features help students recognize phonetic patterns, infer meaning, and maintain sustained focus during learning. The study also identifies several supporting factors, including teacher competence in designing AI-based instruction and students’ positive attitudes toward digital media. However, challenges remain in the form of unstable internet connectivity, occasional unclear AI-generated audio, and the need for pedagogical supervision to ensure information validity. Overall, interactive AI serves as an effective complementary tool that enhances phonetic accuracy, contextual understanding, and learner autonomy in Arabic listening instruction. This research contributes empirically to the integration of AI-mediated listening pedagogy at the secondary Islamic education level and provides a model for future curriculum innovation in Arabic language learning.

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References

Abdumutalijonovna, S. P., & Kizi, M. M. R. (2025). THE IMPACT OF DIGITAL TECHNOLOGY ON STUDENTS’ LANGUAGE PROFICIENCY. INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY. https://doi.org/10.70728/tech.v2.i06.030

Al-Busaidi, F. (2012). Listening Difficulties among Non-Native Speakers of Arabic. Journal of Educational and Psychological Studies [JEPS]. https://doi.org/10.24200/jeps.vol6iss3pp31-44

AlAfnan, M. (2024). Artificial Intelligence and Language: Bridging Arabic and English with Technology. Journal of Ecohumanism. https://doi.org/10.62754/joe.v3i8.4961

Alalwan, N. (2022). Actual use of social media for engagement to enhance students’ learning. Education and Information Technologies, 27, 9767–9789. https://doi.org/10.1007/s10639-022-11014-7

Algabri, M., Mathkour, H., Alsulaiman, M., & Bencherif, M. (2022). Mispronunciation Detection and Diagnosis with Articulatory-Level Feedback Generation for Non-Native Arabic Speech. Mathematics. https://doi.org/10.3390/math10152727

Aljanabi, M. (2024). Assessing the Arabic Parsing Capabilities of ChatGPT and Cloude: An Expert-Based Comparative Study. Mesopotamian Journal of Arabic Language Studies. https://doi.org/10.58496/mjals/2024/002

Alkaabi, M., & Almaamari, A. S. (2025). Generative AI Implementation and Assessment in Arabic Language Teaching. Int. J. Online Pedagog. Course Des., 15, 1–18. https://doi.org/10.4018/ijopcd.368037

Asrifan, A., De Barros Cardoso, L. M. O., & Vargheese, K. (2025). Fostering collaborative learning in ESP: AI-driven approaches integrating learning styles and multiple intelligences. Englisia: Journal of Language, Education, and Humanities. https://doi.org/10.22373/ej.v12i2.29330

Bashori, M., Van Hout, R., Strik, H., & Cucchiarini, C. (2024). I Can Speak: improving English pronunciation through automatic speech recognition-based language learning systems. Innovation in Language Learning and Teaching, 18, 443–461. https://doi.org/10.1080/17501229.2024.2315101

Çalik, S. S., Kucukmanisa, A., & Kilimci, Z. H. (2023). An ensemble-based framework for mispronunciation detection of Arabic phonemes. ArXiv, abs/2301.01378. https://doi.org/10.48550/arxiv.2301.01378

Cosentino, G., Gelsomini, M., Sharma, K., & Giannakos, M. (2025). Students’ experience and learning outcomes in multisensory environments: the moderating role of interaction modalities. Smart Learning Environments. https://doi.org/10.1186/s40561-025-00402-4

Ellikkal, A., & Rajamohan, S. (2024). AI-enabled personalized learning: empowering management students for improving engagement and academic performance. Vilakshan - XIMB Journal of Management. https://doi.org/10.1108/xjm-02-2024-0023

Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL learners’ speaking skills and willingness to communicate via artificial intelligence-mediated interactions. System. https://doi.org/10.1016/j.system.2024.103254

Fidan, M., & Gencel, N. (2022). Supporting the Instructional Videos With Chatbot and Peer Feedback Mechanisms in Online Learning: The Effects on Learning Performance and Intrinsic Motivation. Journal of Educational Computing Research, 60, 1716–1741. https://doi.org/10.1177/07356331221077901

Fink, M., Robinson, S., & Ertl, B. (2024). AI-based avatars are changing the way we learn and teach: benefits and challenges. Frontiers in Education. https://doi.org/10.3389/feduc.2024.1416307

Giray, L., Nemeño, J., & Edem, J. (2025). Self-directed Learning Using ChatGPT Positively Affects Student Engagement. International Journal of Technology in Education. https://doi.org/10.46328/ijte.1162

Guaña-Moya, J., Arteaga-Alcívar, Y., Criollo-C, S., & Cajamarca-Carrazco, D. (2024). Use of Interactive Technologies to Increase Motivation in University Online Courses. Education Sciences. https://doi.org/10.3390/educsci14121406

Haroud, S., & Saqri, N. (2025). Generative AI in Higher Education: Teachers’ and Students’ Perspectives on Support, Replacement, and Digital Literacy. Education Sciences. https://doi.org/10.3390/educsci15040396

Hellín, C., Calles-Esteban, F., Valledor, A., Gómez, J., Otón-Tortosa, S., & Tayebi, A. (2023). Enhancing Student Motivation and Engagement through a Gamified Learning Environment. Sustainability. https://doi.org/10.3390/su151914119

Hijriyah, U. (2025). How Effective Is SUNO.AI in Enhancing Arabic Listening Skills? An Evaluation of AI-Based Personalized Learning. International Journal of Information and Education Technology. https://doi.org/10.18178/ijiet.2025.15.2.2251

Hirschi, K., Kang, O., Yang, M., Hansen, J., & Beloin, K. (2025). Artificial Intelligence‐Generated Feedback for Second Language Intelligibility: An Exploratory Intervention Study on Effects and Perceptions. Language Learning. https://doi.org/10.1111/lang.12719

Ibrahim, A., Seddiq, Y., Meftah, A., Alghamdi, M., Selouani, S., Qamhan, M., Alotaibi, Y., & Alshebeili, S. (2020). Optimizing Arabic Speech Distinctive Phonetic Features and Phoneme Recognition Using Genetic Algorithm. IEEE Access, 8, 200395–200411. https://doi.org/10.1109/access.2020.3034762

Islam, M. Z., & Wang, G. (2025). Avatars in the educational metaverse. Visual Computing for Industry, Biomedicine, and Art, 8. https://doi.org/10.1186/s42492-025-00196-9

Kang, B., Jeon, H., & Lee, Y. K. (2024). AI‐based language tutoring systems with end‐to‐end automatic speech recognition and proficiency evaluation. ETRI Journal, 46, 48–58. https://doi.org/10.4218/etrij.2023-0322

Li, Y., Chen, D., & Deng, X. (2024). The impact of digital educational games on student’s motivation for learning: The mediating effect of learning engagement and the moderating effect of the digital environment. PLOS ONE, 19. https://doi.org/10.1371/journal.pone.0294350

Liu, C.-C., Hwang, G., Yu, P., Tu, Y., & Wang, Y. (2025). Effects of an automated corrective feedback-based peer assessment approach on students’ learning achievement, motivation, and self-regulated learning conceptions in foreign language pronunciation. Educational Technology Research and Development. https://doi.org/10.1007/s11423-025-10484-z

Madwi, F. H. M. (2025). Integrating Artificial Intelligence in Arabic Language Education: Challenges and Opportunities. Dzil Majaz: Journal of Arabic Literature. https://doi.org/10.58223/dzilmajaz.v3i1.371

Malik, M., Malang, I., Bahruddin, U., Imaduddin, M., & Muhammady, A. (2025). The Possibility Of Benefiting From Artificial Intelligence In Designing Arabic Language Teaching For Non-Native Speakers. Abjadia : International Journal of Education. https://doi.org/10.18860/abj.v10i1.32147

Mayer, R. E. (2005). Cognitive theory of multimedia learning. The Cambridge Handbook of Multimedia Learning, 41(1), 31–48.

Mohamed, A., Shaaban, T., Bakry, S., Guillén-Gámez, F., & Strzelecki, A. (2024). Empowering the Faculty of Education Students: Applying AI’s Potential for Motivating and Enhancing Learning. Innovative Higher Education. https://doi.org/10.1007/s10755-024-09747-z

Mötteli, C., Grob, U., Pauli, C., Reusser, K., & Stebler, R. (2023). The influence of personalized learning on the development of learning enjoyment. International Journal of Educational Research Open. https://doi.org/10.1016/j.ijedro.2023.100271

Mufidah, I., Khoiriyah, S., & Ainiy, N. (2025). Implementation of Arabic Language Learning Media in Islamic Universities: Benefits and Problems. Journal of Arabic Language Learning and Teaching (JALLT). https://doi.org/10.23971/jallt.v3i1.254

Mulyanto, D., Zaky, M., & Ridho, A. M. A. (2024). استخدام الذكاء الاصطناعي لتطوير مهارات اللغة العربية في تعلمها. An-Nidzam : Jurnal Manajemen Pendidikan Dan Studi Islam. https://doi.org/10.33507/an-nidzam.v11i1.1940

Ningsih, A. G. (2025). Exploring the Impact of Adaptive Real-Time Quiz Platforms with Differentiated Learning Features on Student Engagement and Learning Outcomes: A Mixed-Methods Approach. International Journal of Information and Education Technology. https://doi.org/10.18178/ijiet.2025.15.6.2329

Paivio, A., & Clark, J. M. (1986). Dual coding theory and education. Pathways to Literacy Achievement for High Poverty Children, 1, 149–210.

Prasetya, R. N., Budiman, R. D. A., Astuti, A., Friani, D. A., & Siradjuddin, S. (2025). Student Perceptions of the Use of Interactive Digital Media in Improving Learning Motivation. Juwara: Jurnal Wawasan Dan Aksara. https://doi.org/10.58740/juwara.v5i1.313

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

Richter, S., Kishore, S., Piven, I., Dodd, P., & Bate, G. (2025). Chatbots in tertiary education: Exploring the impact of warm and competent avatars on self‐directed learning. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13610

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68.

Salvetti, F., Bertagni, B., & Contardo, I. (2025). AI Conversational Agents for Corporate Language Learning: Enhancing Engagement and Retention. Int. J. Adv. Corp. Learn., 18, 60–69. https://doi.org/10.3991/ijac.v18i3.52593

Sarif, S., Paputungan, M. Z., & Samad, M. (2024). INOVASI PEMBELAJARAN BAHASA ARAB BERTEKNOLOGI ARTIFICIAL INTELLEGENCE. Al-Mulk: Jurnal Pengabdian Masyarakat. https://doi.org/10.46339/al-mulk.v2i2.1404

Sivakumar, A., Jayasingh, S., & Shaik, S. (2023). Social Media Influence on Students’ Knowledge Sharing and Learning: An Empirical Study. Education Sciences. https://doi.org/10.3390/educsci13070745

Tolba, R., Elarif, T., Taha, Z., & Hammady, R. (2024). Interactive Augmented Reality System for Learning Phonetics Using Artificial Intelligence. IEEE Access, 12, 78219–78231. https://doi.org/10.1109/access.2024.3406494

Tuah, N., Nizam, D., & Sani, Z. (2021). Modelling the Player and Avatar Attachment based on Student’s Engagement and Attention in Educational Games. https://doi.org/10.14569/ijacsa.2021.0120740

Vygotsky, L., & Cole, M. (1978). Lev Vygotsky: Learning and social constructivism. Learning Theories for Early Years Practice. UK: SAGE Publications Inc, 68–73.

Wang, Y.-M., Wei, C.-L., Lin, H., Wang, S.-C., & Wang, Y.-S. (2022). What drives students’ AI learning behavior: a perspective of AI anxiety. Interactive Learning Environments, 32, 2584–2600. https://doi.org/10.1080/10494820.2022.2153147

Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1261955

Wu, D., Zhang, S., Zhiyuan, Yue, X.-G., & Dong, R. K. (2024). Unlocking Potential: Key Factors Shaping Undergraduate Self-Directed Learning in AI-Enhanced Educational Environments. Syst., 12, 332. https://doi.org/10.3390/systems12090332

Wu, J. (2025). English Listening Prediction Strategy Based on Deep Learning and Its Training Methodology. International Journal of Cognitive Informatics and Natural Intelligence. https://doi.org/10.4018/ijcini.384513

Ye, Y., & Kaplan-Rakowski, R. (2024). An exploratory study on practising listening comprehension skills in high-immersion virtual reality. Br. J. Educ. Technol., 55, 1651–1672. https://doi.org/10.1111/bjet.13481

Yuliani, S. Y., & Sopian, A. (2025). Integration of AI-Based Text-to-Speech Technology in Arabic Listening Skills Learning. Aphorisme: Journal of Arabic Language, Literature, and Education. https://doi.org/10.37680/aphorisme.v6i1.7144

Zaimah, N. R., Fatchiatuzahro, & Hartanto, E. B. (2024). ENHANCING WRITING COMPREHENSION IN L2 ARABIC LEARNERS THROUGH AI-BASED TRANSLANGUAGING CHATBOTS. Al-Mubin: Islamic Scientific Journal. https://doi.org/10.51192/almubin.v7i1.753

Zhang, R., & Wu, Q. (2024). Impact of using virtual avatars in educational videos on user experience. Scientific Reports, 14. https://doi.org/10.1038/s41598-024-56716-9

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Published

2025-12-12