BRIDGING THE GAP: TEACHERS’ KNOWLEDGE AND APPLICATION OF AI-DRIVEN LEARNING PLATFORMS IN STEM-BASED ENGLISH LANGUAGE EDUCATION
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This study aims to determine teachers' knowledge level about AI-driven learning platforms in STEM education, to determine the extent to which language teachers apply AI-driven learning platforms in STEM education, and to see whether the level of knowledge, attitudes and readiness of teachers is balanced with its application. This study uses a quantitative and qualitative design or mixed method and applies a correlation approach. The participants of this study involved 33 English teachers in Indonesia. The results of this study conclude that the level of knowledge of language teachers on AI-driven platforms in STEM learning is still classified as intermediate. The application of AI-driven platforms in STEM learning for English teachers is also in the intermediate category. Language teachers have not yet entered the high level of application of AI-driven platforms in STEM learning, although a small number of teachers can reach this level. The correlation between teacher knowledge of AI-driven platforms in STEM learning is directly proportional to their application in learning practices. However, the data shows no correlation between teacher attitudes and readiness towards AI-driven platforms in STEM learning and the application of AI-driven platforms in STEM learning.
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Wahyunengsih, W. (2025). BRIDGING THE GAP: TEACHERS’ KNOWLEDGE AND APPLICATION OF AI-DRIVEN LEARNING PLATFORMS IN STEM-BASED ENGLISH LANGUAGE EDUCATION. English Review: Journal of English Education, 13(1), 67-80. https://doi.org/10.25134/erjee.v13i1.11155
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Referensi
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S. A. (2024). Exploring the impact of artificial intelligence on transforming physics, chemistry, and biology education. https://doi.org/10.21428/a70c814c.747297aa
Ting, Y. (2024). Evaluation of the effect of generative AI in English writing class. Journal of Education, Humanities and Social Sciences, 38, 279-285. https://doi.org/10.54097/t9echq16
Valentyna, L., & Kornieva, Z. (2024). Generative AI in student essays: English teachers' perspectives on effective assessment methods. XLinguae, 17(4), 235-250. https://doi.org/10.18355/xl.2024.17.04.14
Xiaochao, Y., & Huang, X. (2024). Study on college English teachers’ attitudes and acceptance of AI-driven language learning applications. https://doi.org/10.26689/ief.v2i6.7621
Yimin, N., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the relationship between knowledge elements. Sustainability. https://doi.org/10.3390/su16030978
Zada, K., Seidaliyeva, G., Degtyareva, X., & Yessenaman, S. (2024). Eclecticism in language teaching: Developing educational and methodological content for an English language qualification course using artificial intelligence. XLinguae, 17(4), 111-137. https://doi.org/10.18355/xl.2024.17.04.08
Ariane, S., Scarci, T., Moser, L., Teixeira, D., Fleig, L., & Forno, D. (2024). Artificial intelligence and its relations with digital competencies and education. https://doi.org/10.53660/clm-4374-24v38
Buthaynah, A. (2024). AI in learning English: Enhancing English skills through the use of AI-powered language learning tools. International Journal of Education and Social Science Research, 7(5), 82-94. https://doi.org/10.37500/ijessr.2024.7508
Carol, A., Chapelle, S., Baghestani, S., Beck, J., Kurt, Ş., Kusumaningrum, W. R., Kim, H. J., & Yin, S. (2024). Exploring Open AI in language teacher professional development. 217-242. https://doi.org/10.31274/isudp.2024.154.13
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
Easaw, A. A. (2024). The double-edged sword of artificial intelligence (AI) in education. The Journal of Quality in Education. https://doi.org/10.37870/joqie.v14i24.450
Emmanuel, A. K. (2021). Exploring the use of artificial intelligent systems in STEM classrooms. 82. https://doi.org/10.7916/D8-QFYK-KP13
Fahad, A., Aljabr, A., Ahmed, A., Hassan, M., & Al-Ahdal, M. (2024). Ethical and pedagogical implications of AI in language education: An empirical study at Ha'il University. Acta Psychologica, 251, 104605. https://doi.org/10.1016/j.actpsy.2024.104605
Fengyao, S., Peiyao, T., Daner, S., Yanhua, F., & Yuqin, Y. (2024). Pre-service teachers' inclination to integrate AI into STEM education: Analysis of influencing factors. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13469
Galip, K. (2023). Contemporary language teaching and learning with ChatGPT. 1(1). https://doi.org/10.62601/crll.v1i1.10
Hao, X. (2024). EFL school teacher’s AI assessment literacy: An exploratory study. 137-150. https://doi.org/10.31274/isudp.2024.154.09
Hui-Chin, Y. (2024). The synergy of generative AI and inquiry-based learning: Transforming the landscape of English teaching and learning. Interactive Learning Environments. https://doi.org/10.1080/10494820.2024.2335491
Idowu, S. A., Adeniyi, C. A., Olabisi, O. A., & Adeleye, M. (2024). A review of AI-driven pedagogical strategies for equitable access to science education. Magna Scientia Advanced Research and Reviews. https://doi.org/10.30574/msarr.2024.10.2.0043
Jan, D., Heil, J., & Ifenthaler, D. (2024). Evidence-based development of an instrument for the assessment of teachers' self-perceptions of their artificial intelligence competence. Educational Technology Research and Development. https://doi.org/10.1007/s11423-024-10418-1
Kevin, K.-W. C., & Ko-Wai, T. (2024). Evaluating English teachers’ artificial intelligence readiness and training needs with a TPACK-based model. World Journal of English Language, 15(1), 129-129. https://doi.org/10.5430/wjel.v15n1p129
Komelia, L. (2018). Readiness for artificial intelligence. 235-238. https://doi.org/10.1109/SISY.2018.8524740
Lin, H. (2024). The impact of STEM teacher competence on job performance in the era of artificial intelligence. https://doi.org/10.1109/cste62025.2024.00070
Małgorzata, N.-M. (2024). Artificial intelligence in the teacher's work. 29-54. https://doi.org/10.24917/9788368020403.3
Mihyun, S. (2023). Analysis of the necessity of AI utilization and digital competencies and use cases for science teachers. Brain, Digital, & Learning, 13(3). https://doi.org/10.31216/bdl.20230015
Musa, A. A., & Sanusi, I. T. (2023). Perceptions of STEM vs. non-STEM teachers toward teaching artificial intelligence. 1-5. https://doi.org/10.1109/africon55910.2023.10293455
Nam, J. K., & Min, K. K. (2022). Teacher’s perceptions of using an artificial intelligence-based educational tool for scientific writing. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.755914
Nicky, H. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal. https://doi.org/10.1177/00336882231168504
Nikolaï, T., & Damyanov, I. (2024). Attitudes of students – future teachers, for the application of generative artificial intelligence. Strategii na obrazovatelnata i naučnata politika, 32(4), 383-394. https://doi.org/10.53656/str2024-4-1-att
Nur, M. Z., Zainuddin, N., Bukhari, N. A., & Mohamad, M. (2024). Implementation of artificial intelligence (AI) as a pedagogical tool in tertiary ESL classroom: Teachers' perspectives. International Journal of Academic Research in Business & Social Sciences. https://doi.org/10.6007/ijarbss/v14-i8/22456
Oktian, F. N., Hikmawaty, L., & Juwita, S. R. (2024). Artificial intelligence technology embedded in high school science learning: A study of teacher perception. Pedagonal: Jurnal Ilmiah Pendidikan, 8(2), 132-143. https://doi.org/10.55215/pedagonal.v8i2.16
Oluwanife, S. F., & Kok, P. J. (2024). Artificial intelligence tools usage: A structural equation modeling of undergraduates’ technological readiness, self-efficacy, and attitudes. Journal for STEM Education Research. https://doi.org/10.1007/s41979-024-00132-1
Pooja, N., & RameshKumar, M. (2024). Navigating teachers' adoption of artificial intelligence in English foreign language: Uncovering inhibitors and drivers. 1(2). https://doi.org/10.69848/sreports.v1i2.4960
Ramazan, Y., & Özer-Altınkaya, Z. (2024). AI in the language classroom: Insights from pre-service English teachers. E-learning and Digital Media. https://doi.org/10.1177/20427530241267011
Sabaruddin, S., Purnama, D. A., Harmilawati, H., Aminah, S., Irmayani, I., Takdir, T., & Ar, A. (2024). Artificial intelligence in English language teaching: A study of English teachers' TPACK. Globish, 13(2), 125-125. https://doi.org/10.31000/globish.v13i2.11250
Sophia, M., Jones, L., & del Barrio-García, S. (2024). AI in the L2 classroom: Serving language educators through professional development. L2 Journal, 16(1). https://doi.org/10.5070/l2.21198
Soumya, T. V., & Selvaraj, A. (2024). Attitude towards AI. In Advances in Educational Marketing, Administration, and Leadership (pp. 293-308). https://doi.org/10.4018/979-8-3693-7016-2.ch014
S. A. (2024). Exploring the impact of artificial intelligence on transforming physics, chemistry, and biology education. https://doi.org/10.21428/a70c814c.747297aa
Ting, Y. (2024). Evaluation of the effect of generative AI in English writing class. Journal of Education, Humanities and Social Sciences, 38, 279-285. https://doi.org/10.54097/t9echq16
Valentyna, L., & Kornieva, Z. (2024). Generative AI in student essays: English teachers' perspectives on effective assessment methods. XLinguae, 17(4), 235-250. https://doi.org/10.18355/xl.2024.17.04.14
Xiaochao, Y., & Huang, X. (2024). Study on college English teachers’ attitudes and acceptance of AI-driven language learning applications. https://doi.org/10.26689/ief.v2i6.7621
Yimin, N., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the relationship between knowledge elements. Sustainability. https://doi.org/10.3390/su16030978
Zada, K., Seidaliyeva, G., Degtyareva, X., & Yessenaman, S. (2024). Eclecticism in language teaching: Developing educational and methodological content for an English language qualification course using artificial intelligence. XLinguae, 17(4), 111-137. https://doi.org/10.18355/xl.2024.17.04.08