BRIDGING THE GAP: TEACHERS’ KNOWLEDGE AND APPLICATION OF AI-DRIVEN LEARNING PLATFORMS IN STEM-BASED ENGLISH LANGUAGE EDUCATION
Abstract
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.
References
Albitar, S., & Syarifudin. (2024). Challenges and opportunities for the application of AI in language learning in Indonesia. Transformational Language Literature and Technology Overview In Learning (TRANSTOOL), 3(1), 49-60. https://doi.org/10.55047/transtool.v3i1.1351
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
All articles published in English Review: Journal of English Education (ERJEE) are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright Ownership
Authors retain the copyright of their articles and grant ERJEE the right of first publication. The journal is granted a non-exclusive license to publish, reproduce, and distribute the article in any format, medium, or platform, provided that proper credit is given to the original authors.
License Terms – CC BY 4.0
Under the Creative Commons Attribution 4.0 International License, others are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially
As long as they:
- Provide appropriate credit to the original author(s) and source
- Provide a link to the license (https://creativecommons.org/licenses/by/4.0/)
- Indicate if any changes were made
There are no restrictions on the reuse, reproduction, or adaptation of published articles as long as attribution is properly given.
Author Warranties
By submitting a manuscript to ERJEE, authors confirm that:
- The work is original and does not infringe any existing copyright.
- The manuscript has not been previously published and is not under consideration elsewhere.
- All sources and references are appropriately acknowledged.
- Necessary permissions have been obtained for any copyrighted materials used.
