Teachers' Readiness, Perceptions, and Use of Generative Artificial Intelligence in Educational Practice

Authors

  • Novia Ayu Lestari Universitas Bengkulu, Bengkulu, Indonesia
  • Agus Susanta Universitas Bengkulu, Bengkulu, Indonesia
  • Nurul Astuty Yensy Universitas Bengkulu, Bengkulu, Indonesia

DOI:

https://doi.org/10.52690/jswse.v7i3.1396

Keywords:

Artificial Intelligence in Education, Educational Technology Adoption, Generative Artificial Intelligence, Teacher Readiness

Abstract

This study examines teachers’ readiness, usage patterns, perceived benefits, barriers, and professional development needs related to integrating Generative Artificial Intelligence (Gen AI) into educational practice. A quantitative descriptive exploratory survey design was employed. Data were collected via online questionnaires from 80 teachers across multiple educational levels (early childhood to vocational secondary) in Bengkulu. Descriptive statistics and thematic analysis were used to analyse the data. Teachers reported high functional readiness and positive perceptions of Gen AI, particularly for lesson planning and content development, while its application for learning analytics and reflective pedagogical inquiry remained limited. The most significant barriers were lack of training and unclear school policies, whereas teachers did not view Gen AI as a threat to their professional role. Key professional development needs included practical training, ethical guidance, curriculum integration, and peer communities. The study provides empirical evidence on teachers actual pedagogical workflows in a developing‑country context, distinguishing functional readiness from conceptual literacy. Findings offer a clear agenda for policy development and teacher professional learning programmes. The research advances understanding of Gen AI integration in resource‑constrained settings and provides an evidence base for pedagogically grounded, ethically responsible AI adoption in education.

References

Akpan, I. J., & Akpan, A. A. (2024). Evolutionary Trends in Decision Sciences Education Research From Simulation and Games to Data Analytics and Generative Artificial Intelligence. https://doi.org/10.20944/preprints202407.1294.v1

Alam, A. (2021). Should Robots Replace Teachers? Mobilisation of AI and Learning Analytics in Education. 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3), 1–12. https://doi.org/10.1109/ICAC353642.2021.9697300

AlSagri, H. S., & Sohail, S. S. (2024). Evaluating the role of Artificial Intelligence in sustainable development goals with an emphasis on “quality education.” Discover Sustainability, 5(1), 458. https://doi.org/10.1007/s43621-024-00682-9

Alshorman, S. (2024). THE READINESS TO USE AI IN TEACHING SCIENCE: SCIENCE TEACHERS’ PERSPECTIVE. Journal of Baltic Science Education, 23(3), 432–448. https://doi.org/10.33225/jbse/24.23.432

BAİDOO-ANU, D., & OWUSU ANSAH, L. (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500

Barrett, A., & Pack, A. (2023). Not quite eye to A.I.: student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20(1), 59. https://doi.org/10.1186/s41239-023-00427-0

Brada, A., & Dahmani, F. (2024). Artificial Intelligence Technologies and Their Significance in Enhancing the Quality of Adaptive E-Learning. Journal of Science and Knowledge Horizons, 4(02), 30–47. https://doi.org/10.34118/jskp.v4i02.4007

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8

Chen, F., Li, Y., Chen, Y., Bian, Z., Duo, L., Zhou, Q., & Zhang, L. (2025). Strategies for the Analysis and Elimination of Hallucinations in Artificial Intelligence Generated Medical Knowledge. Journal of Evidence-Based Medicine, 18(3). https://doi.org/10.1111/jebm.70075

Creswell, J. W., & Creswell J. David. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (fifth Edition).

Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review. https://doi.org/10.1162/99608f92.8cd550d1

Fütterer, T., Fischer, C., Alekseeva, A., Chen, X., Tate, T., Warschauer, M., & Gerjets, P. (2023). ChatGPT in education: global reactions to AI innovations. Scientific Reports, 13(1), 15310. https://doi.org/10.1038/s41598-023-42227-6

Heine, S., & König, J. (2025). Applying artificial intelligence in teacher education: preservice teachers’ attitudes and reflections in using ChatGPT for teaching and learning. European Journal of Teacher Education, 48(5), 934–963. https://doi.org/10.1080/02619768.2025.2540791

Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533

Hwang, G. J., & Chen, N. S. (2023). Editorial Position Paper: Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions. Educational Technology and Society, 26(2). https://doi.org/10.30191/ETS.202304_26(2).0014

Jang, J., Jeon, J., & Jung, S. K. (2022). Development of STEM-Based AI Education Program for Sustainable Improvement of Elementary Learners. Sustainability, 14(22), 15178. https://doi.org/10.3390/su142215178

Kefi, H., Khelladi, I., Mani, Z., & Veg-Sala, N. (2024). AI-enabled social support chatbot usage: flowing ambivalence and liminalities. Journal of Decision Systems, 1–24. https://doi.org/10.1080/12460125.2024.2443226

Monib, W. K. (2024). Afghan undergraduate students’ perceptions toward e-learning. E-Learning and Digital Media, 21(6), 535–558. https://doi.org/10.1177/20427530231180029

Nazari, M., & Saadi, G. (2024). Developing effective prompts to improve communication with ChatGPT: a formula for higher education stakeholders. Discover Education, 3(1), 45. https://doi.org/10.1007/s44217-024-00122-w

Rudolph Jurgen, Tan Shannon, & Aspland Tania. (2023). Editorial 6(2): Personal digital assistant or job killer? Generative AI and the teaching profession in higher education. Journal of Applied Learning & Teaching, 6(2). https://doi.org/10.37074/jalt.2023.6.2.1

Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009

Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1), 54. https://doi.org/10.1186/s41239-021-00292-9

Tella, A. (2015). Electronic and paper based data collection methods in library and information science research. New Library World, 116(9/10), 588–609. https://doi.org/10.1108/NLW-12-2014-0138

Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440. https://doi.org/10.1016/j.compedu.2011.06.008

Tlili Ahmed, Huang Ronghuai, Yasir Mustafa Muhammad, Zhao Jialu, Bozkurt Aras, Xu Lin, Wang Huanhuan, Salha Soheil, Altinay Fahriye, Affouneh Saida, & Burgos Daniel. (2023). Speaking of transparency: Are all Artificial Intelligence (AI) literature reviews in education transparent? Journal of Applied Learning & Teaching, 6(2). https://doi.org/10.37074/jalt.2023.6.2.15

Toncelli Rachel, & Kostka Ilka. (2024). A Love-Hate Relationship: Exploring Faculty Attitudes Towards GenAI and Its Integration into Teaching. International Journal of TESOL Studies. https://doi.org/10.58304/ijts.20240306

Tondeur, J., Scherer, R., Siddiq, F., & Baran, E. (2020). Enhancing pre-service teachers’ technological pedagogical content knowledge (TPACK): a mixed-method study. Educational Technology Research and Development, 68(1), 319–343. https://doi.org/10.1007/s11423-019-09692-1

Veledar, B., Bašić, M., Demirović, L., & Beširević, E. (2024). Does Artificial Intelligence Represent a Threat to the Accounting Profession? Journal of Forensic Accounting Profession, 4(2), 67–85. https://doi.org/10.2478/jfap-2024-0010

Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798995

Yang, Y., Sun, W., Sun, D., & Salas-Pilco, S. Z. (2025). Navigating the AI-Enhanced STEM education landscape: a decade of insights, trends, and opportunities. Research in Science & Technological Education, 43(3), 693–717. https://doi.org/10.1080/02635143.2024.2370764

Zhai, X. (2025). Transforming Teachers’ Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices. Journal of Science Education and Technology, 34(6), 1323–1333. https://doi.org/10.1007/s10956-024-10174-0

Zhang, Y., & Dong, C. (2024). Unveiling the Dynamic Mechanisms of Generative AI in English Language Learning: A Hybrid Study Based on fsQCA and System Dynamics. Behavioral Sciences, 14(11), 1015. https://doi.org/10.3390/bs14111015

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Published

2026-05-16

How to Cite

Lestari, N. A., Susanta, A., & Yensy, N. A. (2026). Teachers’ Readiness, Perceptions, and Use of Generative Artificial Intelligence in Educational Practice. Journal of Social Work and Science Education, 7(3), 1949–1964. https://doi.org/10.52690/jswse.v7i3.1396

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