TEACHERS’ ARTIFICIAL INTELLIGENCE COMPETENCE AND SELF-EFFICACY ON LEARNERS’ ACADEMIC PERFORMANCE

Author

SHIELA MARI C. LURIDO


Abstract

 This study aims to determine the relationship between teachers’ artificial intelligence (AI) competence and AI self-efficacy and learners’ academic performance in public elementary schools in the District of Angat, Schools Division of Bulacan, during School Year 2026–2027. Specifically, it seeks to assess teachers’ levels of AI competence and self-efficacy, examine learners’ academic performance, determine significant differences in teachers’ responses when grouped according to selected demographic and professional characteristics, and establish the relationships among the study variables. 

The study will adopt an explanatory sequential mixed-methods research design that calls for conducting a survey and a qualitative study. In this case, both quantitative and qualitative data will be collected, with the former being analyzed first, and the latter being used to explain the results. The total number of participants will be 258 public elementary school teachers selected through total enumeration. The data will be collected using valid and reliable research instruments to measure participants’ AI competence and efficacy. The learners’ achievement data will be extracted from their academic transcripts. The quantitative results will be analyzed using frequency, percentage, and mean, and standard deviation, tests of significant differences and correlation. The qualitative data will be analyzed thematically to expound on the quantitative results.

The results of the study will contribute to the understanding of how teachers’ ability to use artificial intelligence and their confidence in utilizing related tools in the field are likely to be connected to learners’ academic performance. The information will be useful in creating relevant professional development programs, enhancing responsible AI-informed education, and identifying approaches that can improve educational outcomes in public elementary schools.


Keywords

artificial intelligence competence, AI self-efficacy, academic performance, elementary education, explanatory sequential mixed-methods design



Full Text:

Download Paper PDF


References


  • Abar, C. A. A. P., dos Santos, J. M. D. S., & de Almeida, M. V. (2024). Contributions of the integration between computational thinking and artificial intelligence for mathematics education. In International Conference on Information Technology & Systems(pp. 290–299). Springer Nature Switzerland.
  • Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K–12 settings. AI and Ethics, 2, 431–440. https://doi.org/10.1007/s43681-021-00096-7
  • Al-Abdullatif, A. M. (2024). Modeling teachers’ acceptance of generative artificial intelligence use in higher education: The role of AI literacy, intelligent TPACK, and perceived trust. Education Sciences, 14(11), Article 1209. https://doi.org/10.3390/educsci14111209
  • Bautista, A., Estrada, C., Jaravata, A. M., Mangaser, L. M., Narag, F., Soquila, R., & Asuncion, R. J. (2024). Preservice teachers’ readiness towards integrating AI-based tools in education: A TPACK approach. Educational Process: International Journal, 13(3), 40–68. https://doi.org/10.22521/edupij.2024.133.3
  • Bryant, J., Heitz, C., Sanghvi, S., & Wagle, D. (2020, January 14). How artificial intelligence will impact K–12 teachers. McKinsey & Company. https://www.mckinsey.com/industries/education/our-insights/how-artificial-intelligence-will-impact-k-12-teachers
  • Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66, 616–630. https://doi.org/10.1007/s11528-022-00715-y
  • Chiu, T. K. F., Ahmad, Z., & Çoban, M. (2025). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30, 6667–6685. https://doi.org/10.1007/s10639-024-13094-z(Springer)
  • Chukwu, P. J., & Ibrahim, Y. K. (2022). AI-driven instructional innovations: Implications for teaching and learning in African schools. African Journal of Digital Education, 5(2), 33–47.
  • Deshen, M., Harari, R., & Aharony, N. (2026). Teachers’ artificial intelligence (AI) literacy: An exploratory study. Smart Learning Environments, 13, Article 7. https://doi.org/10.1186/s40561-026-00433-5(Springer)
  • Dimacali, V. N., Labao, N. M., Tayag, C. C., & Garcia, R. C. (2025). Exploring the external resource generation strategies of secondary public schools in San Luis, Pampanga. World Journal of Advanced Research and Reviews, 25(3), 1399–1410. https://doi.org/10.30574/wjarr.2025.25.3.0877
  • Dinopol, M. C., Camilo, J. B. C., & Oyangoren, M. O. (2025). School leaders’ strategies for teachers’ instructional functions in using AI-powered Edtech tools. Psychology and Education: A Multidisciplinary Journal, 41(2).
  • Eze, V. O., & Idowu, O. P. (2021). Teachers’ digital competence and readiness for artificial intelligence integration in secondary schools. International Review of Education Technology, 12(4), 52–67.
  • Galindo-Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126, 102381. https://doi.org/10.1016/j.ijer.2024.102381
  • Langreo, L. (2026, January 12). More teachers are using AI in their classrooms. Here’s why. Education Week. https://www.edweek.org/technology/more-teachers-are-using-ai-in-their-classrooms-heres-why/2026/01
  • Lu, J., Zheng, R., Gong, Z., & Xu, H. (2024). Supporting teachers’ professional development with generative AI: The effects on higher order thinking and self-efficacy. IEEE Transactions on Learning Technologies, 17, 1267–1277. https://doi.org/10.1109/TLT.2024.3369690
  • Mah, D.-K., & Groß, N. (2024). Artificial intelligence in higher education: Exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21, Article 58. https://doi.org/10.1186/s41239-024-00490-1
  • Manaig, K. A., Yazon, A. D., Buama, C. A. C., & Bonganciso, R. T. (2025). Teachers’ awareness in artificial intelligence and digital competence in the workplace. Advanced Journal of STEM Education, 3(1), 27–44. https://doi.org/10.31098/ajosed.v3i1.3302
  • Merrill, S. (2020). In schools, are we measuring what matters? Edutopia. https://www.edutopia.org/article/schools-are-we-measuring-what-matters
  • Mikeladze, T. (2024). A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review. European Journal of Education, 59(3), e12663. https://doi.org/10.1111/ejed.12663
  • Molenaar, I. (2022). Towards hybrid human-AI learning technologies. European Journal of Education, 57, 632–645. https://doi.org/10.1111/ejed.12527
  • Mousavinasab, E., Zarifsanaiey, N., Niakan Kalhori, S. R., Rakhshan, M., Keikha, L., & Ghazi Saeedi, M. (2021). Intelligent tutoring systems: A systematic review of characteristics, applications, and evaluation methods. Interactive Learning Environments, 29(1), 142–163. https://doi.org/10.1080/10494820.2018.1558257
  • Nwankwoala, H. C. O., Omonigho-Moses, E. J., & Hobobo-Moni, M. P. (2025). Teachers’ knowledge of artificial intelligence and its importance in enhancing teaching and learning in schools. International Journal of Scientific Research in Education, 18(4), 708–715.
  • Ogunleye, A. A. (2020). Enhancing pedagogy through artificial intelligence: The role of teacher competence. Journal of Modern Pedagogical Research, 6(3), 78–89.
  • Raguindin, C. (2025). Artificial intelligence in the teaching process in public elementary schools: Inputs to curriculum enhancement. The International Journal of Science, Technology and Engineering, 2(1).
  • San Gabriel, J. D., & Manalastas, A. S. (2025). Experimental skills of senior high school students on academic performance in chemistry. International Journal of Research Publication and Reviews,6(1), 2390-2406   https://doi.org/10.13140/RG.2.2.14229.64486
  • Silagan, B. L., & Tumapon, T. T. (2025). Technological competence, training and support, attitude towards AI, and teachers’ acceptance. Psychology and Education: A Multidisciplinary Journal, 36(8).
  • South African Broadband Education Networks. (2024, May 30). The role of AI in education: Transformative trends and future implications. SABEN. https://saben.ac.za/the-role-of-ai-in-education-transformative-trends-and-future-implications/
  • Subosa, M. (2026). Teachers’ knowledge, attitude, and practices on artificial intelligence (AI). International Journal of Research and Innovation in Social Science, 10(7), 4364–4400. https://doi.org/10.47772/ijriss.2026.100700296
  • Taşkın, T. (2026). Artificial intelligence in teacher education: Exploring the role of AI literacy on attitudes. Journal of Research in Innovative Teaching & Learning. Advance online publication. https://doi.org/10.1108/JRIT-03-2026-0082
  • S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. U.S. Department of Education.
  • Walton Family Foundation. (2023, March 1). Teachers and students embrace ChatGPT for education. https://www.waltonfamilyfoundation.org/learning/teachers-and-students-embrace-chatgpt-for-education
  • Winne, P. H. (2021). Open learner models working in symbiosis with self-regulating learners: A research agenda. International Journal of Artificial Intelligence in Education, 31(3), 446–459. https://doi.org/10.1007/s40593-020-00212-4
  • Yang, Y.-F., Tseng, C. C., & Lai, S.-C. (2024). Enhancing teachers’ self-efficacy beliefs in AI-based technology integration into English speaking teaching through a professional development program. Teaching and Teacher Education, 144, 104582. https://doi.org/10.1016/j.tate.2024.104582(ScienceDirect)
  • Yue, M., Jong, M. S.-Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29(15), 19505–19536. https://doi.org/10.1007/s10639-024-12621-2(The Chinese University of Hong Kong)
  • Zacamy, J., & Roschelle, J. (2022). Navigating the tensions: How could equity-relevant research also be agile, open, and scalable?Digital Promise. http://hdl.handle.net/20.500.12265/159

Share your valuable work from Social Media Buttons