The Reality of Employing Artificial Intelligence Applications in Teaching Science Subjects from Teachers' Perspectives: A Community Study
DOI:
https://doi.org/10.31185/eduj.Vol64.Iss2.5264Keywords:
Artificial Intelligence, Science Education, Community Study, Vocational Education.Abstract
This study aimed to investigate the reality of employing Artificial Intelligence (AI) applications in teaching science subjects from the perspectives of teachers at Al-Aqila Zainab Vocational Secondary School, as well as to identify their level of professional awareness and knowledge regarding AI, determine the major obstacles limiting its educational use, and explore developmental proposals to enhance its implementation in the teaching process. The study adopted a descriptive survey design and employed a questionnaire administered to a sample of 43 teachers. The instrument consisted of four main dimensions: the current status of AI implementation, awareness and professional knowledge, implementation obstacles, and developmental proposals, in addition to one open-ended question. The overall reliability coefficient of the instrument, measured using Cronbach’s Alpha, reached 0.89, indicating a high level of internal consistency. The findings revealed that the mean score for the implementation dimension was 3.79, while the awareness and knowledge dimension scored 3.66. The obstacles dimension recorded a mean of 4.15, whereas the developmental proposals dimension achieved the highest mean score of 4.20. The results also indicated that teachers generally held positive attitudes toward integrating AI applications into science teaching. However, effective implementation remains constrained by inadequate digital infrastructure, limited professional training opportunities, insufficient administrative support, and the absence of clear institutional guidelines. The study recommends expanding professional development programs, improving digital infrastructure, providing AI-supported educational platforms, and developing practical guidelines to promote the responsible pedagogical integration of AI applications in science education.
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References
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe Publishing.
Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Miao, F., & Holmes, W. (2021). Guidance for generative AI in education and research. UNESCO.
OECD. (2023). Digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/b14bef59-en
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO. https://unesdoc.unesco.org/
Weyant, L. E. (2022). Research methods for the social sciences: An introduction. Routledge.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0
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Copyright (c) 2026 م.م. زهراء كاظم علي ماهود، أ.م.د. صفاء عامر هاشم، .د. عمار عواد كاظم

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