1Graduate School, University of La Salette, Inc., Santiago City, Philippines
2Aguinaldo National High School, Schools Division Office-Ifugao, Department of Education, Philippines
American Journal of Educational Research.
2026,
Vol. 14 No. 3, 96-102
DOI: 10.12691/education-14-3-3
Copyright © 2026 Science and Education PublishingCite this paper: Marjorie L. Chinaman, Madeilyn B. Estacio, Romiro G. Bautista. Teachers’ Attitude, Competence, and Challenges in Using Artificial Intelligence in Teaching Secondary Science.
American Journal of Educational Research. 2026; 14(3):96-102. doi: 10.12691/education-14-3-3.
Correspondence to: Marjorie L. Chinaman, Graduate School, University of La Salette, Inc., Santiago City, Philippines. Email:
marjorie.chinaman@deped.gov.phAbstract
This study aimed to assess teachers’ attitudes, perceived competence, and challenges in using AI in teaching secondary science, examining differences based on age, sex, highest educational attainment, years of teaching experience, number of relevant trainings, and specialization. The study was conducted in the different high schools in the District II of Ifugao, Philippines. A quantitative descriptive research design was employed. Data were collected using an adapted questionnaire and analyzed using frequencies and percentages, and mean. Key findings indicated that teachers held a very positive attitude toward AI in science education, recognizing its ability to enhance learning, personalize instruction, and support critical thinking. Teachers perceived competence was examined using three domains: general competence, access to resources, and professional development. Respondents rated themselves very high (very competent) in general competence, demonstrating confidence in understanding AI concepts, integrating AI with traditional teaching methods, and evaluating AI’s effectiveness. Access to AI tools and support was also rated very high, with teachers reporting sufficient availability of software, technical support, and instructional materials. Professional development was rated high; teachers actively sought AI-related learning and perceived training opportunities as available, but the actual receipt, quality, and relevance of training were limited. The most severe challenges identified included concerns about data privacy, reliability of AI-based assessments, ethical issues, institutional policy ambiguity, and keeping up with rapid technological developments. The study recommends an action plan to enhance teachers’ knowledge and understanding of AI and its applications in science education, strengthen skills for integrating AI into lesson planning, instruction, and assessment aligned with MELCs, and promote ethical, responsible, and secure use of AI in compliance with DepEd data privacy and child protection policies.
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