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Salamin, A. D., Russo, D., & Rueger, D. (2023). ChatGPT, an excellent liar how conversational agent hallucinations impact learning and teaching. In Proceedings of the 7th International Conference on Teaching, Learning and Education.

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Article

Perceived AI – Tools Proficiency and Skill among Higher Education Science Major Students

1Teacher Education Program, St. Rita’s College of Balingasag, Inc., Misamis Oriental, Philippines


American Journal of Educational Research. 2025, Vol. 13 No. 9, 438-444
DOI: 10.12691/education-13-9-4
Copyright © 2025 Science and Education Publishing

Cite this paper:
Rene K. Abejaron Jr. Perceived AI – Tools Proficiency and Skill among Higher Education Science Major Students. American Journal of Educational Research. 2025; 13(9):438-444. doi: 10.12691/education-13-9-4.

Correspondence to: Rene  K. Abejaron Jr, Teacher Education Program, St. Rita’s College of Balingasag, Inc., Misamis Oriental, Philippines. Email: reneabejaron@srcb.edu.ph

Abstract

This study examined undergraduate science majors’ perceptions of AI tools (including ChatGPT), their own AI proficiency, and instructors’ AI proficiency at St. Rita’s College of Balingasag during the 2024–2025 academic year. Data were collected using a 30-item Synthetic Index of Use of Artificial Intelligence Tools (pilot Cronbach’s α = .96–.98) and summarized with descriptive statistics. Students perceived AI tools as effective for comprehension (M = 3.19), problem solving (M = 3.16), and productivity (M = 3.06), but less effective for creativity (M = 2.80) and broader educational enhancement (M = 2.87). Self-rated proficiency was proficient for prompt formulation (M = 3.03) and basic problem solving (M = 2.87), but developing for advanced features (≈ M = 2.68) and higher-order tasks such as evaluating AI outputs (M = 2.74) and applying AI feedback (M = 2.80). Students also perceived instructors’ integration of AI tools as limited. These findings indicate practical benefits alongside gaps in creativity, advanced student skills, and faculty implementation. Recommendations include scaffolded, discipline-specific AI training, sustained faculty development, and clear ethical use policies.

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