Artificial Intelligence, Resources and Technology, and Academic Achievement among Global Learners

Authors

Dhebie T. Lecaniel

Education Department/La Carlota City College/6130 (Philippines)

Article Information

DOI: 10.47772/IJRISS.2026.100701029

Subject Category: Education

Volume/Issue: 10/7 | Page No: 15086-15097

Publication Timeline

Submitted: 2026-08-06

Accepted: 2026-08-12

Published: 2026-08-20

Abstract

This study investigated the relationship between artificial intelligence (AI), resources and technology, and academic achievement among global learners using a quantitative correlational research design. The respondents consisted of 279 Grade 7 students from 12 schools in the Pendergast Elementary School District, Avondale, Arizona, USA, representing diverse cultural and academic backgrounds. Data were gathered through a structured questionnaire covering demographic profiles, AI utilization, and technology experiences. Findings revealed that students demonstrated a moderate level of AI utilization, recognizing its relevance for academic tasks but showing limited confidence and motivation for deeper engagement. Resources and technology experiences were generally high, with strong access to basic digital platforms but limited exposure to advanced tools. Academic achievement was satisfactory overall, with comparable performance across demographic groups. Results indicated no significant differences in AI utilization, resources, or achievement based on age, though gender influenced AI engagement. Importantly, a statistically significant but weak relationship existed between AI utilization and academic achievement, suggesting that while AI contributed positively, it was not the sole determinant of success. Resources and technology experiences showed no significant impact on achievement, implying that instructional quality and learner related factors played a greater role.

Keywords

Academic Achievement, Artificial Intelligence, Digital Learning, Educational Equity

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References

1. Alvarez, P., Mempin, C., Morales, G., & Ocampo, A. (2023). School management system and governance of elementary school heads as perceived by the school community. International Journal of English Literature and Social Sciences, 8(3), 18. https://doi.org/10.22161/ijels.83.18 [Google Scholar] [Crossref]

2. Bond, M., Marín, V. I., & Zawacki-Richter, O. (2024). Digital technologies and equitable access in education. Computers & Education, 195, 104712. https://doi.org/10.1016/j.compedu.2024.104712 [Google Scholar] [Crossref]

3. Chan, K., & Hu, Y. (2023). Student willingness to invest time in learning artificial intelligence: The role of ease and relevance. Journal of Learning Analytics, 10(1), 55–72. https://doi.org/10.18608/jla.2023.10.1.55 [Google Scholar] [Crossref]

4. Chiu, L. (2023). Developing student confidence in artificial intelligence through authentic learning tasks. Computers & Education, 190, 104605. https://doi.org/10.1016/j.compedu.2023.104605 [Google Scholar] [Crossref]

5. Crompton, H., & Burke, D. (2023). The role of educators in fostering positive attitudes toward artificial intelligence. Educational Technology Research and Development, 71(2), 345–362. https://doi.org/10.1007/s11423-023-10123-7 [Google Scholar] [Crossref]

6. Kasneci, E., Seufert, T., & Kruse, S. (2023). Artificial intelligence in education: Practical applications and student perceptions. International Journal of Artificial Intelligence in Education, 33(1), 1–25. https://doi.org/10.1007/s40593-023-00345-2 [Google Scholar] [Crossref]

7. Liu, D., Tang, X., & Wang, X. (2025). Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis. Computers and Education: Artificial Intelligence, 8, 100400. https://doi.org/10.1016/j.caeai.2025.100400 [Google Scholar] [Crossref]

8. Mariyono, J., & Alif, M. (2025). Artificial intelligence and inclusivity in global education: Personalizing learning experiences. International Journal of Educational Technology, 42(2), 115–132. https://doi.org/10.1080/ijet.2025.42.2.115 [Google Scholar] [Crossref]

9. Ng, W., Lim, C., & Tan, J. (2023). AI literacy and instructional support in effective utilization of artificial intelligence. Education and Information Technologies, 28(4), 5123–5142. https://doi.org/10.1007/s10639-023-11567-9 [Google Scholar] [Crossref]

10. 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. https://tech.ed.gov/ai-report/ [Google Scholar] [Crossref]

11. UNESCO. (2024). Artificial intelligence in education: Ethics, inclusivity, and equitable access. Paris: UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000387654 [Google Scholar] [Crossref]

12. Volungevičienė, A., Teresevičienė, M., & Daukšienė, E. (2021). Review and validation of the benchmarking of technology enabled learning (TEL) toolkit: Assessing institutional digital infrastructure and research software capabilities. International Journal of Educational Technology in Higher Education, 18(1), 1–23. https://doi.org/10.1186/s41239-021-00265-5 [Google Scholar] [Crossref]

13. Yurt, E., & Kasarci, H. (2024). A questionnaire of artificial intelligence use motives: A contribution to investigating the connection between AI and motivation. Computers & Education, 195, 104712. https://doi.org/10.1016/j.compedu.2024.104712 [Google Scholar] [Crossref]

14. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2023). Students’ interest in artificial intelligence through active participation and problem-solving. Computers in Human Behavior, 139, 107502. https://doi.org/10.1016/j.chb.2023.107502 [Google Scholar] [Crossref]

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