AI Literacy and Academic Performance: A Cross-Sectional Analysis of Senior High School Students
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| Title: | AI Literacy and Academic Performance: A Cross-Sectional Analysis of Senior High School Students |
|---|---|
| Language: | English |
| Authors: | Stephen Jay Co (ORCID |
| Source: | International Journal of Technology in Education. 2026 9(2):476-490. |
| Availability: | International Society for Technology, Education, and Science. ISTES Organization, Monument, CO 80132. e-mail: istesorganization@gmail.com; e-mail: ijteoffice@gmail.com; Web site: https://www.ijte.net/index.php/ijte/about |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | High Schools Secondary Education Grade 11 Grade 12 |
| Descriptors: | Artificial Intelligence, Digital Literacy, High School Students, Technology Uses in Education, Technology Integration, Foreign Countries, Academic Achievement, Intellectual Disciplines, Grade 11, Grade 12 |
| Geographic Terms: | Philippines |
| ISSN: | 2689-2758 |
| Abstract: | This study investigates the relationship between artificial intelligence (AI) literacy and academic performance among senior high school students using the validated Artificial Intelligence Literacy Scale (AILS). A cross-sectional correlational study examined 525 students from four academic strands. Despite widespread AI tool adoption (85.7% use ChatGPT), learning remains predominantly informal and peer-driven rather than teacher-guided. AI literacy was measured across four dimensions: awareness, usage, evaluation, and ethics. Academic performance was assessed through grade point averages and standardized test scores. Results reveal significant positive relationships between AI literacy and academic performance (r = 0.27-0.28, p < 0.001), with awareness and ethics dimensions emerging as primary predictors over technical usage skills. AI literacy explained 7.2% of variance in grades and 7.7% of variance in test scores. Students demonstrated significant variations across academic strands--STEM students significantly outperformed business and general academic students, while humanities students achieved levels comparable to STEM students. This suggests interdisciplinary approaches combining critical thinking with technology understanding may be optimal for AI literacy development. The prominence of conceptual understanding over technical skills challenges prevailing assumptions about AI education priorities. Findings provide empirical evidence for integrating strand-specific AI literacy curricula and demonstrate urgent need for systematic AI literacy education to address current informal learning gaps in secondary education globally. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1506275 |
| Database: | ERIC |
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