(untitled) (The International Journal of Educational Sciences and Arts, 2026)
This study aimed to identify artificial intelligence (AI) applications that can be used in teaching chemistry at the secondary level, to determine appropriate AI-based activities for chemistry instruction, and to examine the effect of activities based on AI applications on academic achievement in chemistry among secondary school female students. The researcher employed an experimental approach using a pre-test and post-test design, with a sample of (32) students. The results revealed statistically significant differences between the mean scores of the students in the pre- and post-tests in favor of the post-test, confirming the effectiveness of AI-based activities in improving academic achievement. The mean score increased from (6) in the pre-test to (19.625) in the post-test. The t-value reached (34.637) at a significance level of (0.01), indicating that the improvement was due to the educational intervention rather than chance. The findings also showed a very large effect size (Cohen’s d = 6.758), reflecting the strong impact of these activities. This improvement can be attributed to the role of AI-based activities in simplifying abstract chemical concepts through simulations and visual representations, as well as enhancing students’ motivation by breaking traditional teaching patterns and improving their ability to understand and represent chemical reactions using interactive applications and virtual laboratories.