ABSTRACT
The objective of this study was to validate, and assess the acceptability and efficacy of AI-generated science learning resources for students in Grade 7. In particular, it evaluated the resulting materials' quality, their degree of acceptability as judged by professionals, educators, and students, and artificial intelligence platform, as well as the pedagogical ramifications of incorporating AI-generated teaching materials into science lessons.
The study used a developmental and evaluative research methodology with a total of 69 Grade 7 students. AI-generated print and multimedia learning resources were created using the Grade 7 Science curriculum. Experts evaluated the materials based on their content (M = 3.6), format (M = 3.5), presentation and organization (M = 3.5), and information accuracy and timeliness (M = 4.0). For multimedia resources, experts graded content (M = 3.8), format/technical design (M = 4.0), presentation and organization (M = 3.8), and accuracy (M = 4.0) as very satisfactory. The materials' acceptability was determined by the replies of teachers (M = 3.6-4.0), students (M = 3.97-4.20), and other Artificial Intelligence Platform (3.26). Pre-test and post-test assessments were used to assess the materials' effectiveness, and data were analyzed using descriptive statistics and a paired samples t-test.
The results showed that pupils' performance improved dramatically from pre-test to post-test. The pre-test mean score was 16.1, while the post-test mean score was 37.8, resulting in a mean difference of 21.8. The paired samples t-test revealed a significant difference (t = 106, df = 68, p <.001), indicating a high effect of the intervention.
Based on these data, the study suggests that AI-generated Science learning materials are effective, valid, and widely accepted instructional resources that greatly increase students' academic performance in science. The incorporation of these materials is thus advised to improve teaching and learning in Grade 7 Science.
Keywords: AI-assisted content generation, curriculum alignment, multimedia instruction, expert validation, learner engagement, personalized learning
https://zenodo.org/records/21825127