Developing and Evaluating an AI Prompt Blueprint for Inter-active Seventh-Grade Mathematics Media
DOI:
https://doi.org/10.57255/intellect.v5i01.1816Keywords:
Prompt Engineering, Canva Code, Grade 7 mathematics, generative AI, ADDIEAbstract
This study developed and evaluated a structured AI prompt blueprint for generating interactive Grade 7 mathematics learning media using Canva Code. Guided by the ADDIE model, the research and development project produced 14 prompts addressing lines and angles, plane geometry, and statistics. Five experts evaluated the prompts and generated media, three mathematics teachers completed a 22-item response questionnaire, and 27 students answered six statements before and after using the media. Normalized expert-rating summaries were 0.90 for the prompts and 0.91 for the media. The teachers’ mean response was 4.61/5 (92.12% of the maximum possible score), while students’ mean item responses increased from 1.98 to 4.20 (normalized score change = 0.73). The available aggregated records do not permit verification of item-level Aiken’s V or calculation of Cohen’s kappa, and the six student statements have not been established as a mathematics achievement test. Accordingly, the findings indicate favorable initial ratings and questionnaire responses but do not establish causal improvements in mathematical proficiency. The study contributes a documented prompt-design workflow that distinguishes prompt evaluation from evaluation of AI-generated instructional media and underscores the need for human review and further validation.
Abstrak
Penelitian ini mengembangkan dan mengevaluasi blueprint prompt AI untuk pembuatan media matematika interaktif kelas VII menggunakan Canva Code. Penelitian pengembangan dengan model ADDIE menghasilkan 14 rancangan prompt pada materi garis dan sudut, bangun datar, serta statistika. Lima ahli menilai rancangan prompt dan media; tiga guru mengisi 22 butir angket respons; dan 27 siswa mengisi enam pernyataan sebelum dan sesudah penggunaan media. Ringkasan penilaian ahli yang dinormalisasi adalah 0,90 untuk prompt dan 0,91 untuk media. Rerata respons guru adalah 4,61 dari 5 (92,12% skor maksimum). Rerata skor per butir siswa berubah dari 1,98 menjadi 4,20, dengan perubahan ternormalisasi 0,73. Data yang tersedia tidak memungkinkan verifikasi Aiken’s V per butir maupun Cohen’s Kappa; enam butir siswa juga belum dapat dipastikan sebagai tes prestasi matematika. Dengan demikian, temuan mendukung kelayakan awal rancangan dan respons positif dalam uji coba terbatas, tetapi belum membuktikan peningkatan hasil belajar secara kausal. Penelitian ini memberikan kontribusi berupa alur kerja perancangan prompt yang terdokumentasi—yang membedakan antara evaluasi prompt dengan evaluasi media pembelajaran hasil AI—serta menekankan pentingnya tinjauan oleh manusia dan validasi lebih lanjut.
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