PEMBELAJARAN GENERATIF TERHADAP KEMAMPUAN PEMODELAN MATEMATIS: SYSTEMATIC LITERATURE REVIEW
DOI:
https://doi.org/10.51878/science.v6i4.14091Keywords:
Pembelajaran Generatif, Kemampuan Pemodelan Matematis, Pendidikan Matematika, Systematic Literature ReviewAbstract
ABSTRACT
The literature on generative learning and mathematical modeling has expanded, yet its direction, characteristics, and remaining research gaps have not been comprehensively mapped. This Systematic Literature Review (SLR) employed the PRISMA 2020 framework to identify, screen, assess eligibility, and synthesize publications addressing these two areas. The literature search was conducted through Scopus, ERIC, Google Scholar, and Garuda using keywords related to generative learning, mathematical modeling, and mathematics education. Of the 115 articles initially identified, 82 remained after duplicate removal and initial screening, 65 proceeded to title and abstract screening, and 32 ultimately met the criteria for synthesis following full-text assessment and quality assessment. The analyzed literature was dominated by quantitative studies and concentrated primarily on secondary education. Publications increased from 1 article in 2021 to 8 articles in both 2023 and 2024, before declining to 7 articles in 2025 and 3 articles in 2026. The main finding indicates that generative learning has been more frequently associated with problem solving, conceptual understanding, communication, and learning outcomes, whereas studies explicitly examining its role in developing mathematical modeling skills remain limited. Future research should therefore integrate mathematical modeling stages more explicitly and employ qualitative and mixed methods approaches to examine students’ thinking processes.
ABSTRAK
Perkembangan kajian mengenai generative learning dan kemampuan pemodelan matematis belum diikuti oleh pemetaan yang memperlihatkan arah, karakteristik, dan ruang kajiannya secara utuh. Systematic Literature Review (SLR) ini menggunakan alur PRISMA 2020 untuk menelusuri, menyaring, menilai kelayakan, dan mensintesis publikasi tentang kedua fokus tersebut. Penelusuran dilakukan melalui Scopus, ERIC, Google Scholar, dan Garuda dengan kata kunci yang berkaitan dengan generative learning, mathematical modeling, dan pendidikan matematika. Dari 115 artikel yang teridentifikasi, 82 artikel tersisa setelah penghapusan duplikasi dan penyaringan awal, 65 artikel dilanjutkan pada pemeriksaan judul dan abstrak, dan 32 artikel akhirnya memenuhi kriteria untuk sintesis setelah pemeriksaan teks lengkap serta quality assessment. Literatur yang dianalisis memperlihatkan dominasi penelitian kuantitatif dan konsentrasi pada jenjang pendidikan menengah. Publikasi meningkat dari 1 artikel pada 2021 menjadi 8 artikel pada 2023 dan 2024, kemudian menurun menjadi 7 artikel pada 2025 dan 3 artikel pada 2026. Temuan utama memperlihatkan bahwa generative learning lebih banyak dikaitkan dengan pemecahan masalah, pemahaman konsep, komunikasi, dan hasil belajar, sedangkan kajian yang secara eksplisit menempatkannya untuk mengembangkan pemodelan matematis masih terbatas. Kajian ini mengarahkan penelitian selanjutnya pada integrasi tahapan pemodelan yang lebih eksplisit serta penggunaan pendekatan kualitatif dan mixed methods untuk mengungkap proses berpikir siswa.
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