Jaki, Gnadia Rambu Nodu
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Desain Pembelajaran Berdiferensiasi Pada Materi Fungsi Linear Siswa Kelas VIII SMP Negeri 17 Kota Kupang Jaki, Gnadia Rambu Nodu; Samo, Damianus D.; Blegur, Irna Karlina Sensiana
Fraktal : Jurnal Matematika dan Pendidikan Matematika Vol 6 No 1 (2025): Mei 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/fractal.v6i1.16828

Abstract

Differentiated learning is a learning approach designed to address the diverse learning needs of students. The aim of this research is to develop a learning design that is suitable for the varying levels of understanding and competency among students, and is effective in meeting the specific learning needs of students at SMP Negeri 17 Kota Kupang, particularly in comprehending the topics related to linear functions, specifically the subchapter on gradients. The research methodology employed is design research, which involves three stages: the preliminary stage (initial design), the implementation stage (experimentation), and the retrospective analysis stage (retrospective analysis). Data collection techniques and instruments used include tests (diagnostic assessment and formative assessment), interviews, and observations. The data analysis techniques employed encompass qualitative and quantitative descriptive analysis. This research yields a learning design that caters to students' needs and provides ample learning opportunities. Each activity in LKPD aids students in grasping concepts such as determining the gradient of a straight line passing through a central point and another point, finding the gradient of a line passing through two points, determining the gradient of a line from its equation, and applying these skills to solve real-life problems involving gradients. The research findings indicate an improvement in students' understanding and abilities, thus confirming the effectiveness of the developed learning design in enhancing students' learning outcomes. Keywords: Differentiated Learning, Linear Function