Analysis of Problem-Solving Abilities Based on Student Proficiency Levels in D Phase
DOI:
https://doi.org/10.30587/didaktika.v30i2.7759Keywords:
Problem-Solving, Student Profiency Levels, Phase DAbstract
This study investigates the problem-solving abilities of seventh-grade students at SMP Muhammadiyah 1 Gresik in the context of flat-sided spatial figures. Employing a qualitative descriptive approach, the study involved three subjects representing varying levels of problem-solving abilities: excellent, moderate, and low. Data collection was conducted through tests, observations, and in-depth interviews. The findings revealed a range of problem-solving abilities among the three subjects. The student with excellent problem-solving skills demonstrated the ability to comprehend the problem, employ clear and rational strategies, construct accurate mathematical models, and thoroughly check their answers. The subject with moderate problem-solving skills exhibited an understanding of the problem and utilized rational strategies; however, they faced challenges in creating accurate models and drawing conclusions. The subject with low problem-solving skills encountered difficulties in comprehending the problem, selecting appropriate strategies, and correctly solving the problem. The study's conclusions emphasize the need for specialized attention and guidance for students with low problem-solving abilities to foster their effective problem-solving skills. Conversely, students with high problem-solving abilities can be provided with more complex challenges to optimize their capabilities. This research provides a foundation for teachers to tailor their support to students' individual problem-solving abilities in mathematics.
References
Anggraeni, R., & Kadarisma, G. (2020). Analisis Kemampuan Pemecahan Masalah Matematik Siswa Smp Kelas VII Pada Materi Himpunan. Jurnal Cendekia : Jurnal Pendidikan Matematika, 4(2), Article 2. https://doi.org/10.31004/cendekia.v4i2.334
Corte, E., Greer, B., & Verschaffel, L. (1996). Mathematics teaching and learning. https://www.semanticscholar.org/paper/Mathematics-teaching-and-learning.-Corte-Greer/b69cc5fe16e8d4155115febbbb12abc936ad4cc9
Ennis, R. H. (1993). Critical thinking assessment. Theory Into Practice, 32(3), 179–186. https://doi.org/10.1080/00405849309543594
Freudenthal, H. (2005). Revisiting Mathematics Education: China Lectures. Springer Science & Business Media.
Imroatun, S. (2014). Strategi Pemecahan Masalah Matematika Siswa Kelas VII SMP Kristen 2 Salatiga Ditinjau Dari Langkah Polya.
Khoerunnisa, G. M., & Imami, A. I. (2020). Analisis Kemampuan Pemecahan Masalah Matematis Siswa SMP Pada Materi SPLDV. Prosiding Sesiomadika, 2(1b), Article 1b. https://journal.unsika.ac.id/index.php/sesiomadika/article/view/2750
National Council of Teachers of Mathematics. (1999). Principles and Standards for School Mathematics. https://www.nctm.org/Standards-and-Positions/Principles-and-Standards/
OECD. (2019). PISA 2018 Results (Volume I): What Students Know and Can Do. OECD. https://doi.org/10.1787/5f07c754-en
Polya, G. (2004). How to Solve It: A New Aspect of Mathematical Method. Princeton University Press.
Rahmawati, A., & Warmi, A. (2022). Analisis Kemampuan Pemecahan Masalah Matematis Siswa SMP Pada Materi Teorema Pythagoras. Jurnal Cendekia : Jurnal Pendidikan Matematika, 6(1), 365–374. https://doi.org/10.31004/cendekia.v6i1.1012
Rio, M., & Pujiastuti, H. (2020). Analisis Kemampuan Pemecahan Masalah Matematik Siswa Smp Pada Materi Bilangan Bulat. AKSIOMA : Jurnal Matematika dan Pendidikan Matematika, 11(1), Article 1. https://doi.org/10.26877/aks.v11i1.6105
Sari, Y. P., Amilda, A., & Syutaridho, S. (2017). IDENTIFIKASI KEMAMPUAN KOGNITIF SISWA DALAM MENYELESAIKAN SOAL-SOAL MATERI BANGUN RUANG SISI DATAR. Jurnal Pendidikan Matematika RAFA, 3(2), 146–164. https://doi.org/10.19109/jpmrafa.v3i2.1738
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