SPEKTRUM RESPONS MAHASISWA PADA MASALAH PERSAMAAN DIFERENSIAL

Fransiskus Nendi -  Universitas Katolik Indonesia Santu Paulus Ruteng, Indonesia
Maximus Tamur* -  Universitas Katolik Indonesia Santu Paulus Ruteng, Indonesia
Emilianus Jehadus -  Universitas Katolik Indonesia Santu Paulus Ruteng, Indonesia
Kristianus Viktor Pantaleon -  Universitas Katolik Indonesia Santu Paulus Ruteng, Indonesia
Viviana Murni -  Universitas Katolik Indonesia Santu Paulus Ruteng, Indonesia

DOI : 10.24269/silogisme.v6i1.3688

Mahasiswa pada umumnya memiliki respons bervariasi terhadap masalah persamaan diferensial (PD) koefisien konstan non homogen. Spektrum respons diperlukan untuk mengetahui level pemahaman mahasiswa pada suatu masalah PD non homogen. Dalam literatur telah dijelaskan bahwa spektrum respon siswa dapat dipahami dengan berbagai cara. Meski demikian, penggunaan Taksonomi SOLO untuk memahami spektrum respon mahasiswa belum banyak dijelajahi. Sebagai upaya mengisi kesenjangan ini maka kami melakukan penelitian deskriptif kualitatif ini untuk mendeskripsikan spektrum respons mahasiswa terhadap masalah persamaan diferensial (PD) koefisien kontan non homogen berbasis taksonomi SOLO. Subjek penelitian ini adalah mahasiswa program studi pendidikan matematika yang memprogramkan mata kuliah persamaan diferensial (PD) tahun akademik 2020/2021. Seluruh subjek penelitian ditetapkan dengan mempertimbangkan kemampuan yang setara pada mata kuliah ini. Masalah PD yang diberikan kepada subyek penelitian tentang PD non homogeny yang diselesaikan menggunakan metode koefisien tak tentu. Hasil penelitian menunjukkan bahwa spektrum respons mahasiswa terhadap masalah persamaan diferensial (PD) koefisien kontan non homogen berbasis taksonomi SOLO, antara lain: mahasiswa menjelaskan masalah menggunakan kalimat sendiri tanpa mengubah arti, menggunakan beberapa informasi yang didapat melalui pembentuk solusi partikular, kemudian informasi tersebut untuk menyelesaikan masalah, memadukan penggalan-penggalan informasi yang terpisah untuk menghasilkan penyelesaian dari suatu masalah, memecahkan masalah secara bertahap, dan memberikan solusi masalah dengan benar. Dengan demikian dapat disimpulkan bahwa respons mahasiswa  terhadap masalah PD koefisien kontan non homogen berada pada tingkat relational

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Keywords
, persamaan diferensial, taksonomi SOLO
  1. Afriyani, D., Sa, C., Muksar, M., & Malang, U. N. (2018). Characteristics of Students ’ Mathematical Understanding in Solving Multiple Representation Task based on Solo Taxonomy. International Electronic Journal of Mathematics Education, 13(3), 281–287. https://doi.org/doi.org/10.12973/iejme/3920
  2. Aripin, M. A., Hamzah, R., Setya, P., Hisham, M. H. M., & Ishar, M. I. M. (2020). Unveiling a new taxonomy in education field. International Journal of Evaluation and Research in Education, 9(3), 524–530. https://doi.org/10.11591/ijere.v9i3.20458
  3. Caniglia, J. C., & Meadows, M. (2018). An Application of The Solo Taxonomy to Classify Strategies Used by Pre-Service Teachers to Solve “ One Question Problems .” Australian Journal of Teacher Education, 43(9), 74–89. https://doi.org/10.14221/ajte.2018v43n9.5
  4. Elazzabi, A., & Kaçar, A. (2020). Investigation of Libyan and Turkish
  5. students ’ thinking levels in solving quadratic word problems based on SOLO Taxonomy. Pegem Eğitim ve Öğretim Dergisi, 10(1), 283–316. https://doi.org/10.14527/pegegog.2020.010
  6. Exacta, A. P., Sujadi, I., & Subanti, S. (2015). Respons Mahasiswa Pendidikan Matematika Universitas Veteran Bangun Nusantara dalam Menyelesaikan Soal Logika Berdasar Taksonomi SOLO. Jurnal Elektronik Pembelajaran Matematika, 3(10), 1057–1065.
  7. Gil-Doménech, D., & Berbegal-Mirabent, J. (2020). Making the learning of mathematics meaningful: An active learning experience for business students. Innovations in Education and Teaching International, 57(4), 403–412. https://doi.org/10.1080/14703297.2020.1711797
  8. Jimoyiannis, A. (2011). Using SOLO taxonomy to explore students ’ mental models of the programming variable and the assignment statement. Themes in Science & Technology Education, 4(2), 53–74.
  9. Kaharuddin, A., & Hajeniati, N. (2020). An Identification of Students ’ Responses Based on Solo Taxonomy in Mathematics Learning Toward Learning Activities and Learning Outcomes. Al-Jabar: Jurnal Pendidikan Matematika, 11(2), 191–200.
  10. Kemal, I., Suryadi, & Rosyidi, U. (2019). Management of lecturers resource development at higher education. International Journal of Higher Education, 8(5), 246–256. https://doi.org/10.5430/ijhe.v8n5p246
  11. Korkmaz, F., & Unsal, S. (2017). Eurasian Journal of Educational Research www.ejer.com.tr. Eurasian Journal of Educational Research, 69, 75–92. https://doi.org/10.14689/ejer.2017.69.5
  12. Latipah, E., Kistoro, H. C. A., & Putranta, H. (2021). How are the parents involvement, peers and agreeableness personality of lecturers related to self-regulated learning? European Journal of Educational Research, 10(1), 413–425. https://doi.org/10.12973/EU-JER.10.1.413
  13. NCTM. (2000). Principles for School Mathematics. Reston: National Council of Teacher of Mathematics. https://www.nctm.org/uploadedFiles/Standards_and_Positions/PSSM_ExecutiveSummary.pdf
  14. Özdemir, A. şükrü, & Yildiz, S. göktepe. (2015). The Analysis of Elementary Mathematics Preservice Teachers ’ Spatial Orientation Skills with SOLO Model. Eurasian Journal of Educational Research, 61, 217–236. https://doi.org/10.14689/ejer.2015.61.12
  15. Standar Proses Pendidikan dan Menengah. Jakarta, Pub. L. No. 65, 1 (2013).
  16. Soltani, A. (2020). Influence of Motivating Science Class, Family, and Peer Models on Students’ Approaches to Learning Science: A Structural Equation Modeling Analysis. Research in Science Education, 50(5), 1665–1687. https://doi.org/10.1007/s11165-018-9748-1
  17. Stålne, K., Kjellström, S., & Utriainen, J. (2015). Assessment & Evaluation in Higher Education Assessing complexity in learning outcomes – a comparison between the SOLO taxonomy and the model of hierarchical complexity. Assessment & Evaluation in Higher Education, August. https://doi.org/10.1080/02602938.2015.1047319
  18. Vrachnos, E., & Jimoyiannis, A. (2017). Secondary education students ’ difficulties in algorithmic problems with arrays : An analysis using the SOLO taxonomy. Themes in Science & Technology Education, 10(1), 31–52.
  19. Widiyatmoko, A. (2018). The Effectiveness of Simulation in Science Learning on Conceptual Understanding : A Literature Review The Effectiveness of Simulation in Science Learning on Conceptual Understanding : A Literature Review. Journal of International Development and Cooperation, 24(1), 35–43.
  20. Williams, M. T., Lluka, L. J., Meyer, J. H. F., & Chunduri, P. (2019). SOLO-based task to improve self-evaluation and capacity to integrate concepts in first-year physiology students. Advances in Physiology Education, 43(19), 486–494. https://doi.org/10.1152/advan.00040.2019
  21. Wong, B., & Chiu, Y. L. T. (2020). University lecturers’ construction of the ‘ideal’ undergraduate student. Journal of Further and Higher Education, 44(1), 54–68. https://doi.org/10.1080/0309877X.2018.1504010

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Submitted: 2021-03-12
Published: 2021-12-19
Section: Artikel
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