ACCURACY OF MATHEMATICAL CRITICAL THINKING SKILLS ASSESSMENT WITH A MODERN APPROACH: GENERALIZED PARTIAL CREDIT MODEL
Abstract
Critical thinking skills mathematical critical thinking skills are essential to face the challenges of the 21st century. These skills in schools is still not optimal because it is not supported by valid and reliable instruments. Instruments that are valid and reliable. This study aims to measure mathematical critical thinking skills through the Generalized Partial Credit Model (GPCM) approach, to increase the accuracy of the assessment. The test instrument used is an indicator-based description test FRISCO (Focus, Reason, Inference, Situation, Clarity, and Overview). The quantitative research method with an experimental design was applied to seventh grade students in four public junior high schools, North Bahar District, Muaro Jambi. North Bahar, Muaro Jambi. Data analysis using GPCM with software PARSCALE 4.1 SOFTWARE. The p value of the fit test of 0.335 (> 0.05) indicates that the question fit the GPCM model. Student ability estimates ranged from -2.23 to 2.35, with the majority in the low ability category. Item parameters showed discrimination values of 0.855-1.534 and difficulty levels of -0.123 to 0.238, indicating good quality and balanced questions. Test information function showed that the instrument effectively measured students' abilities at various levels. These results prove that GPCM is appropriate for developing a valid, valid, and balanced mathematical critical thinking assessment instrument valid, accurate, and informative.
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References
Adhikari, N. P. (2023). The Use of Critical Thinking for Organizational Decisions. GS WOW: Wisdom of Worthy Research Journal, 1(1), 47–55. https://doi.org/https://doi.org/10.5281/zenodo.10440809
Aji, N. W., & Retnawati, H. (2024). Perbandingan Kecocokan Model Analisis Teori Respons Butir Pada Data Politomi. Jurnal Statistika Dan Sains Data, 1(2), 31–47. https://doi.org/10.21831/jssd.v1i2.18484
Arini, R., Riansi, E. S., Fadillah, I., & Hasan, M. K. (2024). Peran Tes Objektif dan Subjektif Dalam Mengukur Keterampilan Berfikir Matematis Siswa Sekolah Dasar. Jurnal Inovasi Dan Riset Pendidikan Matematika, 5(3), 236–244. http://www.jurnal.untirta.ac.id/index.php/wilangan%0Ap-ISSN
Atiaturrahmaniah, A., Arnyana, I. B. P., & Suastra, I. W. (2022). Peran Model Science, Technology, Engineering, Arts, And Math (STEAM) Dalam Meningkatkan Berpikir Kritis Dan Literasi Sains Siswa Sekolah Dasar. JPGI (Jurnal Penelitian Guru Indonesia), 7(4), 368–375. https://doi.org/http://dx.doi.org/10.29210/022537jpgi0005
Bahar, R., & Retnawati, H. (2022). Analisis Karakteristik Soal Kemampuan Koneksi Matematika Penskoran Politimus. JURNAL TARBIYAH, 29, 195. https://doi.org/10.30829/tar.v29i2.1650
Cahayu, A., Siburian, J., Hamidah, A., & Falani, I. (2024). A Rasch Model Analysis in Measuring students’ Critical Thinking Skills in science learning model Problem-Based Learning (PBL) Based on Local Wisdom Article history Abstract Keyword Rasch Model Critical Thinking Science Learning Problem-Based Local Wisdom. Jurnal Pendidikan Sains Universitas Muhammadiyah Semarang, 12(1), 786–2339. https://doi.org/https://doi.org/10.26714/jps.12.1.2024.1-8
Dewanti, S. S., Yogyakarta, U. N., Sunan, U. I. N., & Yogyakarta, K. (2021). The Application of Item Response Theory in Analysis of Characteristics of Mathematical Literacy Test Items. İlköğretim Online, 20(1), 1226–1237. https://doi.org/10.17051/ilkonline.2021.01.119
Falani, I. (2023). Desain dan Validasi Aplikasi Tes Literasi Matematika Berbasis Komputer dengan Pendekatan Item Response Theory. Edu-Sains: Jurnal Pendidikan Matematika Dan Ilmu Pengetahuan Alam, 12(2), 16–28. https://doi.org/10.22437/jmpmipa.v12i2.26716
Falani, I., Akbar, M., & Naga, D. S. (2020a). Comparison of the Accuracy of Item Response Theory Models in Estimating Student â€TM s Ability. Journal of Educational Science and Technology, 6(2), 178–184. https://doi.org/https://doi.org/10.26858/est.v6i2.13295
Falani, I., Akbar, M., & Naga, D. S. (2020b). The Precision of Students’ Ability Estimation on Combinations of Item Response Theory Models. International Journal of Instruction, 13(4), 545–558. https://doi.org/https://doi.org/10.29333/iji.2020.13434a
Harsana, F. N., & Lumenyela, R. A. (2024). Comparison Of Item Characteristic Analysis Models Of Reading Literacy Test With Polytomous Item Response Theory. REID (Research and Evaluation in Education), 10(2). https://doi.org/https://doi.org/10.21831/reid.v10i2.77852 INTRODUCTION
Liu, D. T. (2024). A Scoping Review Of Rasch Analysis And Item Response Theory In Otolaryngology: Implications And Future Possibilities. In Laryngoscope Investigative Otolaryngology (Vol. 9, Issue 1). https://doi.org/10.1002/lio2.1208
Luo, Y. (2018). Parameter Recovery with Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation for the Generalized Partial Credit Model. National Center for Assessment in Saudi Arabia, 1–36. https://doi.org/https://doi.org/10.48550/arXiv.1809.07359
Mardhiyah, R. H., Aldriani, S. N. F., Chitta, F., & Zulfikar, M. R. (2021). Pentingnya Keterampilan Belajar Di Abad 21 Sebagai Tuntutan Dalam Pengembangan Sumber Daya Manusia. Lectura: Jurnal Pendidikan, 12(1), 29–40. https://doi.org/http://dx.doi.org/10.31849/lectura.v12i1.5813
Muraki, E. (1992). A Generalized Partial Credit Model: Application Of An EM Algorithm Index Terms: Item Response Model, National Assess-Ment Of Educational Progress, Nominal Response Model, Partial Credit Model, Polytomous Response Model, Rating Scale Model. Applied Psychological Measurement, Uj 1, 159–176. https://doi.org/https://hdl.handle.net/11299/115645
Mursidah, M., Rosjanuardi, R., & Juandi, D. (2023). Kemampuan Berpikir Kritis Dalam Pemecahan Masalah Matematika; Systematic Literatur Review. JPMI (Jurnal Pembelajaran Matematika Inovatif), 6(4), 1421–1430. https://doi.org/https://doi.org/10.22460/jpmi.v6i4.17933
Niken, Somayasa, W., Budiman, H., Ruslan, & Adi Wibawa, G. N. (2024). Uji Goodness of Fit Dengan Statistik Pulkstenis - Robinson Dalam Model Regresi Logistik Ordinal. Jurnal Matematika Komputasi Dan Statistika, 4(1), 571–576. https://doi.org/10.33772/jmks.v4i1.72
Prayoga, K. P., Suryana, D., Supriatna, M., & Budiman, N. (2024). Penggunaan Rasch Model Untuk Menganalisis Konstruk Instrumen Kontrol Diri Pada Siswa Sekolah Menengah. G-Couns: Jurnal Bimbingan Dan Konseling, 9(1), 367–381. https://doi.org/10.31316/gcouns.v9i1.4459
Safitri, I., Lestarani, D., Imtikhanah, R. D. N. W., Akbarini, N. R., Sari, M. W., Fitrah, M., & Hapsan, A. (2024). Teori Pengukuran dan Evaluasi. CV. Ruang Tentor.
Satria, M. R. (2024). Transformasi Standar Penilaian Pendidikan Dan Revitalisasi Penilaian Pembelajaran Di Indonesia. Jurnal Penelitian Kebijakan Pendidikan, 17(1), 57–66. https://doi.org/10.24832/jpkp.v17i1.930
Tohani, E., & Aulia, I. (2022). Effects Of 21st Century Learning On The Development Of Critical Thinking, Creativity, Communication, And Collaboration Skills. Journal of Nonformal Education, 8(1), 46–53. https://doi.org/https://doi.org/10.15294/jne.v8i1.33334
Zainal, N. F. (2020). Pengukuran, Assessment dan Evaluasi dalam Pembelajaran Matematika. Laplace : Jurnal Pendidikan Matematika, 3(1), 8–26. https://doi.org/10.31537/laplace.v3i1.310
Zalukhu, H., Naibaho, T., & Simanjuntak, R. M. (2023). Evaluasi dan Penilaian pada Pembelajaran Matematika. Journal on Education, 6(01), 4781–4792. https://doi.org/https://doi.org/10.31004/joe.v6i1.3634
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