http://pmat.ustjogja.ac.id/jurnal/index.php/indomath Vol 4, No. 2, August 2021, pp. 151-158 Copyright © Authors. This is an open access article distributed under the Attribution-NonCommercial- ShareAlike 4.0 International (CC BY-NC-SA 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Effect of GeoGebra- Assisted Learning Cycle 7e Model and Cognitive Style on the Mathematical Concepts Understanding Ability Santi Widyawati Universitas Nahdlatul Ulama Lampung, Indonesia, santiwidyawati24@gmail.com Fredi Ganda Putra Universitas Islam Negeri Raden Intan Lampung, Indonesia Bistari Universitas Tanjungpura Pontianak, Indonesia Hamdani Universitas Tanjungpura Pontianak, Indonesia ABSTRACT This research aimed to investigate the effects of 1) cognitive style on mathematical concepts understanding model; 2) the application of the GeoGebra-assisted Learning Cycle 7e Model on mathematical concepts understanding; 3) the interaction between the learning model group (Learning Cycle 7e Model, GeoGebra-assisted Learning Cycle 7e Model, and conventional learning model) and the cognitive styles on students' mathematical concepts understanding ability. The samples of this research were 90 eighths--grade students of SMPN 8 Metro determined using the cluster random sampling technique. The researchers employed the quasi-experimental design as the research method with tests as data collecting techniques. The two-way ANOVA test was used to find answers to the research questions. Based on the analysis results, it can be concluded that: 1) The application of the Learning Cycle 7e Model assisted by GeoGebra positively influenced students' mathematical concepts understanding; 2) cognitive style did not affect mathematical understanding ability; 3) there was no interaction between the learning model group and the cognitive style group on mathematical concepts understanding. Further researchers can combine the Learning Cycle 7e Model with other media and see students' cognitive styles differences to maintain the smooth learning process in the classroom. Keywords: Learning Cycle 7E, Geogebra, cognitive Style, Mathematical Understanding Concept. ABSTRAK Penelitian ini bertujuan untuk melihat pengaruh: 1) gaya kognitif terhadap kemampuan pemahaman konsep matematis; 2) penerapan model pembelajaran cycle 7e menggunakan geogebra terhadap kemampuan pemahaman konsep matematis; 3) interaksi antara kelompok model pembelajaran (model pembelajaran learning cycle 7E, model pembelajaran learning cycle 7E berbantuan geogebra dan model pembelajaran konvensional) dan kelompok gaya kognitif terhadap kemampuan pemahaman konsep matematis siswa. Sampel dalam penelitian ini ialah siswa kelas VIII SMPN 8 Metro yang berjumlah 75 siswa. Sampel diambil dengan menggunakan Teknik acak kelas. Quasi eksperimental design digunakan sebagai metode penelitian ini dengan teknik pengumpulan data menggunakan tes pemahaman konsep dan tes gaya kognitif. Uji two way Anova digunakan untuk mencari jawaban dari tujuan penelitian yang sebelumnya dilakukan uji normalitas dan uji homogenitas. Berdasarkan hasil uji, diperoleh simpulan bahwa: 1) Penerapan model pembelajaran learning cycle 7E dengan geogebra berpengaruh baik terhadap kemampuan pemahaman konsep matematis; 2) gaya kognitif tidak berpengaruh terhadap kemampuan pemahaman matematis; serta 3) tidak adanya interaksi antara kelompok model pembelajaran dan kelompok gaya kognitif terhadap kemampuan pemahaman konsep matematis. Bagi peneliti selanjutnya dapat menggunakan model learning cycle 7E dikombinasikan dengan media-media yang lain, serta dapat melihat perbedaan gaya kognitif siswa untuk keperluan kelancara proses belajar di kelas. Kata Kunci: Pembelajaran siklus 7E, Geogebra, Gaya Kognitif, Pemahaman Konsep Matematis. INTRODUCTION The way we think, communicate, convince the other person and draw conclusions is often based on analogy (Azmi, 2017). The analogy is part of inductive reasoning, where the way to conclude is based on previously known facts. Goswami (2004) reveals that reasoning by analogy is 152 Santi Widyawati, Fredi Ganda Putra, Bistari, and Hamdani The Effect of GeoGebra- Assisted Learning Cycle 7e Model and Cognitive Style on the Mathematical Concepts Understanding Ability widely accepted as a core component of human cognition. Analogous reasoning has long been believed to play an essential role in mathematics learning and problem-solving (Genter, Holyoak, & Kokinov, 2001). In addition, Hofstadter (Pearse & Walton, 2011) argues that analogy plays a vital role in problem-solving, decision making, perception, memory, creativity, emotion, explanation, and communication. Analogies in mathematics can help students understand another material by looking for similarities in properties between the material being compared (Kariadinata, 2012). The explanation about the importance of analogy ability illustrates that students' mathematical analogy skills need to be developed in learning activities. Mathematics is a subject that exists at all levels of the educational curriculum, from elementary school to university and even in everyday life (Fauzi et al., 2020; R. Utami & Endaryono, 2020). Therefore, students must possess good mathematical concepts understanding to face challenges in their daily lives (Fatimah, 2020; Rahmawati, 2019). Optimizing mathematical concepts understanding requires a solution, one of which is the learning models (Pratiwi, 2016; Sekfia et al., 2020; Suryati & Cahyani, 2018). One of the many learning models used is the Learning Cycle 7e Model(Puluhulawa et al., 2020; DN Utami & Aznam, 2020). This learning model was selected because it is student-centred, and the students are allowed to directly conduct the activities during the classroom learning process (Anshori & Syaiful, 2020; Sritresna, 2015). The following are the stages of learning cycle 7e: Figure 1. The Stages of the Learning Cycle 7e Learning models require instruments to support the learning process (Hidayatussani et al., 2020). One of the causes of poor mathematical concept understanding is the lack of instruments (Dazrullisa & Mahdi, 2020; Ulia, 2016). In this research, the learning model was assisted by GeoGebra. GeoGebra is a software that combines geometry and calculus. It can also construct points, vectors, line segments, conic sections, and form fields to construct spatial shapes, even directly determine coordinates, function integrals, and extreme points (Purwanti et al., 2016; Santos & Macedo, 2020; Suryani et al., 2020). Mathematical concepts understanding can be supported by meaningful learning, where students are required to be active and think creatively in solving problems (Aidah et al., 2020; Yunita et al., 2020). Therefore, students need a learning environment that provides opportunities to develop knowledge through experience and affects the learning process, one of which is cognitive style Elicite Engage Explore Explain Elaborate Evaluate Extend Indomath: Indonesia Mathematics Education – Volume 4 | Issue 2| 2021 153 (Mawardi et al., 2020). The cognitive style connects intelligence and personality and refers to a person's character in processing, responding, storing, thinking, and using the information in various environmental situations (Nurmala et al., 2019; Ulya, 2015). A study on the application of the Learning Cycle 7e Model has been carried out by Manurung (2018), who states that the Learning Cycle 7e Model can improve students' critical thinking skills. This learning model can also positively impact students' problem-solving abilities, motivation, and mathematical connections (Darojat, 2016; Nur'aini et al., 2017; Partini et al., 2017; Yenni 2016). Based on this data, research on the effect of the Learning Cycle 7e Modelassisted by GeoGebra on junior high school students' mathematical concepts understanding has not been carried out. Therefore, the researchers were interested in researching this issue. Besides classroom learning, the researchers suspected that other factors influence students' low conceptual understanding, one of which was cognitive style. Cognitive style is an individual's characteristic in building beliefs about the surrounding world and reacting to the received information (Febriyanti, 2015). Therefore, the teacher should pay attention to the patterns or thinking styles of each student. The patterns or thinking styles differences should become the basis for planning the classroom learning process and selecting learning media. Suryanti (2014) states that cognitive style affects students' learning outcomes. Other studies also mention that cognitive style affects mathematical problem-solving skills (Nurmutia, 2019; Wulandari & Agustika, 2018), appreciation, and achievement (Marlissa & Widjajanti, 2015; YASA et al., 2013). The statement further strengthens the notion that cognitive style will also affect students' concepts understanding. METHOD The researchers employed the quasi-experimental design with a quantitative approach. This method was selected because the researchers could not control all the external factors influencing students' concepts understanding. The research design consisted of three groups: experimental group 1, experimental group 2, and control group using a 3 x 2 factorial design. Table 1. Research Design Learning Model (Ai) Cognitive Style (Bj) Field Independent (B1) Field Dependent (B2) Learning Cycle 7e Model Model (A1) A1B1 A1B2 Learning Cycle 7e Model + GeoGebra (A2) A2B1 A2B2 Conventional Model (A3) A3B1 A3B2 The population in this research was all eighth-grade students of SMPN 8 Metro in the academic year 2020/2021, which consisted of 396 students distributed into fourteen classes. The samples were determined by cluster random sampling technique, which obtained class VIII-B (29 students) as the control class, class VIII-D (31 students) as the experimental class 1, and class VIII- J (30 students) as the experimental class 2. The total number of samples was 90 students within three classes. 154 Santi Widyawati, Fredi Ganda Putra, Bistari, and Hamdani The Effect of GeoGebra- Assisted Learning Cycle 7e Model and Cognitive Style on the Mathematical Concepts Understanding Ability The researchers collected the data using tests that had been tested for their validity and reliability. The researchers also conducted prerequisite tests on the obtained data, which consisted of the normality test using the Liliefors formula and the homogeneity test using the Barlett test. The ANOVA of two unequal cell paths and then double comparison test (advanced test) using Scheffe' method were performed using the SPSS software. RESULTS AND DISCUSSION Students' mathematical concepts understanding of the coordinate system material is presented in Table 2. Table 2. Descriptive Test of Experimental Group 1, Experimental Group 2, and Control Group Exp 1, Exp 2, control FI, FD mean Std. Deviation N Experimental 1 FD 74.31 6,741 18 FI 75.52 4,178 12 Total 74.79 5,799 30 Experimental 2 FD 78.47 8,896 18 FI 76.56 4,711 12 Total 77.71 7,465 30 Control FD 61.40 10,878 17 FI 58,17 10.008 13 Total 60.00 10,458 30 Total FD 71.58 11,404 53 FI 69.76 10,976 37 Total 70.83 11.204 90 Table 2 shows the average score differences of students' mathematical concept understanding ability between the experimental group 1 (Exp1), experimental group 2 (Exp 2), and control group. Experimental group 2 obtained a higher score than experimental group 1 and the control group. Based on the prerequisite tests, the data met the requirements (normally distributed and homogeneous). Therefore, the researchers performed the hypothesis testing using analysis of variance (ANOVA) of two unequal cell paths assisted by SPSS software version 2.4 at a significant level of 5%. Table 3. The Results of ANOVA Test Source Type III Sum of Squares df Mean Square F Sig. Corrected Model 5522,316a 5 1104,463 16,422 ,000 Intercept 435625,782 1 435625,782 6477,066 ,000 Class 5360,104 2 2680,052 39,848 ,000 cognitive_style 37,130 1 37,130 ,552 ,460 interaction 75.488 2 37,744 ,561 .573 Error 5649,559 84 67,257 Total 462734,375 90 Corrected Total 11171,875 89 a. R Squared = ,494 (Adjusted R Squared = ,464) Table 3 displays that (1) the GeoGebra-assisted Learning Cycle 7e Model influenced students' mathematical concepts understanding ability; (2) there was an effect of field-dependent and field-independent cognitive styles on students' mathematical concepts understanding ability; and Indomath: Indonesia Mathematics Education – Volume 4 | Issue 2| 2021 155 (3) there was an interaction between the GeoGebra-assisted Learning Cycle 7e Model and cognitive style (FD and FI) on students' mathematical concepts understanding ability. The marginal mean of each group is displayed in Table 4. Table 4. Marginal Mean of Each Group Learning model Marginal Mean Learning Cycle 7e Model (A1) 73.82 Learning Cycle 7e Model + GeoGebra (A2) 78.79 Conventional model (A3) 56.79 Subsequently, a multiple comparison test (post-ANOVA follow-up) was conducted using Scheffe' method. The Scheffe' method was used to determine which treatment influenced students' mathematical concept understanding ability. The following are the results of the multiple comparison test using SPSS version 2.4 software. Table 5. The Results of the Double Comparison Test between Rows (I) Exp1, Exp2, Control (J) Exp1, Ex2, Control Mean Difference (IJ) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Experimental Group 1 Experimental Group2 -2.92 2,117 ,391 -8.19 2.36 Control Group 14.79* 2,117 ,000 9.51 20.07 Experimental Group 2 Experimental Group 1 2.92 2,117 ,391 -2.36 8.19 Control Group 17.71* 2,117 ,000 12.43 22.99 Control Group Experimental Group 1 -14.79* 2,117 ,000 -20.07 -9.51 Experimental Group 2 -17.71* 2,117 ,000 -22.99 -12.43 Based on observed means. The error term is Mean Square(Error) = 67.257. *. The mean difference is significant at the .05 level. Based on the results of the multiple comparison test between rows using the Scheffe' method with a significant level of 0.5, the following conclusions were obtained: The average difference between Fi (Experimental Group 1) and FJ (Experimental Group 2) was -2.92, which means that E1 - E2 < 0 with a significant value of 0.391. Since 0.391 was higher than 0.05, it can be concluded that there was no influence difference between students who received Learning Cycle 7e Model and those who received the GeoGebra-assisted Learning Cycle 7e Model. Based on the average difference between the two groups, then E1 was lower than E2. Therefore, the GeoGebra-assisted Learning Cycle 7e Model provided better results on students' mathematical concepts understanding than the Learning Cycle 7e Model. The average difference between Fi (Experimental Group 1) and FJ (Control Group) was 14.79. It means that E1 – K > 0 with a significant value of 0.000. Since 0.000 was lower than 0.05, it can be concluded that there was an influence difference between students who received the Learning Cycle 7e Model and those who received the conventional learning model. Based on the average value difference between the two groups, E1 was higher than K. It means that the Learning 156 Santi Widyawati, Fredi Ganda Putra, Bistari, and Hamdani The Effect of GeoGebra- Assisted Learning Cycle 7e Model and Cognitive Style on the Mathematical Concepts Understanding Ability Cycle 7e Model provided better results on students' mathematical concepts understanding than the conventional learning model. These results also complement previous research with the same results (Alfin et al., 2019). The average difference between Fi (Experimental Group 2) and FJ (Experimental Group 1) was 2.92. It means that E2 – E1 > 0 with a significant value of 0.391. Since 0.391 was higher than 0.05, it can be concluded that there was no influence difference between students who received the GeoGebra -assisted Learning Cycle 7e Model and those who received the Learning Cycle 7e Model. Based on the average difference between the two groups, then E2 was higher than E1. It means that the GeoGebra-assisted Learning Cycle 7e Model provided better results on students' mathematical concepts understanding than the Learning Cycle 7e Model. The average difference between Fi (Experimental Group 2) and FJ (Control Group) was 17.71. It means that E2 – K > 0 with a significant value of 0.000. Since 0.000 was lower than 0.05, it can be concluded that there was an influence difference between students who received the GeoGebra-assisted Learning Cycle 7e Model and those who received the conventional learning model. Based on the average value difference between the two groups, E2 was higher than K. It means that the GeoGebra-assisted Learning Cycle 7e Model provided better results on students' mathematical concepts understanding than the conventional learning model. The average difference between Fi (Control Group) and FJ (Experimental Group 1) was - 14.79. It means that K – E1 < 0 with a significant value of 0.000. Since 0.000 was lower than 0.05, it can be concluded that there was an influence difference between students who received conventional learning and those who received the Learning Cycle 7e Model. Based on the average value difference between the two groups, then K was lower than E1. The Learning Cycle 7e Model gave better results on students' mathematical concepts understanding than the conventional learning model. The average difference between Fi (Control Group) and Fj (Experimental Group 2) was - 17.71. It means that K –E2 < 0 with a significant value of 0.000. Since 0.000 was lower than 0.05, it can be concluded that there was an influence difference between students who received the GeoGebra-assisted Learning Cycle 7e Model and those who received the conventional learning mode. Based on the average difference between the two groups, then K was lower than E2. It means that the GeoGebra-assisted Learning Cycle 7e Model gave better results on students' mathematical concepts understanding than the conventional learning model. CONCLUSION The results of the analysis concluded that: 1) GeoGebra-assisted Learning Cycle 7e Model had a positive influence on students' mathematical concepts understanding ability; 2) cognitive styles (field dependent and field independent) did not influence students' mathematical understanding ability; and 3) there was no interaction between the learning model group (Learning Cycle 7e Model, GeoGebra-assisted Learning Cycle 7e Model, and conventional learning model) and groups' cognitive styles on students' mathematical concepts understanding. Indomath: Indonesia Mathematics Education – Volume 4 | Issue 2| 2021 157 This research provides varied combinations of learning models and media to be applied in the classroom. Further researchers are expected to use the Learning Cycle 7e Model and GeoGebra in conducting further research by replacing variables, methods, and approaches (qualitative, Research and Development, and quantitative approaches. REFERENCES Aidah, D. H., Sobarningsih, N., & Rahayu, N. (2020). Pemahaman matematis melalui metaphorical thinking berbantuan aplikasi powtoon. Jurnal Analisa, 6(1), 91–99. Alfin, M. B., Hidayati, Y., Hadi, W. P., & Rosidi, D. I. (2019). Analisis Kemampuan Berpikir Kritis Siswa Terhadap Pembelajaran Hypothetico-Deductive Reasoning Dalam Learning Cycle 7E. JPPIPA, 4(2), 75–81. Anshori, M., & Syaiful. (2020). Pengaruh Learning Cycle 7E Disertai Mind Mapping Terhadap Kemampuan Pemecahan Masalah Matematika ditinjau Dari Adversity Quotient. Jurnal Pendidikan Matematika, 11(2), 226–241. Darmayanti Manurung, I. (2018). Pengaruh Model Learning Cycle 7E Terhadap Motivasi Mahasiswa Dalam Pembelajaran Menyimak (Listening). Jurnal Pendidikan, 1(1), 1–10. Darojat, L. (2016). Kemampuan Pemecahan Masalah Siswa Dalam Menyelesaikan Soal Open Ended Berdasarkan Aq Dengan Learning Cycle 7E. Unnes Journal of Mathematics Education Research, 5(1), 1–8. Dazrullisa, & Mahdi, C. (2020). Pengaruh Penggunaan Model Pembelajaran Disovery Leaening Terhadap Pemahaman Konsep Matematis Siswa dengan Menggunakan Geometric Sketcpad. Jurnal Numeracy, 7(1), 79–94. Fatimah, A. E. (2020). Peningkatan Self-Efficacy Siswa Melalui Model Pembelajaran Connecting Organizing Reflecting Extending (CORE). Jurnal Sintaksis, 2(04), 54–62. Fauzi, A., Sawitri, D., & Syahrir, S. (2020). Kesulitan Guru Pada Pembelajaran Matematika Di Sekolah Dasar. Jurnal Ilmiah Mandala Education, 6(1), 142–148. Febriyanti, C. (2015). Pengaruh Bentuk Umpan Balik dan Gaya Kognitif terhadap Hasil Belajara Trigonometri. Formatif: Jurnal Ilmiah Pendidikan MIPA, 3(3). Hidayatussani, H., Hadisaputra, S., & Al-Idrus, S. W. (2020). Pengaruh Model Pembelajaran Inkuiri Terbimbing Berbasis Etnokimia Terhadap Hasil Belajar Kimia Siswa Kelas Xi Di MA Al- Aziziyah Putra Kapek Gunungsari. Chemistry Education Practice, 3(1), 34. Marlissa, I., & Widjajanti, D. B. (2015). Pengaruh strategi REACT ditinjau dari gaya kognitif terhadap kemampuan pemecahan masalah, prestasi belajar dan apresiasi siswa terhadap matematika. Jurnal Riset Pendidikan Matematika, 2(2), 186–196. Mawardi, A. V., Yanti, A. W., & Arrifadah, Y. (2020). Analisis Proses Berpikir Siswa Dalam Menyelesaikan Soal HOTS ditinjau Dari Gaya Kognitif. Jurnal Review Pembelajaran Matematika, 5(1), 40–52. https://doi.org/10.15642/jrpm.2020.5.1.40-52 Nur’aini, I. L., Harahap, E., Badruzzaman, F. H., & Darmawan, D. (2017). Pembelajaran Matematika Geometri Secara Realistis Dengan GeoGebra. Matematika, 16(2), 1–6. https://doi.org/10.29313/jmtm.v16i2.3900 Nurmala, I., Yuhana, Y., & Fatah, A. (2019). Analisis Kemampuan Komunikasi Matematis Siswa Ditinjau Dari Gaya. JARME, 3(1), 17. Nurmutia, H. E. (2019). Pengaruh gaya kognitif terhadap kemampuan pemecahan masalah matematis siswa. Edumatika: Jurnal Riset Pendidikan Matematika, 2(2), 98–103. Partini, Budijanto, & Bachri, S. (2017). Penerapan Model Pembelajaran Learning Cycle 7E Untuk Meningkatkan Kemampuan Berpikir Kritis Siswa. Jurnal Pendidikan, 2(2), 268–272. Pratiwi, D. D. (2016). Pembelajaran Learning Cycle 5e berbantuan GeoGebra terhadap Kemampuan Pemahaman Konsep Matematis. Al-Jabar: Jurnal Pendidikan Matematika, 7(9), 191–202. Puluhulawa, I., Hulukati, E., & Kaku, A. (2020). Pengaruh Model Pembelajaran Learning Cycle dan Penalaran Formal terhadap Hasil Belajar Matematika. Jambura Journal of Mathematics Education, 1(1), 32–40. https://doi.org/10.34312/jmathedu.v1i1.4557 Purwanti, R. D., Pratiwi, D. D., & Rinaldi, A. (2016). Pengaruh Pembelajaran Berbantuan GeoGebra Terhadap Pemahaman Konsep Matematis ditinjau dari Gaya Kognitif. Al-Jabar: Jurnal Pendidikan Matematika, 7(1), 115–122. Rahmawati, N. K. (2019). Implementasi Teams Games Tournaments dan Number Head Together ditinjau dari Kemampuan Penalaran Matematis. Journal of Chemical Information and Modeling, 53(9), 1689–1699. 158 Santi Widyawati, Fredi Ganda Putra, Bistari, and Hamdani The Effect of GeoGebra- Assisted Learning Cycle 7e Model and Cognitive Style on the Mathematical Concepts Understanding Ability Santos, A., & Macedo, J. (2020). Contribuições do uso do software GeoGebra no estudo da derivada Contributions of using GeoGebra software in the study of the derivative Contribuciones al uso del software GeoGebra en el estudio de la derivada. Research Society and Development, 21(1), 1–9. Sekfia, R., La, J., & Samparadja, H. (2020). Pengaruh Model Pembelajaran Generatif Terhadap Kemampuan Pemahaman Konsep Matematis Siswa Kelas VII SMP Negeri 34 Konawe Selatan. Jurnal Penelitian Pendidikan Matematika, 8(1), 99–113. Sritresna, T. (2015). Meningkatkan Kemampuan Komunikasi Matematis dan Self Confident Siswa Melalui Model Pembelajaran Cycle 7E. Jurnal “Mosharafa,” 30(September 2017), 17–22. Suryani, A. I., Anwar, Hajidin, & Rofiki, I. (2020). The practicality of mathematics learning module on triangles using GeoGebra. Journal of Physics: Conference Series, 1470(1). Suryanti, N. (2014). Pengaruh Gaya Kognitif Terhadap Hasil Belajar Akuntansi Keuangan Menengah 1. Jurnal Ilmiah Akuntansi Dan Humanika, 4(1). Suryati, A., & Cahyani, R. (2018). Model Pembelajaran Cooperative Tipe Meaningful Instruction Design (MID) terhadap Peningkatan Kemampuan Pemahaman Konsep Matematika Siswa SMA. Ujmes, 03(01), 160–168. Ulia, N. (2016). Peningkatan Pemahaman Konsep Matematika Materi Bangun Datar dengan Pembelajaran Kooperatif Tipe Group Investigation Dengan Pendekatan Saintifik di SD. Jurnal Tunas Bangsa, 3(2), 55–68. Ulya, H. (2015). Hubungan Gaya Kognitif Dengan Kemampuan Pemecahan Masalah Matematika Siswa. Jurnal Konseling Gusjigang, 1(2). https://doi.org/10.24176/jkg.v1i2.410 Utami, D. N., & Aznam, N. (2020). LKPD IPA berbasis learning cycle 7E terintegrasi potensi lokal pantai Parangtritis untuk meningkatkan critical thinking siswa. Jurnal Inovasi Pendidikan IPA, 6(1), 11–25. Utami, R., & Endaryono, B. (2020). Meningkatkan Kemampuan Berpikir Kreatif Siswa Melalui Pendekatan Open-Ended. Faktor Jurnal Ilmiah Kependidikan, 7(1), 43–48. Wulandari, I. G. A. A., & Agustika, G. N. S. (2018). Pengaruh Gaya Kognitif Terhadap Hasil Belajar Matematika Pada Mahasiswa Semester IV Jurusan PGSD UPP Denpasar Universitas Pendidikan Ganesha Tahun Ajaran 2016/2017. Jurnal Ilmiah Sekolah Dasar, 2(1), 94–98. YASA, I. M. A., Sadra, I. W., & Suweken, G. (2013). Pengaruh pendidikan matematika realistik dan gaya kognitif terhadap prestasi belajar matematika siswa. Jurnal Pendidikan Dan Pembelajaran Matematika Indonesia, 2(2). Yenni, Y. (2016). Pengaruh Model Pembelajaran Learning Cycle Terhadap Kemampuan Pemahaman Dan Koneksi Matematis Siswa Smp. KALAMATIKA Jurnal Pendidikan Matematika, 1(1), 71. https://doi.org/10.22236/kalamatika.vol1no1.2016pp71-83 Yunita, P., Surahmat, & Walida, S. (2020). Kemampuan Pemahaman Konsep Matematis dan Pemecahan Masalah Matematika Melalui Model Pembelajaran Contextual Teaching and Learning Pada Materi SPLDV Kelas VIII. JP3, 15(19), 1–7.