Main Article Content

Abstract

Online learning during the Covid-19 pandemic requires lecturers to provide a stimulus that can increase student learning independence. However, not all lecturers and students are ready to carry out online learning, as a result, the anxiety factor for students is getting higher. In some studies, it is said that anxiety has a negative correlation with student self-concept. This study aims to find out how the mathematics self-concept (MSC), mathematics anxiety (MA), and mathematics learning independence (MSRL) of students are during the Covid-19 pandemic. This research is quantitative descriptive. The population of this study was active students in the Mathematics and Mathematics Education study program. Data were collected using a cross-sectional survey technique with cluster sampling. The data analysis technique used descriptive statistical analysis, Spearman correlation analysis, and ordinal regression analysis. The results showed that the average student had a positive MSC, MA, and moderate MSRL. Students with negative MSC had a significant tendency to have a high MSRL than students with positive MSC. The increasing probability of students with negative MSC having a high MSRL is 0.5110 times better than students with positive MSC. MSC and MA have an effect of 7.9% on changes in the student's MSRL variable. Thus, during the Covid-19 pandemic mathematics self-concept directly affects changes in student learning independence, but not with math anxiety.


DOI: https://doi.org/10.22342/jpm.15.2.13200.103-114

Keywords

Mathematics Self-Concept Anxiety Self-Regulated Learning

Article Details

How to Cite
Delima, N., & Cahyawati, D. (2021). Students’ Mathematics Self-Concept, Mathematics Anxiety and Mathematics Self-Regulated Learning during the Covid-19 Pandemic . Jurnal Pendidikan Matematika, 15(2), 103–114. Retrieved from https://jpm.ejournal.unsri.ac.id/index.php/jpm/article/view/230

References

  1. Adegoke, B. A. (2015). The big-fish-little-pond effect on mathematics self concept of junior school students in academically selective and non-selective schools. Journal of Studies in Education, 5(2), 91. https://doi.org/10.5296/jse.v5i2.7121.
  2. Al Mutawah, M. A., Thomas, R., & Khine, M. S. (2017). Investigation into self-regulation, engagment in learning mathematics and science and achievement among bahrain secondary school students. International Electronic Journal of Mathematics Education, 12(3), 633–653.
  3. Baloğlu, M., & Balgalmiş, E. (2010). The adaptation of the mathematics anxiety rating scale-elementary form into Turkish, language validity, and preliminary psychometric investigation. Educational Sciences: Theory & Practice, 10(1), 101–110.
  4. Cakir, R., Korkmaz, O., Bacanak, A., & Arslan, O. (2016). An exploration of the relationship between students’ preferences for formative feedback and self-regulated learning skills. Malaysian Online Journal of Educational, 4(4), 14–30.
  5. Chaterine, R. N. (2020). Students learn from home, KPAI: children stress given many tasks [in Bahasa]. DetikNews. Retrieved from https://news.detik.com/berita/d-4944071/siswa-belajar-dari-rumah-kpai-anak-anak-stres-dikasih-banyak-tugas
  6. Cohen, M. T. (2012). The importance of self-regulation for college student learning. College Student Journal, 46(4), 892–902. https://doi.org/10.1108/09513570810842368
  7. Darnah. (2011). Ordinal logistic regression to analyze the factors that influence adolescent sexual behavior [in Bahasa]. Jurnal Eksponensial, 2(1), 47–52.
  8. Delima, N. (2019). Comprehensive Mathematics Instruction (CMI) model to improve mathematical thinking and mathematics self-concept ability of high school students [in Bahasa]. Skripsi. Bandung: Universitas Pendidikan Indonesia.
  9. Delima, N., Rahmah, M. A., & Akbar, A. (2018). The analysis of students’ mathematical thinking based on their mathematics self-concept. Journal of Physics: Conference Series, 1108(1). https://doi.org/10.1088/1742-6596/1108/1/012104
  10. Dina, D., & Nugraheni, A. R. E. (2017). Profile of chemistry education students’ independence and interest in mathematics and sciences’ insight and knowledge course through e-learning. Jurnal Inovasi Pendidikan Kimia, 11(2), 1921–1931. https://journal.unnes.ac.id/artikel_nju/JIPK/10608
  11. Githua, B. N., & Mwangi, J. G. (2003). Students’ mathematics self-concept and motivation to learn mathematics: Relationship and gender differences among Kenya’s secondary-school students in Nairobi and Rift Valley provinces. International Journal of Educational Development, 23(5), 487–499. https://doi.org/10.1016/S0738-0593(03)00025-7
  12. Hansford, C. (1994). The relationships between self-concept, perceived locus of control, self-regulated learning, and academic achievement in college students. Texas Tech University.
  13. Hastini, L. Y., Fahmi, R., & Lukito, H. (2020). Can learning using technology improve human literacy in generation Z in Indonesia? [in Bahasa]. Jurnal Manajemen Informatika (JAMIKA), 10(1), 12–28. https://doi.org/10.34010/jamika.v10i1.2678
  14. Howse, R. B., Lange, G., Farran, D. C., & Boyles, C. D. (2003). Motivation and self-regulation as predictors of achievement in economically disadvantaged young children. The Journal of Experimental Education, 71(2), 151–174. https://www.tandfonline.com/doi/abs/10.1080/00220970309602061
  15. Isiksal, M., Curran, J. M., Koc, Y., & Askun, C. S. (2009). Mathematics anxiety and mathematical self-concept: Considerations in preparing elementary-school teachers. Social Behavior and Personality, 37(5), 631–644. https://doi.org/10.2224/sbp.2009.37.5.631
  16. Jado, M. A. (2015). The effect of using learning journals on developing self- regulated learning and reflective thinking among pre-service teachers in Jordan. Journal of Education and Practice, 6(5), 89–104.
  17. Kesici, Ş., Balo, M., & Deniz, M. E. (2011). Self-regulated learning strategies in relation with statistics anxiety. Learning and Individual Differences, 21, 472–477. https://doi.org/10.1016/j.lindif.2011.02.006
  18. Kvedere, L. (2014). Mathematics self-efficacy, self-concept and anxiety among 9 th grade students in latvia. Procedia - Social and Behavioral Sciences, 116, 2687–2690. https://doi.org/10.1016/j.sbspro.2014.01.636
  19. Latifah, E. (2015). Self regulated learning strategy and learning achievement: Meta analysis study [in Bahasa]. Jurnal Psikologi, 37(1), 110 – 129–129. https://doi.org/10.22146/jpsi.7696
  20. Loviana, S., & Baskara, W. N. (2020). The impact of the Covid-19 pandemic on the readiness of IAIN Metro Lampung on tadris mathematics learning [in Bahasa]. Epsilon, 1(2), 61–70.
  21. Maksum, A., & Lestari, I. (2020). Analysis of student learning independence profile in higher education [in Bahasa]. Parameter: Jurnal Pendidikan Universitas Negeri Jakarta, 32(1), 75–86. https://doi.org/10.21009/parameter.321.05
  22. Martinez-Pons, M. (2002). A social cognitive view of parental influences on student academic self-regulation. Theory into Practice, 41(2), 126–131.
  23. Meric, O., & Ilhan, A. (2016). Does 12-week latin dance training affect the self-confidence of the university students?. Journal of Education and Learning, 5(4), 159. https://doi.org/10.5539/jel.v5n4p159
  24. Morgan, H. (2020). Best practices for implementing remote learning during a pandemic. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 93(3), 135–141. https://doi.org/10.1080/00098655.2020.1751480
  25. Morony, S., Kleitman, S., Lee, Y. P., & Stankov, L. (2013). Predicting achievement: confidence vs self-efficacy, anxiety, and self-concept in confucian and european countries. International Journal of Educational Research, 58, 79–96. https://doi.org/10.1016/j.ijer.2012.11.002
  26. Nagy, G., Watt, H. M. G., Eccles, J. S., Trautwein, U., Lüdtke, O., & Baumert, J. (2010). The development of students’ mathematics self-concept in relation to gender: Different countries, different trajectories?. Journal of Research on Adolescence, 20(2), 482–506. https://doi.org/10.1111/j.1532-7795.2010.00644.x
  27. OECD. (2013). Ready to learn: students’ engagement, drive and self-beliefs-volume III. Paris: OECD. https://doi.org/10.1787/888932963844
  28. Pakpahan, R., & Fitriani, Y. (2020). Analysis of the use of information technology in distance learning in the middle of the Corona Covid-19 virus pandemic [in Bahasa]. JISAMAR (Journal of Information System, Applied, Management, Accounting and Researh), 4(2), 30–36.
  29. Prayekti. (2015). Effect of self-regulated learning and motivation to achieve against teacher professional capability for student S1 PGSD of science field compared with regular student S1 PGSD at UPBJJ Serang. Journal of Education and Practice, 6(36), 47–55.
  30. Purdie, N., Hattie, J., & Douglas, G. (1996). Student conceptions of learning and their use of self-regulated learning strategies : A cross-cultural comparison. Journal of Educational Psychology, 88(1), 87–100.
  31. Richardson, F. C., & Suinn, R. M. (1972). The mathematics anxiety rating scale: Psychometric data. Journal of Counseling PsycMogv Mi, 18(6), 651–655.
  32. Sadikin, A., & Hamidah, A. (2020). Online learning in the Covid-19 pandemic [in Bahasa]. BIODIK: Jurnal Ilmiah Pendidikan Biologi, 6(2), 214–224. https://doi.org/10.17509/t.v6i2.20887
  33. Shukla, T., Dosaya, D., Nirban, V. S., & Vavilala, M. P. (2020). Factors extraction of effective teaching-learning in online and conventional classrooms. International Journal of Information and Education Technology, 10(6), 422–427. https://doi.org/10.18178/ijiet.2020.10.6.1401
  34. Sudiana, R., Fatah, A., & Khaerunnisa, E. (2017). Independent student learning through virtual class-based learning [in Bahasa]. Jurnal Penelitian Dan Pembelajaran Matematika, 10(1). https://doi.org/10.30870/jppm.v10i1.1292
  35. Suinn, R. I. M., & Winston, E. H. (2003). The mathematics anxiety rating scale, a brief version: Psychometric data. Psychological Reports, 92, 167–173.
  36. Vusvitasari, R., Nugroho, S., & Akbar, S. (2016). Study of the Pearson Correlation Coefficient ( ρ ), Spearman- [in Bahasa]. Journal Statistika, 41–54.
  37. Wolters, C. A., & Hussain, M. (2015). Investigating grit and its relations with college students’ self-regulated learning and academic achievement. Metacognition and Learning, 10(3), 293–311. https://doi.org/10.1007/s11409-014-9128-9
  38. Wolters, C., & Rosenthal, H. (2000). The relation between students’ motivational beliefs and their use of motivational regulation strategies. International Journal of Educational Research, 33(7–8), 801–820. https://doi.org/https://doi.org/10.1016/S0883-0355(00)00051-3
  39. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
  40. Zimmerman, B. J., & Martinez-Pons, M. (1988). Construct Validation of a Strategy Model of Student Self-Regulated Learning. Journal of Educational Psychology, 80(3), 284–290. https://doi.org/10.1037/0022-0663.80.3.284