Mathematical Problem-Solving Process Reviewed from Emotional Intelligence through Metacognition: A Literature Review
Abstract
Abstract: Mathematical Problem Solving Reviewed from Emotional Intelligence through Metacognition: A Literature Review. Metacognition is an essential part of the math problem-solving process, with emotional intelligence helping to maintain student consistency and focus. Objectives: This study aims to provide an overview of research related to the role of metacognition in mathematical problem solving, particularly from the perspective of emotional intelligence, in the period 2013 to 2024. It focuses on how emotional intelligence affects monitoring, evaluating, and controlling cognitive states and regulating students' interpersonal interactions in problem-solving. Method: This study used the PRISMA Method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) to select relevant literature. Data analysis was conducted with the help of VOSViewers and Bibliometrix R-Package software, which enabled the mapping of relationships between variables and identifying major trends in research. This study focused on articles that explored metacognition in mathematical problem-solving and the impact of emotional intelligence on this process. Findings: The results of this literature review show a 1.21% decrease in metacognition research trends from 2013 to 2024. Metacognition is connected to student variables, cognitive systems, problem-solving strategies, working memory, self-efficacy, active learning, and reflection. The integration of metacognition and emotional intelligence emphasizes their role in mathematics education. Conclusion: This study provides insights for further research on mathematics problem-solving regarding emotional intelligence through metacognition. In addition, variables such as active learning, problem-solving skills, math anxiety, student characteristics, and math awareness can be used as research references relevant to the current generation.
Keywords: metacognition, mathematics, problem-solving, emotional quotient.
DOI: http://dx.doi.org/10.23960/jpmipa/v25i1.pp399-418
Full Text:
PDFReferences
Alfiyah, N., & Siswono, T. Y. E. (2014). Identifikasi kesulitan metakognisi siswa dalam memecahkan masalah matematika [identification of students' metacognition difficulties in solving mathematics problems]. MATHEdunesa, 3(2), 131–138.
Anderson, N. J. (2008). Metacognition and good language Learners. In C. Griffith, Lessons from Good Language Learners, pp. 99-109. Cambridge, Cambridge University Press.
Anggo, M. (2011). Pemecahan masalah matematika kontekstual untuk meningkatkan kemampuan metakognisi siswa [contextualized mathematics problem solving to improve students' metacognition skills]. Edumatika, 1(2), 35–42. https://online-journal.unja.ac.id/index.php/edumatica/article/view/182
Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
Brackett, M. A., Rivers, S. E., & Salovey, P. (2011). Emotional intelligence: Implications for personal, social, academic, and workplace success. Social and Personality Psychology Compass, 5(1), 88–103. https://doi.org/10.1111/j.1751-9004.2010.00334.x
Brick, N., MacIntyre, T., & Campbell, M. (2015). Metacognitive processes in the self-regulation of performance in elite endurance runners. Psychology of Sport and Exercise, pp. 19, 1–9. https://doi.org/10.1016/j.psychsport.2015.02.003
Burnham, J. F. (2006). Scopus database: A review. Biomedical Digital Libraries, 3, 1–8. https://doi.org/10.1186/1742-5581-3-1
Cozza, B., & Oreshkina, M. (2013). Cross-cultural study of cognitive and metacognitive processes during math problem solving. School Science and Mathematics, 113(6), 275–284. https://doi.org/10.1111/ssm.12027
Damayanti, R., Sunardi, Yuliati, N., Karimah, R., & Albab, A. U. (2020). Students' metacognitive ability in solving quadrilateral problems based on adversity quotient. Journal of Physics: Conference Series, 1538(1). https://doi.org/10.1088/1742-6596/1538/1/012077
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133(March), pp. 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Doulik, P., Skoda, J., & Rican, J. (2015). Metacognitive strategies: asset to efficient learning and education. Slavonic Pedagogical Studies Journal, 4(1), 62–81. https://doi.org/10.18355/pg.2015.4.1.62-81
Drigas, A. S., & Papoutsi, C. (2018). A new layered model on emotional intelligence. Behavioral Sciences, 8(5), 1–17. https://doi.org/10.3390/bs8050045
Efklides, A. (2006). Metacognition and affect: What can metacognitive experiences tell us about the learning process? Educational Research Review, 1(1), 3–14. https://doi.org/10.1016/j.edurev.2005.11.001
Fernandez, M. L., Hadaway, N., & Wilson, J. W. (1994). Problem-solving: Managing it all. Mathematics Teacher, 87(3), 195–199.
Goleman, D., Boyatzis, R., & McKee, A. (2002). The emotional reality of teams. Journal of Organizational Excellence, 21(2), 55–65. https://doi.org/10.1002/npr.10020
Irdayani Hamid, Helmi Abdullah, K. (2020). Pengembangan tes pengetahuan metakognitif berbasis fisika dengan model two-tier multiple choice [development of physics-based metacognitive knowledge test with two-tier multiple choice model]. 110–113.
Israria, W. O., & Misu, L. (2014). Pengaruh kecerdasana emosional terhadap pemahaman matematis pada siswa kelas VIII Di SMP Negeri 5 Kendari [the effect of emotional intelligence on mathematical understanding in class VIII Students at SMP Negeri 5 Kendari]. 2(3), 145–164.
Jiang, Y., Gong, T., Saldivia, L. E., Cayton-Hodges, G., & Agard, C. (2021). Using process data to understand problem-solving strategies and processes for drag-and-drop items in a large-scale mathematics assessment. Large-Scale Assessments in Education, 9(1). https://doi.org/10.1186/s40536-021-00095-4
Kaas, R., Laeven, R., Lin, S., Tang, Q., Willmot, G., & Yang, H. (2018). IME’s Editorial Board. Insurance: Mathematics and Economics, p. 78, A1–A3. https://doi.org/10.1016/j.insmatheco.2017.08.008
Kartika, H., & Firmansyah, D. (2018). Peran kesadaran metakognitif terhadap kemampuan pemecahan masalah matematis [the role of metacognitive awareness on mathematical problem solving ability]. Theorems (The Original Research of Mathematics), 3, 1–6.
Kurniawan, P., & Wijayanti, P. (2022). Profil metakognisi siswa sma dalam memecahkan masalah matematika materi fungsi komposisi dan fungsi invers ditinjau dari kemampuan siswa [metacognition profile of senior high school students in solving mathematical problems on composition function and inverse function material based on student ability]. MATHEdunesa, 11(3), 644–656. https://doi.org/10.26740/mathedunesa.v11n3.p644-656
Livingston, J. A. (1997). Metacognition: an overview. Psychology, pp. 13, 259–266. http://gse.buffalo.edu/fas/shuell/CEP564/Metacog.htm
Mahdavi, M. (2014). An overview: Metacognition in education. International Journal of Multidisciplinary and Current Research, 2(6), 529–535. http://ijmcr.com
Masnia, Waluya, S. B., Dewi, N. R., & Sohilait, E. (2023). Proses berpikir aljabar berdasarkan metakognisi [algebraic thinking process based on metacognition]. FIBONACCI: Jurnal Pendidikan Matematika dan Matematika, 9(1), 89–94.
Mayasari, D., Utomo, D. P., & Cholily, Y. M. (2018). Analysis metakognisi siswa dalam memecahkan masalah matematika ditinjau dari tipe kepribadian hippocrates [analysis of students' metacognition in solving mathematics problems given hypocrites personality type]. Jurnal Kajian Pembelajaran Matematika, 2(1), 10. http://journal2.um.ac.id/index.php/jkpm
Mayer, J. D., & Salovey, P. (1993). The intelligence of emotional intelligence. Intelligence, 17(4), 433–442. https://doi.org/10.1016/0160-2896(93)90010-3
Mayer, J. D., Salovey, P., & Caruso, D. (2000). Models of emotional intelligence [modelos de la inteligencia emocional]. Handbook of Intelligence, 396–420.
Nkeobuna Nnah Ugoani, J. (2021). Emotional intelligence and its impact on effective human resource management. International Journal of Economics and Financial Research, 7(71), 5–13. https://doi.org/10.32861/ijefr.71.5.13
Nurjamil, D., & Saepulloh, A. (2023). Pengembangan bahan ajar matematika beroerientasi high order thinking skill (hots) matematika yang memfasilitasi kecerdasan emosional dan kecerdasan spritual [development of high order thinking skill (hots) oriented mathematics teaching materials that facilitate emotional intelligence and spiritual intelligence]. Jurnal THEOREMS (The Original Research of Mathematics), 7(2), 286. https://doi.org/10.31949/th.v7i2.4452
Ormrod, J. E. (2006). Essentials of educational psychology. Essex: Pearson Merrill Prentice Hall.
Özcan, Z. Ç. (2014). Assessment of metacognition in mathematics: which one of two methods is a better predictor of mathematics achievement? International Online Journal of Educational Sciences, 6(1), 49–57. https://doi.org/10.15345/iojes.2014.01.006
Pólya, G. (1945/1973). How to solve it. Princeton, NJ: Princeton University.
Porumb, I., & Manasia, L. (2015). A Clusterial conceptualization of metacognition in students. Educatia in Societatea Contemporana.Aplicatii, May, 33--44.
Prasetyoningrum, F. D., & Mahmudi, A. (2017). Pengaruh strategi metakognitif terhadap kemampuan pemecahan masalah matematis siswa kelas VIII di SMP Negeri 6 Yogyakarta [The effect of metacognitive strategies on mathematical problem solving skills of grade VIII students at SMP Negeri 6 Yogyakarta]. Jurnal Pendidikan Matematika, 6(4), 19–27.
Rahman, M. (2019). 21st Century skill " problem solving ": defining the concept. 2(1).
Riani, Asyril, & Untu, Z. (2022). Metakognisi siswa dalam memecahkan masalah matematika [students' metacognition in solving math problems]. Primatika, 51–60.
Rusmini, R., Harahap, F. S. W., & Guntoro, F. R. (2020). Analysis of the role of metacognition based on complex problem-solving processes against the mathematical understanding of statistics in the era of the COVID-19 pandemic. Journal of Physics: Conference Series, 1663(1). https://doi.org/10.1088/1742-6596/1663/1/012039
Safitri, P. T., Yasintasari, E., Putri, S. A., & Hasanah, U. (2020). Analisis kemampuan metakognisi siswa dalam memecahkan masalah matematika model pisa [analysis of students' metacognition ability in solving pisa model mathematics problems]. Journal of Medives : Journal of Mathematics Education IKIP Veteran Semarang, 4(1), 11. https://doi.org/10.31331/medivesveteran.v4i1.941
Santomauro, D. F., Mantilla Herrera, A. M., Shadid, J., Zheng, P., Ashbaugh, C., Pigott, D. M., Abbafati, C., Adolph, C., Amlag, J. O., Aravkin, A. Y., Bang-Jensen, B. L., Bertolacci, G. J., Bloom, S. S., Castellano, R., Castro, E., Chakrabarti, S., Chattopadhyay, J., Cogen, R. M., Collins, J. K., … Ferrari, A. J. (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet, 398(10312), 1700–1712. https://doi.org/10.1016/S0140-6736(21)02143-7
Sari, N. I., Amrullah, A., Azmi, S., & Sarjana, K. (2021). Analisis tingkat metakognisi peserta didik dalam memecahkan masalah matematika [analysis of students' metacognition level in solving mathematics problems]. Griya Journal of Mathematics Education and Application, 1(1), 36–43. https://doi.org/10.29303/griya.v1i1.10
Siagian, M. V, Saragih, S., & Sinaga, B. (2019). Development of learning materials oriented on problem-based learning model to improve students ' mathematical problem solving and metacognition ability. 14(2), 331–340.
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Measuring Scholarly Impact. https://doi.org/10.1007/978-3-319-10377-8_13
van Eck, N. J., & Waltman, L. (2023). VOSviewer Manual version 1-6-19. Leiden: Univeristeit Leiden, January, 54. http://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.1.pdf
Wellman, H. (1985). The origins of metacognition. In D. L. Forrest-Pressley, G. E. MacKinnon, and T. G. Waller, Metacognition, Cognition, and Human Performance, volume 1, Theoretical Perspectives, pp. 1–31. Academic Press, Inc
Zhou, D., Du, X., Hau, K., Luo, H., Feng, P., & Liu, J. (2019). Teacher-student relationship and mathematical problem-solving ability : mediating roles of self-efficacy and mathematical anxiety. Educational Psychology, 0(0), 1–17. https://doi.org/10.1080/01443410.2019.1696947
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Jurnal Pendidikan MIPA
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The copyright is reserved to The Jurnal Pendidikan MIPA that is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.