Mathematics Identity of Prospective Mathematics Teachers: Content Analysis of Open-Ended Survey Questions

Yıl 2023, Cilt: 10 Sayı: 4, 181 - 201, 01.07.2023

Annisa Dwi Kurniawati Dwi Junıatı Abadi Abadi

https://doi.org/10.17275/per.23.66.10.4

Cited By: 1

Öz

Many problems faced by mathematics learners both at the school and college levels have occurred so far. Mathematics education students involved in mathematics daily also face various problems, be it problems related to cognitive and affective abilities. Problems such as the emergence of mathematical anxiety, negative self-perception of mathematics, lack of mathematical competence, and many other problems have become the recent focus in mathematics education research. So, how do mathematics education students, especially prospective mathematics teachers, view themselves as related to mathematics? What is their mathematical identity? This study aims to determine the mathematics identity possessed by prospective mathematics teachers. To find out the mathematics identity of prospective mathematics teachers, a descriptive design utilizing a survey with five open-ended questions was asked. Demographic data were analyzed using descriptive frequencies, while the five open-ended questions were analyzed using summative content analysis to analyze free-text responses from 225 prospective mathematics teachers. Free-text responses contain answers to five questions in each component of the mathematical identity obtained from disseminating questions through google forms. We obtained the results that prospective mathematics teachers generally have a positive mathematical identity, but some components need improvement. However, it was also found that the results were quite surprising concerning the mathematical identity of the prospective mathematics teacher. A complete explanation will be discussed in this article.

Anahtar Kelimeler

mathematics identity, prospective mathematics teacher, open-ended survey, content analysis

Kaynakça

• Aiken, L. R. (1980). Content validity and reliability of single items or questionnaires. Educational and Psychological Measurement, 40(4), 955–959.
• Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45(1), 131–142.
• Anjariyah, D., Juniati, D., Yuli, T., Siswono, E., & Siswono, T. Y. E. (2018). Critical thinking skill of high-performance mathematics teacher in solving mathematical problem. Proceedings of Mathematics, Informatics, Science, and Education International Conference (MISEIC), 157, 138–141. https://doi.org/10.2991/miseic-18.2018.34
• Aronson, J., Lustina, M. J., Good, C., Keough, K., Steele, C. M., & Brown, J. (1999). When white men can’t do math: Necessary and sufficient factors in stereotype threat. Journal of Experimental Social Psychology, 35(1), 29–46.
• Attard, C. (2014). “ I don’t like it, I don’t love it, but I do it and I don’t mind”: Introducing a framework for engagement with mathematics. Curriculum Perspectives, 1–14.
• Berkowitz, M., Edelsbrunner, P., & Stern, E. (2022). The relation between working memory and mathematics performance among students in math-intensive STEM programs. Intelligence, 92, 101649.
• Boaler, J., & Greeno, J. G. (2000). Identity, agency, and knowing. Multiple Perspectives on Mathematics Teaching and Learning, 1, 171.
• Büyüköztürk, Ş., Kılıç-Çakmak, E., Akgün, Ö., Karadeniz, Ş., & Demirel, F. (2011). Bilimsel araştırma yöntemleri. Pegem A yayıncılık.
• Chipman, S. f., Krantz, D. h., & Silver, R. (1992). Mathematics anxiety and science careers among able college women. Psychological Science, 3(5), 292–296. https://doi.org/10.1111/j.1467-9280.1992.tb00675.x
• Chouinard, R., Karsenti, T., & Roy, N. (2007). Relations among competence beliefs, utility value, achievement goals, and effort in mathematics. British Journal of Educational Psychology, 77(3), 501–517. https://doi.org/10.1348/000709906X133589
• Cohen, L., Manion, L., & Morrison, K. (2000). Research methods in education (5" ed.) London. England: Routledge Falmer.
• Cribbs, J., Cass, C., Hazari, Z., Sadler, P. M., & Sonnert, G. (2016). Mathematics identity and student persistence in engineering. The International Journal of Engineering Education, 32(1), 163–171.
• Cribbs, J., Hazari, Z., Sonnert, G., & Sadler, P. M. (2015). Establishing an explanatory model for mathematics identity. Child Development, 86(4), 1048–1062.
• Cribbs, J., Huang, X., Piatek-Jimenez, K., & Piatek‐Jimenez, K. (2021). Relations of mathematics mindset, mathematics anxiety, mathematics identity, and mathematics self‐efficacy to STEM career choice: A structural equation modeling approach. School Science and Mathematics, 121(5), 275–287. https://doi.org/10.1111/ssm.12470
• Cribbs, Jennifer D., Hazari, Z., Sonnert, G., & Sadler, P. M. (2015). Establishing an explanatory model for mathematics identity. Child Development, 86(4), 1048–1062. https://doi.org/10.1111/cdev.12363
• Cribbs, Jennifer Dawn. (2012). The development of freshman college calculus students’ mathematics identity and how it predicts students’ career choice. Clemson University.
• Crossley, S., Ocumpaugh, J., Labrum, M., Bradfield, F., Dascalu, M., & Baker, R. S. (2018). Modeling math identity and math success through sentiment analysis and linguistic features. Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018, 11–20.
• Darragh, L. (2015). Recognising ‘good at mathematics’: Using a performative lens for identity. Mathematics Education Research Journal, 27(1), 83–102.
• Darragh, L. (2016). Identity research in mathematics education. Educational Studies in Mathematics, 93(1), 19–33. https://doi.org/10.1007/s10649-016-9696-5
• Doyle, L., McCabe, C., Keogh, B., Brady, A., & McCann, M. (2020). An overview of the qualitative descriptive design within nursing research. Journal of Research in Nursing, 25(5), 443–455.
• Du, C., Qin, K., Wang, Y., & Xin, T. (2021). Mathematics interest, anxiety, self-efficacy and achievement: Examining reciprocal relations. Learning and Individual Differences, 91, 102060. https://doi.org/10.1016/J.LINDIF.2021.102060
• Edmonds, W. A., & Kennedy, T. D. (2016). An applied guide to research designs: Quantitative, qualitative, and mixed methods. Sage Publications.
• Galloway, A. (2005). Non-Probability Sampling. In Encyclopedia of Social Measurement (pp. 859–864). Elsevier. https://doi.org/10.1016/B0-12-369398-5/00382-0
• Gardee, A. (2019). Social relationships between teachers and learners, learners’ mathematical identities and equity. African Journal of Research in Mathematics, Science and Technology Education, 23(2), 233–243.
• Gilbert, M. C. (2016). Relating aspects of motivation to facets of mathematical competence varying in cognitive demand. The Journal of Educational Research, 109(6), 647–657. https://doi.org/10.1080/00220671.2015.1020912
• Giovanni, P., & Sangcap, A. (2010). Mathematics-related beliefs of Filipino college students: Factors affecting mathematics and problem solving performance. Procedia Social and Behavioral Sciences, 8, 465–475.
• Graven, M., & Heyd-Metzuyanim, E. (2019). Mathematics identity research: the state of the art and future directions: Review and introduction to ZDM Special Issue on Identity in Mathematics Education. ZDM, 51(3), 361–377.
• Grootenboer, P. (2020). Mathematics education: Building mathematical identities. AIP Conference Proceedings, 2215(April), 060006. https://doi.org/10.1063/5.0000581
• Grootenboer, P., & Marshman, M. (2015). Mathematics, affect and learning. Springer.
• Gudyanga, A., Mandizvidza, V., & Gudyanga, E. (2016). Participation of rural Zimbabwean female students in mathematics: The influence of perception. Cogent Education, 3(1), 1156836. https://doi.org/10.1080/2331186X.2016.1156836
• Gweshe, L. C., & Brodie, K. (2019). High school learners’ mathematical identities. African Journal of Research in Mathematics, Science and Technology Education, 23(2), 254–262.
• Hannula, M. S., Di Martino, P., Pantziara, M., Zhang, Q., Morselli, F., Heyd-Metzuyanim, E., Lutovac, S., Kaasila, R., Middleton, J. A., Jansen, A., & Goldin, G. A. (2016). Attitudes, Beliefs, Motivation, and Identity in Mathematics Education. In Attitudes, beliefs, motivation, and identity in mathematics education: An overview of the field and future directions (pp. 1–35). https://doi.org/10.1007/978-3-319-32811-9_1
• Haser, Ç., & Doğan, O. (2012). Pre-service mathematics teachers’ belief systems. Journal of Education for Teaching, 38(3), 261–274. https://doi.org/10.1080/02607476.2012.668336
• Herrmann, K. J. (2013). The impact of cooperative learning on student engagement: Results from an intervention. Active Learning in Higher Education, 14(3), 175–187.
• Hibberts, M., Burke Johnson, R., & Hudson, K. (2012). Common survey sampling techniques. Handbook of Survey Methodology for the Social Sciences, 53–74.
• Hildebrand, L., Posid, T., Moss-Racusin, C. A., Hymes, L., & Cordes, S. (2022). Does my daughter like math? Relations between parent and child math attitudes and beliefs. Developmental Science, e13243. https://doi.org/10.1111/DESC.13243
• Hodaňová, J., & Nocar, D. (2016). Mathematics importance in our life. INTED2016 Proceedings, 3086–3092.
• Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288.
• Hurst, M., & Cordes, S. (2017). When being good at math is not enough: How students’ beliefs about the nature of mathematics impact decisions to pursue optional math education. Understanding Emotions in Mathematical Thinking and Learning, 221–241. https://doi.org/10.1016/B978-0-12-802218-4.00008-X
• Juniati, D., & Budayasa, I. K. (2020). The mathematics anxiety: Do prospective math teachers also experience it? Journal of Physics: Conference Series, 1663(1), 012032. https://doi.org/10.1088/1742-6596/1663/1/012032
• Juniati, Dwi, & Budayasa, I. K. (2020). Working memory capacity and mathematics anxiety of mathematics undergraduate students and its effect on mathematics achievement. Journal for the Education of Gifted Young Scientists, 8(1), 271–290.
• Juniati, Dwi, & Budayasa, I. K. (2021). Field-based tasks with technology to reduce mathematics anxiety and improve performance. World Transactions on Engineering and Technology Education, 19(1), 58–64.
• Karimi, A., & Venkatesan, S. (2017). Mathematics anxiety, mathematics performance and academic hardiness in high school students. Kamla Raj Enterprises, 1(1), 33–37. https://doi.org/10.1080/09751122.2009.11889973
• Kim, H., Sefcik, J. S., & Bradway, C. (2017). Characteristics of qualitative descriptive studies: A systematic review. Research in Nursing & Health, 40(1), 23–42.
• Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134. https://doi.org/10.1037/0022-3514.77.6.1121
• Kurniawati, A. D., Juniati, D., & Abadi. (2022a). Development of the Pre-Service Teachers’ Mathematics Identity Instrument (P-STMI). Acta Scientiae, 24(6), 338–369.
• Kurniawati, A. D., Juniati, D., & Abadi. (2022b). The impact of beliefs on motivation and mathematical problem-solving in prospective teacher with different personality types. AIP Conference Proceedings, 2577(July). https://doi.org/10.1063/5.0096026
• Kurniawati, A. D., & Noviani, J. (2022). Motivational profiles of prospective mathematics teachers based on different types of personalities. Beta: Jurnal Tadris Matematika, 15(1), 20–36. https://doi.org/10.20414/betajtm.v15i1.502
• Langer-Osuna, J. M., & Esmonde, I. (2017). Identity in research on mathematics education. Compendium for Research in Mathematics Education, 637–648.
• Lazarides, R., Gaspard, H., & Dicke, A. L. (2019). Dynamics of classroom motivation: Teacher enthusiasm and the development of math interest and teacher support. Learning and Instruction, 60, 126–137. https://doi.org/10.1016/J.LEARNINSTRUC.2018.01.012
• Lester, Frank K. (2007). Second handbook of research on mathematics teaching and learning: A project of the National Council of Teachers of Mathematics. IAP.
• Luczak, R. (2021). Adolescents’ mathematics identities in a math circle. Mathematics Education Across Cultures: Proceedings of the 42nd Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, 1450–1451.
• Lutovac, S., & Kaasila, R. (2018). Future directions in research on mathematics-related teacher identity. International Journal of Science and Mathematics Education, 16(4), 759–776.
• Mao, Y. (2017). Intercoder Reliability Techniques: Holsti Method. In The SAGE Encyclopedia of Communication Research Methods (pp. 741–743). SAGE Publications, Inc. https://doi.org/10.4135/9781483381411.n258
• Martin, D. B. (2000). Mathematics success and failure among African-American youth: The roles of sociohistorical context, community forces, school influence, and individual agency. Routledge.
• Martinot, D., & Désert, M. (2007). Awareness of a gender stereotype, personal beliefs and self-perceptions regarding math ability: when boys do not surpass girls. Social Psychology of Education 2007 10:4, 10(4), 455–471. https://doi.org/10.1007/S11218-007-9028-9
• McGee, E. O. (2015). Robust and fragile mathematical identities: A framework for exploring racialized experiences and high achievement among black college students. Journal for Research in Mathematics Education, 46(5), 599–625. https://doi.org/10.5951/jresematheduc.46.5.0599
• Meltzer, L., Reddy, R., Pollica, L. S., Roditi, B., Sayer, J., & Theokas, C. (2004). Positive and negative self‐perceptions: Is there a cyclical relationship between teachers’ and students’ perceptions of effort, strategy use, and academic performance? Learning Disabilities Research & Practice, 19(1), 33–44.
• Miele, D. B., Browman, A. S., Shen, C., Vasilyeva, M., & Tyumeneva, Y. A. (2022). Domain-general and math-specific self-perceptions of perseverance as predictors of behavioral math persistence. The Journal of Experimental Education, 90(3), 593–614. https://doi.org/10.1080/00220973.2020.1799312
• Mielicki, M. K., Schiller, L. K., Fitzsimmons, C. J., Scheibe, D., & Thompson, C. A. (2022). Perceptions of ease and difficulty, but not growth mindset, relate to specific math attitudes. British Journal of Educational Psychology, 92(2), 707–729. https://doi.org/10.1111/BJEP.12472
• Mtetwa, D., & Garofalo, J. (1989). Beliefs about mathematics: An overlooked aspect of student difficulties. Academic Therapy, 24(5), 611–618.
• Muhtarom, Juniati, D., Yuli, T., & Siswono, E. (2019). Examining prospective teacher s ’ belief and pedagogical content knowledge towards teaching practice in mathematics class : a case study. Journal on Mathematics Education, 10(2), 185–202.
• Muhtarom, M., Juniati, D., & Siswono, T. Y. E. (2017). Exploring beliefs in a problem-solving process of prospective teachers’ with high mathematical ability. WIETE, 19(2), 130–136.
• National Council of Teachers of Mathematics (NCTM). (2014). Principles to actions: Ensuring mathematical success for all. VA: NCTM.
• Ní Fhloinn, E., Fitzmaurice, O., Mac an Bhaird, C., & O’Sullivan, C. (2014). Student perception of the impact of mathematics support in higher education. International Journal of Mathematical Education in Science and Technology, 45(7), 953–967. https://doi.org/10.1080/0020739X.2014.892161
• O’Reilly, J., & Barry, B. (2023). The effect of the use of computer-aided design (CAD) and a 3D printer on the child’s competence in mathematics. Irish Educational Studies, 42(2), 233–256. https://doi.org/10.1080/03323315.2021.1964561
• Philipp, R. A. (2007). Mathematics teachers’ beliefs and affect. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 257–315). NCTM.
• Prabhu, S. (2022). Changing Students’ Perception of Learning Mathematics. PRIMUS, 32(4), 503–516. https://doi.org/10.1080/10511970.2020.1844826
• Purwaningtyas, B. A., Sary, R. M., & Artharina, F. P. (2020). Analysis of misconceptions in fpb and kpk material for students. International Journal of Elementary Education, 4(4), 596–604.
• Radovic, D., Black, L., Salas, C. E., & Williams, J. (2017). Being a girl mathematician: Diversity of positive mathematical identities in a secondary classroom. Journal for Research in Mathematics Education, 48(4), 434–464.
• Radovic, D., Black, L., Williams, J., & Salas, C. E. (2018). Towards conceptual coherence in the research on mathematics learner identity: a systematic review of the literature. Educational Studies in Mathematics, 99(1), 21–42. https://doi.org/10.1007/s10649-018-9819-2
• Rahimi, S., & Vallerand, R. J. (2021). The role of passion and emotions in academic procrastination during a pandemic (COVID-19). Personality and Individual Differences, 179, 110852. https://doi.org/10.1016/J.PAID.2021.110852
• Retnowati, E., Ayres, P., & Sweller, J. (2017). Can collaborative learning improve the effectiveness of worked examples in learning mathematics? Journal of Educational Psychology, 109(5), 666.
• Ridlon, C. L. (2009). Learning mathematics via a problem-centered approach: A two-year study. Mathematical Thinking and Learning, 11(4), 188–225.
• Rowley, J. (2014). Designing and using research questionnaires. Management Research Review, 37(3), 308–330.
• Ruiz-Alfonso, Z., & León, J. (2016). The role of passion in education: A systematic review. Educational Research Review, 19, 173–188. https://doi.org/10.1016/J.EDUREV.2016.09.001
• Sandelowski, M. (2000). Whatever happened to qualitative description? Research in Nursing & Health, 23(4), 334–340.
• Seixas, B. V, Smith, N., & Mitton, C. (2018). The qualitative descriptive approach in international comparative studies: using online qualitative surveys. International Journal of Health Policy and Management, 7(9), 778.
• Siedlecki, S. L. (2020). Understanding descriptive research designs and methods. Clinical Nurse Specialist, 34(1), 8–12.
• Siedlecki, S. L., Butler, R. S., & Burchill, C. N. (2015). Survey design research: A tool for answering nursing research questions. Clinical Nurse Specialist, 29(4), E1–E8.
• Solomon, Y. (2009). Mathematical literacy: Developing identities of inclusion. Routledge.
• Stephanou, G. (2014). Feelings towards child–teacher relationships, and emotions about the teacher in kindergarten: effects on learning motivation, competence beliefs and performance in mathematics and literacy. European Early Childhood Education Research Journal, 22(4), 457–477. https://doi.org/10.1080/1350293X.2014.947830
• Stylianides, A. J., & Stylianides, G. J. (2007). Learning mathematics with understanding: A critical consideration of the learning principle in the principles and standards for school mathematics. The Mathematics Enthusiast, 4(1), 103–114.
• Syyeda, F. B. (2021). Mathematical identity: an investigation into the learning journeys of adult learners. University of Leicester.
• Thomaes, S., Tjaarda, I. C., Brummelman, E., & Sedikides, C. (2020). Effort self-talk benefits the mathematics performance of children with negative competence beliefs. Child Development, 91(6), 2211–2220. https://doi.org/10.1111/CDEV.13347
• Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & Health Sciences, 15(3), 398–405.
• Zhang, D., & Wang, C. (2020). The relationship between mathematics interest and mathematics achievement: mediating roles of self-efficacy and mathematics anxiety. International Journal of Educational Research, 104, 101648. https://doi.org/10.1016/J.IJER.2020.101648
• Zhao, N., Valcke, M., Desoete, A., Zhu, C., Sang, G., & Verhaeghe, J. (2014). A Holistic Model to Infer Mathematics Performance: The Interrelated Impact of Student, Family and School Context Variables. Scandinavian Journal of Educational Research, 58(1), 1–20. https://doi.org/10.1080/00313831.2012.696210