Article Sidebar

Download
PDF
Statistic
Read Counter : 718 Download : 455

Downloads

Download data is not yet available.

Main Article Content

Abstract

Realistic Mathematics Education (RME) is a re-emerging teaching and learning pedagogy approach that has gained a lot of momentum since 2016. Prior publications concentrated mostly on curriculum design and student achievement, while little attention was devoted to understanding teachers’ perceptions toward RME. Thus, the purpose of this study was to investigate the effects of factors that influence teachers' perceptions to adopt RME in the long term. Ten hypotheses were proposed and tested employing the Generalized Structured Component Analysis (GSCA) technique. 226 primary school teachers from various regions were recruited to answer the questionnaires via Google Form. The experimental results validated six out of ten expected relationships between the factors in the extended self-determination theory model. That is, perceived competence affected confirmation, confirmation influenced both intrinsic motivation and satisfaction, intrinsic motivation influenced satisfaction, and satisfaction and parental involvement both were considered reliable predictors of realistic math education continuance intention. The remaining hypotheses were not validated, that is, autonomy, relatedness and competence were not found significant on intrinsic motivation, and intrinsic motivation did not influence RME continuance intention. Overall, the model explains 57.9% the amount of variance in the data. Administrators and policymakers are recommended to intervene on validated relationships to increase teachers' retention and long-term commitment to RME, whereas unsupported assumptions must be reexamined in the future.

Keywords

Confirmation Parental Involvement Realistic Mathematics Education Satisfaction Self-Determination Theory

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Nguyen, G. T. C., & Pham, C. T. H. (2023). An empirical study of factors influencing primary school teachers’ long-term commitment to Realistic Mathematics Education. Journal on Mathematics Education, 14(1), 1–18. https://doi.org/10.22342/jme.v14i1.pp1-18
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Adams, N., Little, T. D., & Ryan, R. M. (2017). Self-Determination Theory. In Development of Self-Determination through the Life-Course (pp. 47-54). Springer.
  2. Adulyasas, L. (2017). Measuring and Factors Influencing Mathematics Teachers’ Technological Pedagogical and Content Knowledge (Tpack) in Three Southernmost Provinces, Thailand. The 4th International Conference on Research, Implementation, and Education of Mathematics and Science, https://doi.org/10.1063/1.4995159
  3. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational behavior and human decision processes, 50(2), 179-211.
  4. Alam, A. (2022). Employing Adaptive Learning and Intelligent Tutoring Robots for Virtual Classrooms and Smart Campuses: Reforming Education in the Age of Artificial Intelligence. In Advanced Computing and Intelligent Technologies (pp. 395-406). Springer. https://doi.org/10.1007/978-981-19-2980-9_32
  5. Alim, J., Fauzan, A., Arnawa, I., Sari, I., & Hermita, N. (2020). Development of Learning Flow on Two-Dimentional Figure Based Realistic Mathematics Education. Univers. J. Educ. Res., 8(8), 3579-3584. https://doi.org/0.13189/ujer.2020.080834
  6. Apsari, R. A., Putri, R. I. I., Abels, M., & Prayitno, S. (2020). Geometry Representation to Develop Algebraic Thinking: A Recommendation for a Pattern Investigation in Pre-Algebra Class. Journal on Mathematics Education, 11(1), 45-58. https://doi.org/10.22342/jme.11.1.9535.45-58
  7. Baxter, G., & Toe, D. (2021). ‘Parents Don’t Need to Come to School to Be Engaged:’Teachers Use of Social Media for Family Engagement. Educational Action Research, 1-23. https://doi.org/10.1080/09650792.2021.1930087
  8. Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS quarterly, 351-370. https://doi.org/10.2307/3250921
  9. Carmichael, C., & MacDonald, A. (2016). Arental Influences on Primary School Children's Mathematics Achievement: Insights from the Longitudinal Study of Australian Children. Education 3-13, 44(2), 197-211. https://doi.org/10.1080/03004279.2014.939684
  10. Chairil Hikayat, S., Hairun, Y., & Suharna, H. (2020). Design of Realistic Mathematics Education Approach to Improve Critical Thinking Skills. Universal Journal of Educational Research, 8(6), 2232-2244. https://doi.org/10.13189/ujer.2020.080606
  11. Cushman, P. (2005). Let's Hear It from the Males: Issues Facing Male Primary School Teachers. Teaching and teacher education, 21(3), 227-240.
  12. Daneji, A. A., Ayub, A. F. M., & Khambari, M. N. M. (2019). The Effects of Perceived Usefulness, Confirmation and Satisfaction on Continuance Intention in Using Massive Open Online Course. Knowledge Management & E-Learning, 11(2), 201-214. https://doi.org/10.34105/j.kmel.2019.11.010
  13. Do, T.-T., Hoang, K. C., Do, T., Trinh, T. P. T., Nguyen, D. N., Tran, T., Le, T. T. B. T., Nguyen, T. C., & Nguyen, T.-T. (2021). Factors Influencing Teachers' Intentions to Use Realistic Mathematics Education in Vietnam: An Extension of the Theory of Planned Behavior. Journal on Mathematics Education, 12(2), 331-348. https://doi.org/10.22342/jme.12.2.14094.331-348
  14. Duyen, N. T. H., & Loc, N. P. (2022). Developing Primary Students' Understanding of Mathematics through Mathematization: A Case of Teaching the Multiplication of Two Natural Numbers. European Journal of Educational Research, 11(1), 1-16. https://doi.org/10.12973/eu-jer.11.1.1
  15. Fishbein, M., & Ajzen, I. (1977). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Philosophy and Rhetoric, 10(2).
  16. Fredriksen, H. (2021). Exploring Realistic Mathematics Education in a Flipped Classroom Context at the Tertiary Level. International Journal of Science and Mathematics Education, 19(2), 377-396. https://doi.org/10.1007/s10763-020-10053-1
  17. Gagné, M., & Deci, E. L. (2005). Self‐Determination Theory and Work Motivation. Journal of Organizational behavior, 26(4), 331-362. https://doi.org/10.1002/job.322
  18. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to Use and How to Report the Results of Pls-Sem. European business review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  19. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A Primer on Partial Least Squares Structural Equation Modeling (Pls-Sem). Sage publications.
  20. Hanson, E. R., Gantwerker, E. A., Chang, D. A., & Nagpal, A. S. (2022). To Teach or Not to Teach? Assessing Medical School Faculty Motivation to Teach in the Era of Curriculum Reform. BMC medical education, 22(1), 1-10. https://doi.org/10.1186/s12909-022-03416-5
  21. Holsapple, C. W., & Lee‐Post, A. (2006). Defining, Assessing, and Promoting E‐Learning Success: An Information Systems Perspective. Decision sciences journal of innovative education, 4(1), 67-85. https://doi.org/10.1111/j.1540-4609.2006.00102.x
  22. Holzer, J., Lüftenegger, M., Korlat, S., Pelikan, E., Salmela-Aro, K., Spiel, C., & Schober, B. (2021). Higher Education in Times of Covid-19: University Students’ Basic Need Satisfaction, Self-Regulated Learning, and Well-Being. Aera Open, 7, 23328584211003164. https://doi.org/10.1177/233285842110031
  23. Hwang, H., Cho, G., & Choo, H. (2022). Gsca Pro 1.1 User’s Manual. doi. https://www.gscapro.com/
  24. Hwang, H., & Takane, Y. (2014). Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling. CRC Press.
  25. Johnston, J., McKeown, E., & McEwen, A. (1999). Choosing Primary Teaching as a Career: The Perspectives of Males and Females in Training. Journal of Education for Teaching, 25(1), 55-64. https://doi.org/10.1080/02607479919673
  26. Jung, K., Nguyen, V. T., Piscarac, D., & Yoo, S.-C. (2020). Meet the Virtual Jeju Dol Harubang—the Mixed Vr/Ar Application for Cultural Immersion in Korea’s Main Heritage. ISPRS International Journal of Geo-Information, 9(6), 367. https://doi.org/10.3390/ijgi9060367
  27. Kalenda, J., & Kočvarová, I. (2022). “Why Don’t They Participate?” Reasons for Nonparticipation in Adult Learning and Education from the Viewpoint of Self-Determination Theory. European Journal for Research on the Education and Learning of Adults. https://doi.org/10.3384/rela.2000-7426.3535
  28. Khairunnisak, C., Johar, R., Maulina, S., Zubainur, C. M., & Maidiyah, E. (2022). Teachers’ Understanding of Realistic Mathematics Education through a Blended Professional Development Workshop on Designing Learning Trajectory. International Journal of Mathematical Education in Science and Technology, 1-24. https://doi.org/10.1080/0020739X.2022.2038800
  29. Kilpatrick, J. (2012). The New Math as an International Phenomenon. Zdm, 44(4), 563-571. https://doi.org/10.1007/s11858-012-0393-2
  30. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford publications.
  31. Kusumaningsih, W., & Herman, T. (2018). Improvement Algebraic Thinking Ability Using Multiple Representation Strategy on Realistic Mathematics Education. Journal on Mathematics Education, 9(2), 281-290. https://doi.org/10.22342/jme.9.2.5404.281-290
  32. Lu, Y., Wang, B., & Lu, Y. (2019). Understanding Key Drivers of Mooc Satisfaction and Continuance Intention to Use. Journal of Electronic Commerce Research, 20(2). http://www.jecr.org/node/580
  33. Mariana, N., Sholihah, S., Riski, R., Rahmawati, I., Wiryanto, W., Indrawati, D., & Budiyono, B. (2021). In-Service Teachers’ Perception on Implementing Realistic Mathematics Education Approach in Their Best Practices. Journal of Physics: Conference Series, 1987(1), 012022. https://doi.org/10.1088/1742-6596/1987/1/012022
  34. Mehrabian, A., & Russell, J. A. (1974). An Approach to Environmental Psychology. the MIT Press.
  35. Nguyen, N. T., Chu, A. T., Tran, L. H., Pham, S. X., Nguyen, H. N., & Nguyen, V. T. (2022). Factors Influencing Elementary Teachers’ Readiness in Delivering Sex Education Amidst Covid-19 Pandemic. International Journal of Learning, Teaching and Educational Research, 21(2). https://doi.org/10.26803/ijlter.21.2.18
  36. Oliveira, T., Barbeitos, I., & Calado, A. (2021). The Role of Intrinsic and Extrinsic Motivations in Sharing Economy Post-Adoption. Information Technology & People, 35(1), 165-203. https://doi.org/10.1108/ITP-01-2020-0007
  37. Olsen, A., & Huang, F. (2019). Teacher Job Satisfaction by Principal Support and Teacher Cooperation: Results from the Schools and Staffing Survey. Education Policy Analysis Archives, 27(1), 1-31. https://doi.org/10.14507/epaa.27.4174
  38. Panisoara, I. O., Lazar, I., Panisoara, G., Chirca, R., & Ursu, A. S. (2020). Motivation and Continuance Intention Towards Online Instruction among Teachers During the Covid-19 Pandemic: The Mediating Effect of Burnout and Technostress. International Journal of Environmental Research and Public Health, 17(21), 8002. https://doi.org/10.3390/ijerph17218002
  39. Phan, T. T., Do, T. T., Trinh, T. H., Tran, T., Duong, H. T., Trinh, T. P. T., Do, B. C., & Nguyen, T.-T. (2022). A Bibliometric Review on Realistic Mathematics Education in Scopus Database between 1972-2019. A Bibliometric Review on Realistic Mathematics Education in Scopus Database Between 1972-2019, 11(2), 1133-1149. https://doi.org/10.12973/eu-jer.11.2.1133
  40. Prahmana, R. C. I., Sagita, L., Hidayat, W., & Utami, N. W. (2020). Two Decades of Realistic Mathematics Education Research in Indonesia: A Survey. Infinity Journal, 9(2), 223-246. https://doi.org/10.22460/infinity.v6i1.234
  41. Purwanto, A., Asbari, M., Santoso, T. I., Sunarsi, D., & Ilham, D. (2021). Education Research Quantitative Analysis for Little Respondents: Comparing of Lisrel, Tetrad, Gsca, Amos, Smartpls, Warppls, and Spss. Jurnal Studi Guru Dan Pembelajaran, 4(2).
  42. Razali, F., Manaf, U. K. A., & Ayub, A. F. M. (2020). Stem Education in Malaysia Towards Developing a Human Capital through Motivating Science Subject. International Journal of Learning, Teaching and Educational Research, 19(5), 411-422. https://doi.org/10.26803/ijlter.19.5.25
  43. Rianasari, V. F., Budaya, I. K., & Patahudin, S. M. (2012). Supporting Students' Understanding of Percentage. Journal on Mathematics Education, 3(1), 29-40. https://doi.org/10.22342/jme.3.1.621.29-40
  44. Rifandi, R., Mulyati, A., Rani, M. M., & Al Aziz, S. (2021). Pre-Service Mathematics Teachers’ Perception on Realistic Mathematics Education. Journal of Physics: Conference Series, https://doi.org/10.1088/1742-6596/1940/1/012101
  45. Robitaille, D., & Travers, K. (2003). International Connections in Mathematics Education. A history of school mathematics, 2, 1491-1508.
  46. Ryan, R. M., & Deci, E. L. (2000). Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American psychologist, 55(1), 68. https://doi.org/10.1037/0003-066X.55.1.68
  47. Ryan, R. M., & Moller, A. C. (2017). Competence as Central, but Not Sufficient, for High-Quality Motivation. Handbook of competence and motivation: Theory and application, 216-238.
  48. Shan, Y. (2020). Whether Successful Language Learners Require Intrinsic Motivation. Open Journal of Modern Linguistics, 10(05), 549.
  49. Shanty, N. O. (2016). Investigating Students' Development of Learning Integer Concept and Integer Addition. Journal on Mathematics Education, 7(2), 57-72. https://doi.org/10.22342/jme.7.2.3538.57-72
  50. Soper, D. (2022). Calculator: A-Priori Sample Size for Structural Equation Models. https://www.danielsoper.com/statcalc/calculator.aspx?id=89
  51. Sørebø, Ø., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The Role of Self-Determination Theory in Explaining Teachers’ Motivation to Continue to Use E-Learning Technology. Computers & Education, 53(4), 1177-1187. https://doi.org/10.1016/j.compedu.2009.06.001
  52. Sumanasekera, I., Abd Hamid, J., Khatibi, A., & Azam, S. F. (2021). Involvement and Style of Parents on Student Motivation Towards Student Performance with the Moderating Effect of Academic Causal Factors: Development of a Conceptual Model. Global Journal of Management and Business Research.
  53. Suriazdin, S. A., Hidayanto, A. N., Maulida, M., Kurtinus, A. Y., Arrumaisha, H., Aisyah, N., & Pradana, R. P. (2022). Technology Attractiveness and Its Impact on Mooc Continuance Intention. International Journal of Emerging Technologies in Learning, 17(4). https://doi.org/10.3991/ijet.v17i04.28853
  54. Tang, M., Wang, D., & Guerrien, A. (2020). A Systematic Review and Meta‐Analysis on Basic Psychological Need Satisfaction, Motivation, and Well‐Being in Later Life: Contributions of Self‐Determination Theory. PsyCh journal, 9(1), 5-33. https://doi.org/10.1002/pchj.293
  55. Treffers, A. (1993). Wiskobas and Freudenthal Realistic Mathematics Education. Educational studies in mathematics, 25(1), 89-108. https://doi.org/10.1007/978-94-017-3377-9_6
  56. Uyen, N. T. T., & Vien, T. (2021). Teachers as Researchers: The Perceptions and Practices of Cantho Tertiary Efl Teachers. European Journal of Foreign Language Teaching, 5(5). https://doi.org/10.46827/ejfl.v5i5.3916
  57. Van de Walle, J. A., Karp, K. S., & Bay-Williams, J. M. (2016). Elementary and Middle School Mathematics. Pearson.
  58. Van den Heuvel-Panhuizen, M. (2010). Reform under Attack--Forty Years of Working on Better Mathematics Education Thrown on the Scrapheap? No Way! Mathematics Education Research Group of Australasia. https://eric.ed.gov/?id=ED521409
  59. Van den Heuvel-Panhuizen, M., & Drijvers, P. (2020). Realistic Mathematics Education. Encyclopedia of mathematics education, 713-717. https://doi.org/10.1007/978-3-030-15789-0_170
  60. Van der Sandt, S. (2007). Research Framework on Mathematics Teacher Behaviour: Koehler and Grouws’ Framework Revisited. Eurasia Journal of Mathematics, Science and Technology Education, 3(4), 343-350. https://doi.org/10.12973/ejmste/75413
  61. Van Zanten, M., & Van den Heuvel-Panhuizen, M. (2021). Mathematics Curriculum Reform and Its Implementation in Textbooks: Early Addition and Subtraction in Realistic Mathematics Education. Mathematics, 9(7), 752. https://doi.org/10.3390/math9070752
  62. Wang, C., Cho, H. J., Wiles, B., Moss, J. D., Bonem, E. M., Li, Q., Lu, Y., & Levesque-Bristol, C. (2022). Competence and Autonomous Motivation as Motivational Predictors of College Students’ Mathematics Achievement: From the Perspective of Self-Determination Theory. International Journal of STEM Education, 9(1), 1-14. https://doi.org/10.1186/s40594-022-00359-7
  63. Wubbels, T., Korthagen, F., & Broekman, H. (1997). Preparing Teachers for Realistic Mathematics Education. Educational studies in mathematics, 32(1), 1-28. https://doi.org/10.1023/A:1002900522457
  64. Zhang, M.-H., Su, C.-Y., Li, Y., & Li, Y.-Y. (2020). Factors Affecting Chinese University Students’ Intention to Continue Using Virtual and Remote Labs. Australasian Journal of Educational Technology, 36(2), 169-185. https://doi.org/10.14742/ajet.5939