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Beta: Jurnal Tadris Matematika
Articles
DOI: 10.20414/betajtm.v17i1.584
Submitted: 2023-08-15
Published: 2024-05-31

Prospective primary mathematics teachers’ attitude towards statistics

Universitas Pasundan
Universitas Kristen Indonesia
Attitudes Statistics Prospective teachers Gender

Galleys

Abstract

[English]: This study aimed to assess attitudes of prospective primary mathematics teachers (PPTs) toward statistics and how these attitudes are influenced by gender. It adopted Attitudes Towards Statistics Survey (SATS-36) and involved 455 PPTs from 9 Teachers Training Institutions (TTI).  Exploratory factor analysis (EFA) was performed because the model fit for confirmatory factor analysis (CFA) failed to yield good indices of reliability and validity. The validated model only contains 27 items in four factors that assess attitudes including competence, values, difficulties, and interests. The prospective teachers’ attitudes toward statistics and the impact of gender were then evaluated using a modified four-factor model. The finding shows that PPTs have a positive attitude toward statistics. In specific, the female participants tend to have a more positive attitude toward statistics than the male.

[Bahasa]: Penelitian ini bertujuan menilai sikap calon guru matematika sekolah dasar terhadap statistika dan bagaimana sikap tersebut dipengaruhi oleh jenis kelamin. Penelitian ini mengadopsi Survei Sikap terhadap Statistik (SATS-36) dan melibatkan 455 calon guru dari 9 Lembaga Pendidik Tenaga Kependidikan. Analisis faktor eksploratori (EFA) dilakukan karena model yang cocok untuk analisis faktor konfirmatori (CFA) gagal menghasilkan indeks yang baik untuk reliabilitas dan validitas. Model yang telah divalidasi hanya memuat 27 item dalam empat faktor untuk menilai sikap yang meliputi kompetensi, nilai, kesulitan, dan minat. Sikap calon guru terhadap statistik dan dampak gender kemudian dievaluasi menggunakan model empat faktor yang dimodifikasi. Hasil penelitian menunjukkan bahwa calon guru mempunyai sikap positif terhadap statistik. Secara spesifik, calon guru perempuan lebih mempunyai sikap positif terhadap statistik daripada calon guru laki-laki.

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References

  1. Ahn, P. H., Dexter, F., Fahy, B. G., & Van Swol, L. M. (2020). Demonstrability of analytics solutions and shared knowledge of statistics and operating room management improves expected performance of small teams in correctly solving problems and making good decisions. Perioperative Care and Operating Room Management, 19(November 2019), 100090.1-7. https://doi.org/10.1016/j.pcorm.2020.100090
  2. Alalwan, N., Cheng, L., Al-Samarraie, H., Yousef, R., Ibrahim Alzahrani, A., & Sarsam, S. M. (2020). Challenges and prospects of virtual reality and augmented reality utilization among primary school teachers: A Developing Country Perspective. Studies in Educational Evaluation, 66(September 2019), 100876.1-12. https://doi.org/10.1016/j.stueduc.2020.100876
  3. Barber, S. J. (2020). The applied implications of age-based stereotype threat for older adults. Journal of Applied Research in Memory and Cognition, 9(3), 274–285. https://doi.org/10.1016/j.jarmac.2020.05.002
  4. Bardach, L., & Klassen, R. M. (2020). Smart teachers, successful students? A systematic review of the literature on teachers’ cognitive abilities and teacher effectiveness. Educational Research Review, 30(November 2019), 100312.1-21. https://doi.org/10.1016/j.edurev.2020.100312
  5. Berndt, M., Schmidt, F. M., Sailer, M., Fischer, F., Fischer, M. R., & Zottmann, J. M. (2021). Investigating statistical literacy and scientific reasoning & argumentation in medical, social sciences, and economics students. Learning and Individual Differences, 86(February 2021), 101963.1-9. https://doi.org/10.1016/j.lindif.2020.101963
  6. Chang, S. H., Shu, Y., Wang, C. L., Chen, M. Y., & Ho, W. S. (2020). Cyber-entrepreneurship as an innovative orientation: Does positive thinking moderate the relationship between cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions in Non-IT students? Computers in Human Behavior, 107(January), 105975.1-8. https://doi.org/10.1016/j.chb.2019.03.039
  7. Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173(July 2021), 121092.1-11. https://doi.org/10.1016/j.techfore.2021.121092
  8. Dushimimana, J. C., & Uworwabayeho, A. (2020). Teacher training college student performance in statistics and probability exams in Rwanda. Rwandan Journal of Education, 5(1), 68–81. https://www.ajol.info/index.php/rje/article/view/202576
  9. Espinoza, A. M., & Taut, S. (2020). Gender and psychological variables as key factors in mathematics learning: A study of seventh graders in Chile. International Journal of Educational Research, 103(May), 101611.1-16. https://doi.org/10.1016/j.ijer.2020.101611
  10. Estrada, A., & Batanero, C. (2019). Prospective primary school teachers’ attitudes towards probability and its teaching. International Electronic Journal of Mathematics Education, 15(1), 1–14. https://doi.org/10.29333/iejme/5941
  11. Filiz, M., Early, E., Thurston, A., & Miller, S. (2020). Measuring and improving university students’ statistics self-concept: A systematic review. International Journal of Educational Research Open, 1(December), 100020.1-16. https://doi.org/10.1016/j.ijedro.2020.100020
  12. Frederick, D. A., Garcia, J. R., Gesselman, A. N., Mark, K. P., Hatfield, E., & Bohrnstedt, G. (2020). The Happy American Body 2.0: Predictors of affective body satisfaction in two U.S. national internet panel surveys. Body Image, 32(1), 70–84. https://doi.org/10.1016/j.bodyim.2019.11.003
  13. Gao, W., Ping, S., & Liu, X. (2020). Gender differences in depression, anxiety, and stress among college students: A longitudinal study from China. Journal of Affective Disorders, 263(15 February 2020), 292–300. https://doi.org/10.1016/j.jad.2019.11.121
  14. García-Castro, J. D., Rodríguez-Bailón, R., & Willis, G. B. (2020). Perceiving economic inequality in everyday life decreases tolerance to inequality. Journal of Experimental Social Psychology, 90(May), 104019.1-10. https://doi.org/10.1016/j.jesp.2020.104019
  15. Groth, R., & Meletiou-Mavrotheris, M. (2018). Research on statistics teachers’ cognitive and affective characteristics. https://doi.org/10.1007/978-3-319-66195-7_10
  16. Guillen-Gamez, F. D., Mayorga-Fernández, M. J., & Del Moral, M. T. (2020). Comparative research in the digital competence of the pre-service education teacher: Face-to-face vs blended education and gender. Journal of E-Learning and Knowledge Society, 16(3), 1–9. https://doi.org/10.20368/1971-8829/1135214
  17. Guo, P., Saab, N., Post, L. S., & Admiraal, W. (2020). A review of project-based learning in higher education: Student outcomes and measures. International Journal of Educational Research, 102(November 2019), 101586.1-13. https://doi.org/10.1016/j.ijer.2020.101586
  18. Huang, S. Y., Kuo, Y. H., & Chen, H. C. (2020). Applying digital escape rooms infused with science teaching in elementary school: Learning performance, learning motivation, and problem-solving ability. Thinking Skills and Creativity, 37(129), 100681.1-17. https://doi.org/10.1016/j.tsc.2020.100681
  19. Huang, X., Mayer, R. E., & Usher, E. L. (2020). Better together: Effects of four self-efficacy-building strategies on online statistical learning. Contemporary Educational Psychology, 63(October 2020), 101924.1-50. https://doi.org/10.1016/j.cedpsych.2020.101924
  20. Huh, S. (2020). Reflections as 2020 comes to an end: The editing and educational environment during the COVID-19 pandemic, the power of Scopus and Web of Science in scholarly publishing, journal statistics, and appreciation to reviewers and volunteers. Journal of Educational Evaluation for Health Professions, 17(30 December 2020), 1–7. https://doi.org/10.3352/JEEHP.2020.17.44
  21. Keng, S. H. (2020). Gender bias and statistical discrimination against female instructors in student evaluations of teaching. Labour Economics, 66(July 2020), 1-12. https://doi.org/10.1016/j.labeco.2020.101889
  22. Kreft, C., Huber, R., Wuepper, D., & Finger, R. (2021). The role of non-cognitive skills in farmers’ adoption of climate change mitigation measures. Ecological Economics, 189(January 2020), 107169.1-11. https://doi.org/10.1016/j.ecolecon.2021.107169
  23. Kucuk, S., & Sisman, B. (2020). Students’ attitudes towards robotics and STEM: Differences based on gender and robotics experience. International Journal of Child-Computer Interaction, 23–24(June 2020), 100167.1-8. https://doi.org/10.1016/j.ijcci.2020.100167
  24. Legaki, N. Z., Xi, N., Hamari, J., Karpouzis, K., & Assimakopoulos, V. (2020). The effect of challenge-based gamification on learning: An experiment in the context of statistics education. International Journal of Human Computer Studies, 144(June), 1-14. https://doi.org/10.1016/j.ijhcs.2020.102496
  25. Legesse, M., Luneta, K., & Ejigu, T. (2020). Analyzing the effects of mathematical discourse-based instruction on eleventh-grade students’ procedural and conceptual understanding of probability and statistics. Studies in Educational Evaluation, 67(January 2020), 100918.1-7. https://doi.org/10.1016/j.stueduc.2020.100918
  26. Lu, H. F. (2023). Statistical learning in sports education: A case study on improving quantitative analysis skills through project-based learning. Journal of Hospitality, Leisure, Sport and Tourism Education, 32(January 2023), 100417. 1-13. https://doi.org/10.1016/j.jhlste.2023.100417
  27. Madaki, A. A. (2021). Mathematics education in Sub-Saharan Africa: Status, challenges, and opportunities. African Scholars Journal of Contemporary Education Research, 23(8), 203–218.
  28. Mai, R., Niemand, T., & Kraus, S. (2021). A tailored-fit model evaluation strategy for better decisions about structural equation models. Technological Forecasting and Social Change, 173(1), 121142.1-17. https://doi.org/10.1016/j.techfore.2021.121142
  29. Male, H., & Lumbantoruan, J. H. (2021). Students’ perceptions and attitudes towards statistics. Atlantis Press, 560(Acbleti 2020), 507–513. https://doi.org/https://doi.org/10.2991/assehr.k.210615.095
  30. Martynenko, O. O., Pashanova, O. V., Korzhuev, A. V., Prokopyev, A. I., Sokolova, N. L., & Sokolova, E. G. (2023). Exploring attitudes towards STEM education: A global analysis of university, middle school, and elementary school perspectives. Eurasia Journal of Mathematics, Science and Technology Education, 19(3), 1-7. https://doi.org/10.29333/ejmste/12968
  31. Meier, M. A., Wambacher, D., Vogel, S. E., & Grabner, R. H. (2022). Interference between naïve and scientific theories in mathematics and science: An fMRI study comparing mathematicians and non-mathematicians. Trends in Neuroscience and Education, 29(October), 1-17. https://doi.org/10.1016/j.tine.2022.100194
  32. Oluoch, S., Lal, P., Susaeta, A., & Vedwan, N. (2020). Assessment of public awareness, acceptance and attitudes towards renewable energy in Kenya. Scientific African, 9(September 2020), e00512.1-13. https://doi.org/10.1016/j.sciaf.2020.e00512
  33. Patricia Aguilera-Hermida, A. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1(July), 100011.1-8. https://doi.org/10.1016/j.ijedro.2020.100011
  34. Ribosa, J., & Duran, D. (2022). Do students learn what they teach when generating teaching materials for others? A meta-analysis through the lens of learning by teaching. Educational Research Review, 37(May), 100475.1-16. https://doi.org/10.1016/j.edurev.2022.100475
  35. Rodríguez-Hernández, C. F., Cascallar, E., & Kyndt, E. (2020). Socio-economic status and academic performance in higher education: A systematic review. Educational Research Review, 29(February 2020), 100305.1-75. https://doi.org/10.1016/j.edurev.2019.100305
  36. Sáez-López, J. M., Cózar-Gutiérrez, R., González-Calero, J. A., & Carrasco, C. J. G. (2020). Augmented reality in higher education: An evaluation program in initial teacher training. Education Sciences, 10(2), 1–12. https://doi.org/10.3390/educsci10020026
  37. Sahin, D., & Yilmaz, R. M. (2020). The effect of augmented reality technology on middle school students’ achievements and attitudes towards science education. Computers and Education, 144(January 2020), 103710.1-24. https://doi.org/10.1016/j.compedu.2019.103710
  38. Saloviita, T., & Pakarinen, E. (2021). Teacher burnout explained: Teacher-, student-, and organisation-level variables. Teaching and Teacher Education, 97(May 2012), 103221.1-14. https://doi.org/10.1016/j.tate.2020.103221
  39. Schau, C., Stevens, J., Dauphinee, T. L., & Vecchio, A. Del. (1995). The development and validation of the survey of antitudes toward statistics. Educational and Psychological Measurement, 55(5), 868–875. https://doi.org/10.1177/0013164495055005022
  40. Sebastien, L. (2020). The power of place in understanding place attachments and meanings. Geoforum, 108(November 2020), 204–216. https://doi.org/10.1016/j.geoforum.2019.11.001
  41. Silvola, A., Näykki, P., Kaveri, A., & Muukkonen, H. (2021). Expectations for supporting student engagement with learning analytics: An academic path perspective. Computers and Education, 168(July 2021), 1-12. https://doi.org/10.1016/j.compedu.2021.104192
  42. Sokal, L., Trudel, L. E., & Babb, J. (2020). Canadian teachers’ attitudes toward change, efficacy, and burnout during the COVID-19 pandemic. International Journal of Educational Research Open, 1(October), 100016.1-8. https://doi.org/10.1016/j.ijedro.2020.100016
  43. Ting, F. S. T., Shroff, R. H., Lam, W. H., Garcia, R. C. C., Chan, C. L., Tsang, W. K., & Ezeamuzie, N. O. (2023). A meta-analysis of studies on the effects of active learning on asian students’ performance in Science, Technology, Engineering and Mathematics (STEM) subjects. Asia-Pacific Education Researcher, 32(3), 379–400. https://doi.org/10.1007/s40299-022-00661-6
  44. Uğurlu, F., Yıldız, S., Boran, M., Uğurlu, Ö., & Wang, J. (2020). Analysis of fishing vessel accidents with Bayesian network and Chi-square methods. Ocean Engineering, 198(August 2019), 1-13. https://doi.org/10.1016/j.oceaneng.2020.106956
  45. Uttl, B., White, C. A., & Gonzalez, D. W. (2017). Meta-analysis of faculty’s teaching effectiveness: Student evaluation of teaching ratings and student learning are not related. Studies in Educational Evaluation, 54(September 2017), 22–42. https://doi.org/10.1016/j.stueduc.2016.08.007
  46. Wakhata, R., Mutarutinya, V., & Balimuttajjo, S. (2023). Dataset on the relationship between students’ attitude towards, and performance in mathematics word problems, mediated by active learning heuristic problem-solving approach. Data in Brief, 48(14 March 2023), 109055.1-8. https://doi.org/10.1016/j.dib.2023.109055
  47. Yu, Z., & Deng, X. (2022). A meta-analysis of gender differences in e-learners’ self-efficacy, satisfaction, motivation, attitude, and performance across the world. Frontiers in Psychology, 13(May), 1–14. https://doi.org/10.3389/fpsyg.2022.897327

How to Cite

Dahlan, T., & Lumbantoruan, J. H. (2024). Prospective primary mathematics teachers’ attitude towards statistics. Beta: Jurnal Tadris Matematika, 17(1), 77–86. https://doi.org/10.20414/betajtm.v17i1.584

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