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Sep 30, 2018
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Abstract

The purpose of this study was to explore students' attitudes toward statistics (ATS) based on the beginning and the end of learning, based on differences in fields of study, and examine its relationship with statistical acheivement. ATS was measured by an attitude instrument, namely The Survey of Attitudes toward Statistics (SATS) which consists of six dimensions (affective, cognitive competence, difficulty, value, interest, effort). Research respondents were undergraduate students who took lectures on statistical recognition that came from at one of the universities in South Sumatra. The results of the descriptive analysis showed the variation of ATS in each dimension of attitudes classified into positive, neutral, or negative attitudes. Although there are variations in the response of student attitudes in each dimension, but the results of statistical tests have not been able to show differences in attitudes between the beginning and the end of learning in each dimension. The differences in attitudes between the beginning and the end of learning that are statistically significant are in the dimensions of affective, value, and effort. The difference in the field of student science shows the difference in ATS, but only in the dimension of value. This study does not have enough evidence to state that there is a significant relationship between student attitudes to statistics and the results of learning statistics.

Keywords

Attitudes toward Statistics Field of Study Statistics Achievement

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References

  1. Andrews, S. (2010). Statistical Software for Teaching: Relevant, Appropriate and Affordable. In Proceeding of The Eight International Conference of Teaching Statistics (Vol. 8).
  2. Arifin, Z. (2016). Evaluasi Pembelajaran: Prinsip, Teknik, dan Prosedur. Bandung: PT Remaja Rosdakarya.
  3. Ashaari, N. S., Judi, H. M., Mohamed, H., & Tengku Wook, T. M. (2011). Student’s Attitude Towards Statistics Course. Procedia - Social and Behavioral Sciences, 18, 287–294. https://doi.org/10.1016/j.sbspro.2011.05.041
  4. Biehler, R., Ben-zvi, D., Bakker, A., & Makar, K. (2013). Technology for Enhancing Statistical Reasoning at the School Level. In Third international Handbook of Mathematics Education (pp. 643–689). New York: Springer. https://doi.org/10.1007/978-1-4614-4684-2
  5. Cahyawati, D. (2015). The Interest of Prospective Students in Study Programs in Higher Education: a Preliminary Study. In The 6th International Conference on Educational, Management, Administration and Leadership (ICEMAL2016) (pp. 312–317).
  6. Chan, S. W., & Ismail, Z. (2013). Assessing Misconceptions in Reasoning About Variability Among High School Students. Procedia - Social and Behavioral Sciences, 93, 1478–1483. https://doi.org/10.1016/j.sbspro.2013.10.067
  7. Chiesi, F., & Primi, C. (2009). Assessing Statistics Attitudes among College Students: Psychometric Properties of The Italian Version of The Survey of Attitudes toward Statistics (SATS). Learning and Individual Differences, 19(2), 309–313. https://doi.org/10.1016/j.lindif.2008.10.008
  8. Chiesi, F., & Primi, C. (2010). Gender Differences in Attitudes Toward Statistics : Is There a Case for a Confidence Gap ?, 1–10.
  9. Cohen, J. (1992). A Power Primer. Psychological Bulletin, 112(1). https://doi.org/10.1038/141613a0
  10. Djaali. (2014). Psikologi Pendidikan. Jakarta: Bumi Aksara.
  11. Gal, I., Ginsburg, L., & Schau, C. (1997). Monitoring Attitudes and Beliefs in Statistics Education. In The Assessment Challenge in Statistics Education. Amsterdam: IOS Press.
  12. García-Santillán, A., Escalera-Chávez, M. E., Rojas-Kramer, C. A., & Pozos-Texon, F. J. (2014). Empirical Study on Students and Their Attitudes toward Statistics Course and Statistical Field. American Journal of Educational Research, 2(12), 1151–1159. https://doi.org/10.12691/education-2-12-4
  13. Garfield, J. B., & Ben-Zvi, D. (2008). Developing Students’ Statistical Reasoning: Connecting Research and Teaching Practice. New York: Springer.
  14. Ghulami, H. R., Hamid, M. R. A., & Zakaria, R. (2015). Students’ Attitudes towards Learning Statistics. In AIP Conference Proceeding (Vol. 050035, p. 050035). https://doi.org/10.1063/1.4915668
  15. Griffith, J. D., Adams, L. T., Gu, L. L., Hart, C. L., & Nichols-Whitehead, P. (2012). Students’ Attitudes Toward Statistics Across The Disciplines: A Mixed-Methods Approach. Statistics Education Research Journal, 11(2), 45–56.
  16. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. New Jersey: Pearson.
  17. Hake, R. R. (1999). Analyzing Change/Gain Scores. Unpublished.[Online] URL: Http://Www. Physics. Indiana. Edu/\~ Sdi/AnalyzingChange-Gain. Pdf. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22025883%5Cnhttp://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:ANALYZING+CHANGE/GAIN+SCORES#0%5Cnhttp://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Analyzing+change/gain+scores%230
  18. Hannula, M. S., Di Martino, P., Pantziara, M., Zhang, Q., Morselli, F., Heyd-Metzuyanim, E., … Goldin, G. A. (2016). Attitudes, Beliefs, Motivation and Identity in Mathematics Education: An Overview of the Field and Future Direction (ICME 13). Hamburg: Springer Open. https://doi.org/10.1007/978-3-319-32811-9
  19. Hilton, S. C., Schau, C., & Olsen, J. A. (2004). Survey of Attitudes Toward Statistics: Factor Structure Invariance by Gender and by Administration Time. Structural Equation Modeling: A Multidisciplinary Journal, 11(1), 92–109. https://doi.org/10.1207/S15328007SEM1101_7
  20. Jahan, S., Al-Saigul, A. M., & Suliman, A. A. (2016). Attitudes to Statistics in Primary Health Care Physicians, Qassim Province. Primary Health Care Research & Development, 17(04), 405–414. https://doi.org/10.1017/S1463423615000535
  21. Kumari, B. (2014). The Correlation of Personality Traits and Academic Performance : A Review of Literature. IOSR Journal Of Humanities And Social Science (IOSR-JHSS), 19(4), 15–18.
  22. Liau, A. K., Kiat, J. E., & Nie, Y. (2014). Investigating the Pedagogical Approaches Related to Changes in Attitudes Toward Statistics in a Quantitative Methods Course for Psychology Undergraduate Students. Asia-Pacific Education Researcher, 24(2), 319–327. https://doi.org/10.1007/s40299-014-0182-5
  23. Menkumham-RI. (2005). Peraturan Pemerintah Nomor 19 Tahun 2005 tentang Standar Nasional Pendidikan. https://doi.org/10.1007/s13398-014-0173-7.2
  24. Ramirez, C., Schau, C., & Emmioǧlu, E. (2012). The Importance of Attitudes in Statistics Education. Statistics Education Research Journal, 11(2), 57–71.
  25. Schau, C. (2004). Scoring the SATS-28 ©, 21–22.
  26. Schau, C. (2008). Common issues in SATS © research. Joint Statistical Meetings Proceedings, 1–4.
  27. Schau, C., Dauphinee, T. L., Del Vecchio, A., & Stevens, J. (1999). Survey of Attitudes toward Statistics (SATS). Retrieved January, 2, 2006.
  28. Tempelaar, D. T., Schim Van Der Loeff, S., & Guselaers, W. H. (2007). A Structural Equation Model Analyzing The Relationship of Students’ Toward Statistics. Statistics Education Research Journal, 6(2).
  29. Thalheimer, W., & Cook, S. (2002). How to Calculate Effect Sizes from Published Research: A Simplified Methodology. Work-Learning Research, (August), 1–9. https://doi.org/10.1113/jphysiol.2004.078915
  30. Yuwono, M. R. (2018). The Correlation between Cognitive Style and Students’ Learning Achievement on Geometry Subject. Infinity Journal of Mathematics Education, 7(1), 35–44. https://doi.org/10.22460/infinity.v7i1.p35-44