Analysis of Statistical Thinking Ability of Mathematics Students Based on Artist Test

Hadi Kusmanto

doi:10.24235/eduma.v12i2.13474

Analysis of Statistical Thinking Ability of Mathematics Students Based on Artist Test

Hadi Kusmanto^(1*),

(1) IAIN Syekh Nurjati Cirebon
(*) Corresponding Author

Abstract

This study aims to determine the statistical thinking skills of mathematics students and their differences based on gender, school origin, and semester level. To map the statistical thinking skills using the modified Artist test standards. The development of students' statistical thinking skills is one of the focuses of learning mathematics in Higher Education. Students' statistical thinking ability is absolutely necessary to be able to think scientifically. Statistical thinking is the ability to think inductively. The population in this study were all mathematics students, while the sampling was based on proportional random sampling. The data analysis technique uses the t-test, Anova, and Least Significance Difference (LSD) as a follow-up test. Based on the results of the analysis carried out, it was found that students 'statistical thinking skills were classified as low which was below the value of 60 on a scale of 100. These results indicated that students' statistical thinking skills were still low, especially the ability to communicate data and draw conclusions. Another result shows that there is a difference in the ability to think statistically at the semester level, while there is no difference between sex and school origin. For semesters, third-semester students do better than other semesters

Keywords

Statistical thinking; The artist test; Student performance evaluation

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References

Britz, G., Emerling, D., Hare, L., Hoerl, R., & Shade, J. (1997). How to teach others to apply statistical thinking. Quality Progress, 30(6), 67â€“79.

Ben- Zvi, D. & Garfield, J (1990). (Eds). (in press). The challenge of developing statistical literacy,

reasoning, and thinking. Dordrecht, The Netherlands: Kluwer Academic Publishers.

DelMas, R. C. (2004). A Comparison Of Mathematical and Statistical reasoning. Journal of Statistics Education, 8, 79â€“95.

Pfannkuch, M., & Wild, C. (1998). Investigating The Nature Of Statistical Thinking (pp. 461â€“467).

Moore, D. (1990). Uncertainty. In L. Steen (Ed.) On the shoulders of giants: new approaches

to numeracy (pp. 95-137). Washington, D.C.: National Academy Press.

S. Suriasumantri, J. (2003). Filsafat Ilmu Sebuah Pengantar Populer. Jakarta: Pustaka Sinar Harapan.

Shaughnessy, J. M. (1996). Missed opportunities in research on the teaching and learning of data and chance. In Proceedings of the Twentieth Annual Conference of the Mathematics Education Research Group of Australasia (pp. 6â€“22).

Snee, R. D. (1990). Statistical Thinking and Its Contribution to Total Quality. The American Statistician, 44(2), 116â€“123. https://doi.org/10.2307/2684144

Snee, R. D. (1993). Whatâ€™s missing in statistical education? American Statistician, 47(2), 149â€“154. https://doi.org/10.1080/00031305.1993.10475964

Snee, R. (1999). Discussion: Development and use of statistical thinking: A new era. International Statistical Review, 67(3), 255-258

Triyono. (2018). Teknik Sampling Dalam Penelitian. Fakultas Ilmu Tarbiayah UIN Yogyakarta, 7(1), 2â€“9. https://doi.org/10.13140/RG.2.2.19674.24003

Watson, J. M., Collis, K. F., Callingham, R. A., & Moritz, J. B. (1995). A Model for Assessing Higher Order Thinking in Statistics. Educational Research and Evaluation, 1(3), 247â€“275. https://doi.org/10.1080/1380361950010303

DOI: 10.24235/eduma.v12i2.13474

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