STUDYING STUDENT STATISTICAL LITERACY IN STATISTICS LECTURES ON HIGHER EDUCATION USING GROUNDED THEORY APPROACH

##plugins.themes.bootstrap3.article.sidebar##

PDF
Published: Jan 11, 2022
DOI: https://doi.org/10.22460/infinity.v11i1.p163-176
Keywords:
Grounded Theory Statistical Literacy

##plugins.themes.bootstrap3.article.main##

Lukman Lukman
Universitas Pendidikan Indonesia, Indonesia
Wahyudin Wahyudin
Universitas Pendidikan Indonesia, Indonesia
Didi Suryadi
Universitas Pendidikan Indonesia, Indonesia
Dadan Dasari
Universitas Pendidikan Indonesia, Indonesia
Sufyani Prabawanto
Universitas Pendidikan Indonesia, Indonesia

Abstract

The purpose of this study was to obtain an overview of the student's Statistical Literacy model in Statistics learning in Higher Education. Researchers conducted an in-depth study of student statistical literacy, how they understand and apply statistics, how statistics are used as a tool for reliable data that can be trusted as scientific works. The research method uses qualitative research methods with a Grounded Theory approach. Participants involved in this study were 114 participants from several universities in West Java, Indonesia. The results of this study found a student statistical literacy model consisting of 2 dimensions and 5 elements. Dimensions of Statistical Knowledge: Descriptive Statistics, Inference Statistics, Statistical Communication and Statistical Reasoning. Attitude Dimensions: Confidence and Critical Attitude.

##plugins.themes.bootstrap3.article.details##

Issue
Vol. 11 No. 1 (2022): VOLUME 11, NUMBER 1, INFINITY
Section
Articles
The author is responsible for acquiring the permission(s) to reproduce any copyrighted figures, tables, data, or text that are being used in the submitted paper. Authors should note that text quotations of more than 250 words from a published or copyrighted work will require grant of permission from the original publisher to reprint. The written permission letter(s) must be submitted together with the manuscript.
Author Biography

Lukman Lukman, Universitas Pendidikan Indonesia

Department Mathematics Education

References

Allen, R., Folkhard, A., Abram, B., & Lancaster, G. (2010). Statistics for the biological and environmental sciences: improving service teaching for postgraduates. In The Eighth International Conference on Teaching Statistics (ICOTS8).

Bakker, A., & Gravemeijer, K. P. E. (2004). Learning to reason about distribution. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 147-168). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_7

Batanero, C., Godino, J. D., Vallecillos, A., Green, D. R., & Holmes, P. (1994). Errors and difficulties in understanding elementary statistical concepts. International Journal of Mathematical Education in Science and Technology, 25(4), 527-547. https://doi.org/10.1080/0020739940250406

Batanero, C., Tauber, L. M., & Sánchez, V. (2004). Students’ reasoning about the normal distribution. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 257-276). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_11

Bellinga, P., & Gillebaart, T. (2018). How to collaborate with the media to enhance statistical literacy of the general public. In the Tenth International Conference on Teaching Statistics (ICOTS10).

Ben-Zvi, D., & Garfield, J. (2004). Statistical Literacy, Reasoning, and Thinking: Goals, Definitions, and Challenges. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 3-15). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_1

Chametzky, B. (2016). Coding in classic grounded theory: i’ve done an interview; now what? Sociology Mind, 6(4), 163-172. https://doi.org/10.4236/sm.2016.64014

Chance, B., del Mas, R., & Garfield, J. (2004). Reasoning about sampling distribitions. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 295-323). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_13

Charmaz, K. (2014). Grounded theory in global perspective: Reviews by international researchers. Qualitative Inquiry, 20(9), 1074-1084. https://doi.org/10.1177/1077800414545235

Cobb, G. W., & Moore, D. S. (1997). Mathematics, statistics, and teaching. The American Mathematical Monthly, 104(9), 801-823. https://doi.org/10.1080/00029890.1997.11990723

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

De Finetti, B. (1989). Probabilism. Erkenntnis, 31(2), 169-223. https://doi.org/10.1007/BF01236563

Gal, I. (2002). Adults' statistical literacy: Meanings, components, responsibilities. International Statistical Review / Revue Internationale de Statistique, 70(1), 1-25. https://doi.org/10.2307/1403713

Gal, I. (2004). Statistical Literacy. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp. 47-78). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_3

Gal, I., & Ginsburg, L. (1994). The role of beliefs and attitudes in learning statistics: Towards an assessment framework. Journal of Statistics Education, 2(2), null-null. https://doi.org/10.1080/10691898.1994.11910471

Garfield, J. (1995). How students learn statistics. International Statistical Review / Revue Internationale de Statistique, 63(1), 25-34. https://doi.org/10.2307/1403775

Garfield, J., & Ahlgren, A. (1988). Difficulties in learning basic concepts in probability and statistics: Implications for research. Journal for Research in Mathematics Education JRME, 19(1), 44-63. https://doi.org/10.5951/jresematheduc.19.1.0044

Garfield, J., & Benâ€Zvi, D. (2007). How students learn statistics revisited: A current review of research on teaching and learning statistics. International statistical review, 75(3), 372-396. https://doi.org/10.1111/j.1751-5823.2007.00029.x

Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory Strategies for Qualitative Research. USA and London: Aldine transaction A Division of Transaction Publishers.

Glaser, B. G., & Strauss, A. L. (1995). La production de la théorie à partir des données. Enquête. Archives de la revue Enquête(1), 183-195. https://doi.org/10.4000/enquete.282

Goulding, C. (1999). Grounded Theory: some reflections on paradigm, procedures and misconceptions. http://hdl.handle.net/2436/11403

Hotelling, H. (1951). The Impact of R. A. Fisher on Statistics. Journal of the American Statistical Association, 46(253), 35-46. https://doi.org/10.1080/01621459.1951.10500765

Konold, C., & Pollatsek, A. (2004). Conceptualizing an average as a stable feature of a noisy process. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 169-199). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_8

Krippendorff, K. (2004). Reliability in content analysis: Some common misconceptions and recommendations. Human communication research, 30(3), 411-433. https://doi.org/10.1111/j.1468-2958.2004.tb00738.x

Meng, X.-L. (2009). Desired and feared—What do we do now and over the next 50 years? The American Statistician, 63(3), 202-210. https://doi.org/10.1198/tast.2009.09045

Moritz, J. (2004). Reasoning about covariation. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 227-255). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_10

Neyman, J. (1956). Note on an article by Sir Ronald Fisher. Journal of the Royal Statistical Society: Series B (Methodological), 18(2), 288-294. https://doi.org/10.1111/j.2517-6161.1956.tb00236.x

Noha, M. R. (2013). The importance of statistical analysis in the development of the capabilities of faculty members in the BAU. International Journal of Education, 5(2), 180-191. https://doi.org/10.5296/ije.v5i2.2905

Reading, C., & Shaughnessy, J. M. (2004). Reasoning about variation. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 201-226). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_9

Sharma, S. (2017). Definitions and models of statistical literacy: a literature review. Open Review of Educational Research, 4(1), 118-133. https://doi.org/10.1080/23265507.2017.1354313

Smith, T., & Staetsky, L. (2007). The teaching of statistics in UK universities. Journal of the Royal Statistical Society: Series A (Statistics in Society), 170(3), 581-622. https://doi.org/10.1111/j.1467-985X.2007.00482.x

Spiegelhalter, D., & Riesch, H. (2008). Bacon sandwiches and middle–class drinkers: the risk of communicating risk. Significance, 5(1), 30-33. https://doi.org/10.1111/j.1740-9713.2008.00277.x

Tishkovskaya, S., & Lancaster, G. A. (2012). Statistical education in the 21st century: A review of challenges, teaching innovations and strategies for reform. Journal of Statistics Education, 20(2), 1-56. https://doi.org/10.1080/10691898.2012.11889641

Verhoeven, P. (2006). Statistics education in the Netherlands and Flanders: An outline of introductory courses at Universities and Colleges. In ICOTS-7 Conference Proceedings.

Watson, J., & Callingham, R. (2003). Statistical literacy: A complex hierarchical construct. Statistics Education Research Journal, 2(2), 3-46.

Watson, J. M. (2004). Developing reasoning about samples. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 277-294). Springer Netherlands. https://doi.org/10.1007/1-4020-2278-6_12