Using Excel in Teacher Education for Sustainability

Author:

Aydın Serhat1

Affiliation:

1. Karamanoğlu MehtmetBey University, Turkey

Abstract

Abstract In this study, the feasibility of using Excel software in teaching whole Basic Statistics Course and its influence on the attitudes of pre-service science teachers towards statistics were investigated. One hundred and two pre-service science teachers in their second year participated in the study. The data were collected from the prospective teachers before and after the compulsory Basic Statistics Course. This is a course offered in the third term aiming at introducing the most basic concepts and operations in descriptive and inferential statistics. In the context of this course, it could be argued that in most universities basically four concept groups are addressed: 1) Data and distributions, 2) How values cluster and/or disperse, 3) How variables move, classify or cluster jointly and 4) How the means between different groups differentiate. The statistics course with the content mentioned above is usually handled theoretically and nearly no statistical software is used considering the needs and expectations of pre-service science teachers. In case a software is used, it is generally SPSS in Turkey. SPSS is nearly the standard in the field here and dominates all other software such as SAS etc. On the other hand, Excel with much of its capabilities, accessibility and ease of use, is not considered by most of the academics as sufficient statistical software. In this paper the capabilities, accessibility and practicality of Excel program in teaching most basic statistics course topics to pre-service science teachers were demonstrated and its superiority to other softwares and traditional instruction were discussed. In addition, the positive effect of such an instruction on the attitudes of pre-service teachers towards statistics was shown.

Publisher

Walter de Gruyter GmbH

Subject

Education

Reference33 articles.

1. Bartz, S. (2007). Excelblatt vereinfacht Stochastik. Stochastik in der Schule, 27(2), 25–29.

2. Borovcnik, M. (2007). Das Sammelbildproblem – Rosinen und Semmeln und Verwandtes: Eine rekursive Lösung mit Irrfahren. Stochastik in der Schule, 27(2), 19–24.

3. Carlberg, C. (2014). Statistical Analysis: Microsoft Excel 2013. Que Publishing.

4. Chiesi, F., & Primi, C. (2010). Cognitive and non-cognitive factors related to students’ statistics achievement. Statistics Education Research Journal, 9(1), 6–26.

5. Cleveland, W. (1994). The elements of graphing data. Summit. New Jersey: Hobart Press.

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