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Statistical Data Analysis in Education Essay (Critical Writing)


Overview

In the area of education, much attention should be paid to the development of statistical reasoning in teachers. Scheaffer and Jacobbe (2014) and Utts (2015) state that the use of statistical data with the focus on its further analysis and interpretation is often a challenge for educators, and they need to concentrate on developing skills in working with statistical methods.

In their article “Hold My Calls: An Activity for Introducing the Statistical Process,” Abel and Poling (2015) described the specific statistical activity that can be used in the teaching-learning process at the secondary level to explain the principles of the statistical process. The article was published in Teaching Statistics, and this descriptive research aimed to discuss aspects of the statistical process with the focus on data analysis and interpretation.

Description of the Research Problem

The statistical process is based on a set of concrete phases that should be performed in a series. The data analysis and interpretation are usually regarded as the most challenging stages of this process (Slootmaeckers, Kerremans, & Adriaensen, 2014). Students’ skills need to be improved regarding the use of statistical methods to conduct studies and analyze the data (Dierker, Cooper, Alexander, Selya, & Rose, 2015).

The problem is in the fact that many teachers also do not have enough skills to apply and explain statistical methods appropriately (Ben-Zvi, 2014; Fotache & Strimbei, 2015). Thus, Abel and Poling (2015) focused on describing the particular statistical activity aimed at providing students and educators with clear information regarding the stages of the statistical process.

Research Methodology: Design, Approach, and Structure

The article by Abel and Poling (2015) presents the description of the results of implementing the GAISE framework for the statistical process. The researchers recruited practicing teachers to participate in the study and use the four-step GAISE model to examine how the use of mobile phones can influence the person’s reactions on roads.

Four groups of participants were formed, and the practical sessions were held for two days. The structure of the article depends on the number of components in the GAISE framework. Thus, the article includes the following sections: Abstract, Introduction, Context, Statistical Process and Activity, including such tasks as to formulate questions, collect data, analyze data, and interpret results, Discussion, and Conclusion.

Data and Research Conclusions

Abel and Poling (2015) focused on collecting the narrative data regarding the results of the activity to conclude about the successes related to implementing the GAISE framework. It was found that all groups of teachers discussed the activity as important to be implemented in the classroom settings because the framework allowed for understanding the nature of stages in the statistical process. The participants emphasized the problems associated with the choice of appropriate statistical methods to analyze the data. Also, the participants accentuated the possibility of adapting the framework to students’ needs.

Critique of the Article

Abel and Poling’s (2015) article has a descriptive title that allows for making conclusions regarding the article’s content, but the abstract is rather short, and it does not provide all the useful information about the work. Still, the authors present the clear purpose of the study in the introduction, and it is impossible to state that this article is appropriate to explain the nature of analyzing and interpreting statistical data in the field of education. The researchers chose to assess the participants’ results at each stage related to the GAISE framework. This approach is effective while paying attention to the nature of the descriptive study.

Thus, Abel and Poling (2015) were able to evaluate successes of the participants regarding the choice of graphs for the statistical analysis, and they determined weaknesses in teachers’ approaches to analyzing the data with the focus on the selection of wrong statistical methods. The section related to the interpretation stage was also effective because the researchers provided a comprehensive analysis of the participants’ activities regarding the challenging task of interpreting the study results.

Still, the detailed information about the procedures for analyzing and interpreting the data was presented only in the section where the activity was described, and the Discussion section needs improvement. It is important to pay more attention to discussing why the procedure of analyzing the statistical data is important, and how mistakes in the analysis can influence the process of interpretation (Ziegler & Garfield, 2013). Therefore, it is possible to expand the Discussion section and provide references to other studies to evaluate the received results.

Despite the determined limitations in the presentation and discussion of the study results, it is possible to state that the authors’ statements are clear, and based on the evidence. Thus, to support their ideas, the authors cited the limited number of studies, but all of them can be discussed as directly related to the study. The purpose of the research was achieved, and the authors’ conclusions are reasonable.

Conclusion

The article by Abel and Poling is effective to accentuate the importance of the data analysis and interpretation stages in the statistical process, as well as to determine possible challenges for educators and students. Still, the article requires improvements in terms of developing its sections. More attention should be paid to the discussion of the activity’s results in the context of prior studies.

References

Abel, T., & Poling, L. (2015). Hold my calls: An activity for introducing the statistical process. Teaching Statistics, 37(3), 96-103.

Ben-Zvi, D. (2014). Data handling and statistics teaching and learning. Mathematics Education, 1(2), 137-140.

Dierker, L., Cooper, J., Alexander, J., Selya, A., & Rose, J. (2015). Evaluating access: A comparison of demographic and disciplinary characteristics of students enrolled in a traditional introductory statistics course vs. a multidisciplinary, project-based course. Journal of Interdisciplinary Studies in Education, 4(1), 22-37.

Fotache, M., & Strimbei, C. (2015). SQL and data analysis: Some implications for data analysts and higher education. Procedia Economics and Finance, 20(1), 243-251.

Scheaffer, R. L., & Jacobbe, T. (2014). Statistics education in the K–12 schools of the United States: A brief history. Journal of Statistics Education, 22(2), 1-10.

Slootmaeckers, K., Kerremans, B., & Adriaensen, J. (2014). Too afraid to learn: Attitudes towards statistics as a barrier to learning statistics and to acquiring quantitative skills. Politics, 34(2), 191-200.

Utts, J. (2015). The many facets of statistics education: 175 years of common themes. The American Statistician, 69(2), 100-107.

Ziegler, L., & Garfield, J. (2013). Teaching bits: Statistics education articles from 2012 and 2013. Journal of Statistics Education, 21(1), 1-18.

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"Statistical Data Analysis in Education." IvyPanda, 3 Aug. 2020, ivypanda.com/essays/statistical-data-analysis-in-education/.

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IvyPanda. "Statistical Data Analysis in Education." August 3, 2020. https://ivypanda.com/essays/statistical-data-analysis-in-education/.

References

IvyPanda. 2020. "Statistical Data Analysis in Education." August 3, 2020. https://ivypanda.com/essays/statistical-data-analysis-in-education/.

References

IvyPanda. (2020) 'Statistical Data Analysis in Education'. 3 August.

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