Concluding Remarks

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Copyright: 2017
Pages: 7
Source title: Assessing and Measuring Statistics Cognition in Higher Education Online Environments: Emerging Research and Opportunities
Source Author(s)/Editor(s): Justin P. Chase (University at Albany (SUNY), USA)and Zheng Yan (University at Albany (SUNY), USA)
DOI: 10.4018/978-1-5225-2420-5.ch007

Keywords: Education / Higher Education / Information Science Reference / Learning Assessment and Measurement

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Abstract

In this chapter, we provide brief concluding remarks which focus on summarizing key frameworks discussed throughout the first six chapters. We argue that by developing a testable model of statistics cognition we can make specific predictions about learning and errors which can help provide educators with the guidance needed to curb the influence errors can have on learning. Additionally, by developing a cognitive curriculum, which is designed to assess student affect and make use of meaningful individual differences, we can enhance the quality of statistics education in online environments. We conclude this chapter by outlining several future directions that can help facilitate our understanding of statistics cognition.

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