Learning Statistics with a Multimedia Resource

Learning Statistics with a Multimedia Resource

Olusola O. Adesope (Washington State University, Pullman, USA)
DOI: 10.4018/978-1-4666-0068-3.ch010
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Abstract

Researchers have often reported the negative attitude and low performance of students in statistics (Francis, 2002; Gordon, 1995; Ograjenšek & BavdažKveder, 2003). While considerable efforts and research have been undertaken to remedy this situation, researchers, educators, and policy makers have admitted a degree of failure in the teaching and learning of statistics and advocated a radical rethinking in the way statistics education is implemented (Cobb & Moore, 1997; Moore, 1997, 2005; Weldon, 2005). One approach that has been advanced is the use of multimedia instruction. Nolan and Lang (2006) observed that the potential for multimedia to enhance the statistics curriculum is clear, but there are challenges to developing instructional materials that take advantage of the riches of multimedia. It requires more than a simple translation of textbooks into the computer in order to obtain a tool that is effective for learning statistics. While statistical tools like SPSS have improved analyses of data, it has not significantly improved the learning of statistical concepts (Hawkins, Jolliffe, & Glickman, 1992). This has necessitated recommendations that technologies should not only be used as a computational tool, but also as a means for providing students with opportunities to explore conceptual ideas (Franklin & Garfield, 2006). It seems plausible that effectively-designed multimedia resources may help alleviate some of the difficulties students face in learning statistics. This chapter describes a prototype digital resource (StatConquer) for learning about correlation of bivariate data1, an important topic in many introductory statistics courses. The Chapter also explains how application of some principles in cognitive load theory and multimedia learning theory might facilitate students’ understanding of correlation. It is expected that by delineating the pedagogical approach of StatConquer, educators, researchers, policy makers, and instructional designers may adapt this design framework for developing other learning tools.

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