Web-based Student Learning of Statistics

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Research and Development in Higher Education Vol. 30: Enhancing Higher Education, Theory and Scholarship

July, 2007, 651 pages
Published by
Geoffrey Crisp & Margaret Hicks
ISBN
0 908557 72 8
Abstract 

A need was identified for a statistical learning system that combines a statistical package offering all standard statistical procedures together with a system that helps students to learn the rudiments of statistics through experiential learning. The WebStat Data Analysis and Learning System, a web-based student learning system, is designed to fulfill this need. Currently, the system can handle large data sets from a range of sources and perform all standard and commonly used statistical procedures such as descriptive statistics, regression analyses, and more sophisticated statistical modelling such as Generalised Linear Models (GLM). WebStat utilises the program R, one of the most sophisticated and extensive statistical programs available. It can be used by many students, particularly non-statistics research students. WebStat can be further developed to suit a wide range of users. In this paper, we describe and discuss the advantages of using WebStat as a learning tool, along with identifying the main features of and possible improvements to the current design.

Keywords: web-based statistical learning system, experiential learning, statistical software