Comparing the Effectiveness of Traditional and Active<br><br>Learning Methods in Business Statistics: Convergence to the<br><br>Mean


Authors: 
David Weltman and Mary Whiteside
Volume: 
18(1)
Pages: 
online
Year: 
2010
Publisher: 
Journal of Statistics education
URL: 
http://www.amstat.org/publications/jse/v18n1/weltman.pdf
Abstract: 

This research shows that active learning is not universally effective and, in fact, may<br><br>inhibit learning for certain types of students. The results of this study show that as<br><br>increased levels of active learning are utilized, student test scores decrease for those<br><br>with a high grade point average. In contrast, test scores increase as active learning is<br><br>introduced for students in the lower level grade point average group. Every student<br><br>involved in the experiment is taught three topics, each one by a different teaching<br><br>method. Students take a test following each learning session to assess comprehension.<br><br>The experiment involves more than 300 business statistics students in seven class<br><br>sections. Method topic combinations are randomly assigned to class sections so that<br><br>each student in every class section is exposed to all three experimental teaching<br><br>methods. The effect of method on student score is not consistent across grade point<br><br>average. Performance of students at three different grade point average levels tended to<br>converge around the overall mean when learning was obtained in an active learning<br><br>environment. The effects of the teaching method on score do not depend on other<br><br>student characteristics analyzed (i.e. gender, learning style, or ethnicity). A linear mixed<br><br>model is used in the analysis of results

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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