Evaluating Two Models of Collaborative Tests in an Online Introductory Statistics Course


Authors: 
Auðbjörg Björnsdóttir, Joan Garfield, and Michelle Everson
Year: 
2015
URL: 
http://iase-web.org/documents/SERJ/SERJ14(1)_Bjornsdottir.pdf
Abstract: 

This study explored the use of two different types of collaborative tests in an online introductory statistics course. A study was designed and carried out to investigate three research questions: (1) What is the difference in students’ learning between using consensus and non-consensus collaborative tests in the online environment?, (2) What is the effect of using consensus and non-consensus collaborative tests on students’ attitudes towards statistics?, and (3) How does using a required consensus vs. a non-consensus approach on collaborative tests affect group discussions? Qualitative and quantitative methods were used for data analysis. While no significant difference was found between groups using the two collaborative testing formats, there was a noticeable increase in students’ attitudes across both formats towards learning statistics. This supports prior research on the benefits of using collaborative tests in face-to-face courses.

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