Technology for insight into student beliefs<br>about statistics in large classes


Authors: 
Michael Bulmer and Emma Low
Pages: 
online
Year: 
2008
Publisher: 
Proceedings from the 6TH AUSTRALIAN CONFERENCE ON TEACHING STATISTICS (OZCOTS)
URL: 
http://silmaril.math.sci.qut.edu.au/ozcots2008/OZCOTS-08-Proceedings.pdf
Abstract: 

Prior beliefs and attitudes of students can have a significant impact on their learning experience<br>but it is usually difficult to engage with student beliefs in depth when dealing with large classes.<br>As part of an ALTC Associate Fellowship project, we have developed technologies and strategies<br>for facilitating connections between staff and student beliefs through the embedding of student<br>reflective writing in statistics courses. Students were free to write whatever they liked in their<br>journals but weekly themes were also provided to give them a starting point if needed. The aim of<br>this paper is to give an overview and analysis of entries around the themes that were particularly<br>related to beliefs about statistics, as well as to demonstrate the use of text mining tools in this<br>context.

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