10th International
Conference on
Teaching Statistics
8 – 13 July 2018
Kyoto, Japan
Contributed paper list

Contributed Paper C220


An Application of the Mixture Rasch Model: Classifying Pre-service Teachers on the Self-Efficacy to Teach Statistics


Leigh Harrell-Williams (USA)
Jennifer Lovett (USA)
M. Alejandra Sorto (USA)
Rebecca Pierce (USA)
Lawrence Lesser (USA)
Teri Murphy (USA)


Leigh Harrell-Williams (United States)


Recent studies using the Self-Efficacy to Teach Statistics instruments found pre-service teachers (PSTs), as a group, exhibit higher self-efficacy for certain statistical topics among the GAISE Level A subscale items than for other statistical topics. Hence, this study explores latent classes for statistics teaching self-efficacy using Rasch mixture modeling of item-level response data. Four classes were identified for n = 588 middle and secondary mathematics PSTs. One class had consistently high efficacy; one had consistently low efficacy. Four items related to graphical displays contributed to differences between the middle two classes, contradicting previous findings that PSTs, on average, are more confident about teaching graphical displays than other topics. Hence, evaluation of statistics teaching self-efficacy should possibly include examination of specific content areas along with subscale scores.