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


Contributed Paper C220

In session C2A  (Monday 9th, 14:00-15:30,   Level 3E - Room A)

Using the SETS level A items to classify pre-service teachers' self-efficacy to teach statistics: an application of the Mixture Rasch Model


Authors

Leigh Harrell-Williams (University of Memphis, USA)
Jennifer Lovett (Middle Tennessee State University, USA)
M. Alejandra Sorto (Texas State University, USA)
Rebecca Pierce (Ball State University, USA)
Lawrence Lesser (University of Texas at El Paso, USA)
Teri Murphy (University of Cincinnati, USA)

Presenter

Leigh Harrell-Williams (United States)

Abstract

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.