Teaching from an informal statistical inference perspective can address the challenge of teaching statistics in a coherent way. We argue that activities that promote model-based reasoning address two additional challenges: providing a coherent sequence of topics and promoting the application of knowledge to novel situations. We take a models and modeling perspective as a framework for designing and implementing an instructional sequence of model development tasks focused on developing primary students' generalized models for drawing informal inferences when comparing two sets of data. This study was conducted with 26 Year 5 students (ages 10-11). Our study provides empirical evidence for how a modeling perspective can bring together lines of research that hold potential for the teaching and learning of inferential reasoning.
|Original language||English (US)|
|Number of pages||30|
|Journal||Statistics Education Research Journal|
|State||Published - Nov 1 2017|
Bibliographical noteFunding Information:
The data from this paper come from a grant funded by the Australian Research Council (DP120100690). The first and second authors’ airfares to Australia were paid by Travel Awards for International Collaboration Research (Category 1) from The University of Queensland.
© International Association for Statistical Education (IASE/ISI), November, 2017.
- Informal statistical inference
- Model development sequences
- Model eliciting activities
- Model-based reasoning
- Statistics education research