Hypothesis testing reasoning is recognized as a difficult area for students. Changing to a new paradigm for learning inference through computer intensive methods rather than mathematical methods is a pathway that may be more successful. To explore ways to improve students’ inferential reasoning at the Year 13 (last year of school) and introductory university levels, our research group developed new learning trajectories and dynamic visualizations for the randomization method. In this paper we report on the findings from a pilot study including student learning outcomes and on the modifications we intend to make before the main study. We discuss how the randomization method using dynamic visualizations clarifies concepts underpinning inferential reasoning and why the nature of the argument still remains a challenge.
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