INTRODUCING HIGH SCHOOL STATISTICS TEACHERS TO PREDICTIVE MODELLING BY EXPLORING DYNAMIC MOVIE RATINGS DATA: A FOCUS ON TASK DESIGN

With the advent of data science, recommendations for teaching statistical modelling include adopting a greater focus on prediction. However, there has been minimal research about the design of tasks for teaching predictive modelling from a data science. Therefore, a design-based research approach was used to develop a new web-based task that explored: accessing and using dynamic movie ratings data from an API; developing a model to generate prediction intervals; and modifying and running provided R code in the browser. The task was implemented within a face-to-face teaching experiment involving six high school statistics teachers. Analysis of the teacher responses to the task identified four key task design features that appeared to stimulate development of statistical and computational ideas related to predictive modelling and APIs.