INTRODUCING HIGH SCHOOL STATISTICS TEACHERS TO PREDICTIVE MODELLING AND APIs USING CODE-DRIVEN TOOLS
DOI:
https://doi.org/10.52041/serj.v21i2.49Keywords:
Statisitcs education research, Data science education, Predictive modeling, Integrating statistical and computational thinking, Task design, High school teachers, APIsAbstract
Tasks for teaching predictive modelling and APIs often require learners to use code-driven tools. Minimal research, however, exists about the design of tasks that support the introduction of high school students and teachers to these new statistical and computational methods. Using a design-based research approach, a web-based task was developed. The task was constructed using our design framework and implemented within a face-to-face professional development workshop involving six high school statistics teachers. The teachers were guided through the process of developing a prediction model using: an informal approach; visual prediction intervals; data about movie ratings from an API; and R code that ran in the browser. Our findings from this exploratory study indicate that the web-based task supported the development of new statistical and computational ideas related to predictive modelling and APIs.
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