Branching out data science education: Developing task and computational environment design principles for teaching data science at the high school level through an international research collaboration
DOI:
https://doi.org/10.52041/iase25.138Abstract
Data science is rapidly emerging as a desired component of education, yet generalisable design principles for tasks and computational environments remain underdeveloped. This paper reports on a design-based research collaboration between Germany and New Zealand, which aims to develop and refine such design principles for high school data science education. Drawing on literature and prior research, we propose that the design of tasks and computational environments should integrate humanistic, algorithmic, and programming approaches. The three key design “branches” of our research are: (1) emphasising a humanistic focus through data construction and exploration; (2) using decision trees to develop algorithmic modelling concepts; (3) using computer programming for gaining insights, supporting creativity, and model tinkering. These branches are illustrated through examples from our collaborative work. Our research contributes to the development of effective educational strategies for data science education and could inform the development of professional development for high school teachers.References
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