High school students’ data modeling practices and processes: from modeling unstructured data to evaluating automated decisions

It’s critical to foster artificial intelligence (AI) literacy for high school students, the first generation grow up surrounded by AI, understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made engage youth in understanding through developing machine learning models, few provided in-depth insights into nuanced processes. In this study, we examined students’ data modeling practices Twenty-eight students developed models with text classifying negative positive reviews ice cream stores. We identified nine that describe processes model exploration, development, testing two themes about evaluating technologies. The results provide implications designing accessible experiences justice as well role responsibility modelers creating