Novices’ reasoning with big data and data-ing through the lens of uncertainty

Abstract

AbstractAdvancements in computing and statistical analyses have significantly transformed mathematics education, integrating it with data and computer science. As big data becomes increasingly prevalent, understanding its complexities, including its unique uncertainties, is crucial. This study explores the uncertainty that novice students can articulate during their initial engagement with big data, including both data preparation activities or data-ing as well as data analysis activities. Consistent with prior research on students’ engagement with small data, we offer a case study revealing that novices can also exhibit extreme views of uncertainty while engaging with big data. Contrary to the context of small data engagement, our analysis revealed different sources for these extreme views. The classification we used can offer means to identify students’ uncertainty views and support them in developing a more balanced, mature, perception of uncertainty. Moreover, the analysis underscores students’ inclination towards high-uncertainty articulations during their initial encounters with big data-ing activities.