<jats:p>Students are not aware and have little understanding of collecting and processing personal data in their everyday contexts of interaction with data-driven digital artifacts. To be aware of where, how and why data are collected and processed is important to be self-determined. Therefore, we develop and evaluate a teaching sequence to provide reasoning about data as a fundamental aspect of statistical literacy. This teaching sequences deals with the context of interaction with a cellular network where location data are collected. Students get real location data from an unknown person which can be explored with the aim to characterize the person. Students gain different insights by using different basic filters and explain how they achieve these. The results of the exploratory study indicate that students learned to gain insights by exploring given location data and that these insights may describe the person with detailed aspects that may not necessarily be true.</jats:p>

Students often have a lack of understanding and awareness of where, how, and why personal data about them is collected and processed. Especially, when interacting with data-driven digital artifacts, an appropriate perception of the data collection and processing is necessary for self-determination. This dissertation deals with the development and evaluation of a concept called data awareness which aims to foster students’ self-determination interacting with data-driven digital artifacts.