Students' managing of modelling problems with superfluous data

Research has shown that students often encounter difficulties in processing modelling problems with missing data. Modelling problems often also contain superfluous data and differentiating between these data and relevant ones is a key competency for carrying out the modelling process. We thus investigate students’ processing of data in a modelling task, wondering to what extent they differentiate between relevant and superfluous data, and how can the anomalous use of relevant and superfluous data be characterized. We perform a qualitative content analysis of the protocols produced by 102 secondary school students, while working in groups. The analysis shows that, for most data, students successfully distinguished relevant and superfluous data. It also provides a first characterization of students’ anomalous use of data, which confirms the students’ tendency of focusing on numerical data and not considering reality in modelling problems.