Combining Surveys and Sensors to Explore Student Behaviour

Inkeri Kontro , Mathieu Génois (1, 2)

1 CPT - E5 Physique statistique et systèmes complexes
2 CPT - Centre de Physique Théorique - UMR 7332

Student belongingness is important for successful study paths, and group work forms an important part of modern university physics education. To study the group dynamics of introductory physics students at the University of Helsinki, we collected network data from seven laboratory course sections of approximately 20 students each for seven consecutive weeks. The data was collected via the SocioPatterns platform, and supplemented with students' major subject, year of study and gender. We also collected the Mechanics Baseline Test to measure physics knowledge and the Colorado Learning Attitudes about Science Survey to measure attitudes. We developed metrics for studying the small networks of the laboratory sessions by using connections of the teaching assistant as a constant. In the network, we found both demographically homogeneous and heterogeneous groups that are stable. While some students are consistently loosely connected to their networks, we were not able to identify risk factors. Based on our results, the physics laboratory course is equally successful in building strongly connected groups regardless of student demographics in the sections or the formed small groups. SocioPatterns supplemented with surveys thus provides an opportunity to look into the dynamics of students' social networks.

Mots clés: student retention; undergraduate laboratory; small group; network; physics education

Domaines: Physique et Société [physics.soc-ph]; Analyse de données, Statistiques et Probabilités [physics.data-an]; Santé publique et épidémiologie; Sociologie; Adaptation et Systèmes auto-organisés [nlin.AO]

Inkeri Kontro, Mathieu Génois. Combining Surveys and Sensors to Explore Student Behaviour. Education Sciences, 2020, 10 (3), pp.68. ⟨10.3390/educsci10030068⟩. ⟨hal-02504851⟩