This qualitative case study investigates the interaction sequences that emerge among secondary school students engaged in mathematical modelling tasks using digital technologies. The study focuses on four groups of 14–17-year-old students in southern Norway, varying in achievement levels, as they worked on two distinct mathematical modelling tasks. Task 1 involved numerical manipulation and function development based on given data, while Task 2 required qualitative decision-making without explicit numerical constraints. Recorded interactions, comprising video and screen-capture data, were analysed using thematic analysis, focusing on pseudo, asymmetrical, reactive and mutual interaction sequences. The findings indicate that Task 1 predominantly elicited asymmetrical interaction sequences, with high-performing students taking the lead in proposing solutions, reflecting limited exchange patterns. In contrast, Task 2 fostered more reactive and mutual interaction sequences, supporting balanced and equitable exchanges within groups. Additionally, group composition shaped interaction patterns: same-achievement, high-performing upper secondary groups and mixed-achievement lower secondary groups demonstrated more mutual and reactive interaction sequences across tasks, while mixed-achievement upper secondary groups exhibited more varied patterns. The study highlights how task design, group composition and digital technology use interact to influence collaborative learning dynamics in mathematical modelling.
Afram et al. (2026) studied this question.