Mathematical Modelling and Argumentation: Designing a Task to Strengthen Variational Thinking by Integrating Data Science

Abstract

This study explores the significance of task design in fostering variational thinking through the principles of PyLVar and task design in mathematics education, particularly in the incorporation of technological and scientific tools to enhance modelling and argumentation skills among secondary school students. To develop and implement interactive mathematical tasks based on the PyLVar principle and task design, incorporating data science tools and STEAM. A qualitative-descriptive approach was employed to design, implement, and analyse interactive tasks centred on the principles of variational thinking, argumentation, and modelling. The sample consisted of nine participants selected from a group of 11th-grade students at a state school, chosen for convenience. Data were gathered through experimental activities, processed using technological tools, and analysed with variational strategies. Students demonstrated a marked improvement in their abilities in mathematical modelling and argumentation. The tasks designed, structured around the PyLVar principles, enabled the identification of variation patterns and the development of critical and analytical skills. Contextualised interactive mathematical tasks not only bolster variational thinking but also equip students to address real-world problems by connecting abstract concepts to practical applications and encouraging the integration of technological tools and interdisciplinary approaches