Enhancing Individual Learning through Inclusive Computational Practices: A Case Study in Financial Mathematics Labs

In higher education, Financial Mathematics and Computational Finance represent distinct but interconnected areas in which the integration of Computational Thinking is particularly relevant. Inclusive computational practices appropriately designed by teachers and implemented within a computer-supported collaborative learning (CSCL) environment can foster students’ knowledge co-construction. This study investigates how tailored Computational Finance practices involving VBA for Excel and Python, when synergistically integrated into group-based interactions within a face-to-face CSCL environment, enhance individual learning. The context of the research is the Advanced Computational Finance module at University College Dublin, Ireland, in Spring 2024. The study analyses the achievement of seven specific learning outcomes among 22 undergraduate students (BSc) who participated in weekly collaborative lab activities, compared with a group of 5 postgraduate students (MSc) who did not. Quantitative analysis of a final learning test administered to students reveals that the BSc cohort consistently outperformed the MSc group across nearly all learning outcomes. The most significant differences appeared in higher-order cognitive processes, such as modelling, data modification and evaluation. These findings suggest that student-led, collaborative lab activities that feature inclusive computational practices are critical drivers of sensemaking and the development of Computational Thinking skills in Financial Mathematics at the individual level.