2020/05/02 by Suzane F. Pinto, Pinto, Suzane F., Ronan S. Ferreira +1
Engineering · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Complex Network Analysis Techniques #Experimental Learning in Engineering #FOS: Physical sciences #Physics Education (physics.ed-ph) #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.2005.00906
openalex publication_date 2020/05/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We analyze the curriculum of the early common-years of engineering in our institute using tools of statistical physics of complex networks. Naturally, a course programme is structured in a networked form (temporal dependency and prerequisites). In this approach, each topic within each programme is associated with a node, which in turn is joined by links representing the dependence of a topic for the understanding of another in a different discipline. As a course programme is a time-dependent structure, we propose a simple model to assign links between nodes, taking into account only two ingredients of the teaching-learning process: recursiveness and accumulation of knowledge. Since we already know the programmes, our objective is to verify if the proposed model is able to capture their particularities and to identify implications of different sequencing on the student learning in the early years of engineering degrees. Our model can be used as a systematic tool assisting the construction of a more interdisciplinary curriculum, articulating between disciplines of the undergraduate early-years in exact sciences.