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Combining the project‐based learning methodology and computer simulation to enhance the engagement in the context of Environmental Engineering courses
Author(s) -
Faba Laura,
Díaz Eva
Publication year - 2020
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.22303
Subject(s) - teamwork , computer science , dynamism , context (archaeology) , process (computing) , relevance (law) , project based learning , curriculum , engineering management , software , engineering , mathematics education , psychology , paleontology , pedagogy , physics , mathematics , quantum mechanics , political science , biology , law , programming language , operating system
This paper analyses the good results obtained in an Environmental Engineering course at the master level after a complete revision of the lecturing system. The traditional methodology (lectures and seminars) was substituted by a project‐based learning strategy, in which students work in groups proposing and developing technical solutions to an actual environmental problem, with the aim of identifying the optimum one, combining technical and economic points of view. This new teaching methodology has been identified as a good approach to increase the students' engagement, with significant improvements in grades (from average values close to 5/10 to >7/10) and better impressions expressed by the students, which can identify the relevance of environmental problems in the development of their own professional curriculum. The core of this methodology is the use of GPS‐X software to study and analyse the different approaches proposed by the students as solutions for their project, to optimise the designs, to study the sensitivity to different process conditions and to evaluate the energy and maintenance costs of each proposal. GPS‐X software is an inductive and comprehensive tool to reinforce previous theoretical concepts and allows a fast analysis of the responses of industrial plants after each disruption, increasing the dynamism of the learning process. The final assessment, based on the continuous evaluation and a final written report, allows the evaluation of transversal skills, such as teamwork, self‐management, communication and problem‐solving, difficult to assess by a traditional methodology.