Implementation of Modeling Tools for Teaching Biorefinery (Focused on Bioethanol Production) in Biochemical Engineering Courses: Dynamic Modeling of Batch, Semi-Batch, and Continuous Well-Stirred Bioreactors
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AuthorMartín Lara, María Ángeles
BiofuelBioprocessingChallenge-based learningComputer-based learningEnergy engineeringHigher education
Martín-Lara, M.Á.; Ronda, A. Implementation of Modeling Tools for Teaching Biorefinery (Focused on Bioethanol Production) in Biochemical Engineering Courses: Dynamic Modeling of Batch, Semi-Batch, and Continuous Well-Stirred Bioreactors. Energies 2020, 13, 5772. [https://doi.org/10.3390/en13215772]
Due to the ever-growing pressure on our planet’s natural resources to supply energy, the production of bioethanol by fermentation of lignocellulosic biomass is increasingly important in courses related to engineering and energy. Moreover, recent changes in the teaching–learning paradigm make necessary the introduction of novel teaching tools where students are the protagonist of their education. In this context, the purpose of this study is to compare the results obtained after traditional lessons with those obtained after the implementation of various computer activities based on modeling and simulation of bioreactors to teach biorefinery concepts focused on bioethanol production. Berkeley Madonna was chosen as the digital simulation software package because it is user-friendly, fast, and easy to program. This software allowed students to gain experience writing models that let optimize fermentations in well-stirred bioreactors and others bioprocess of industrial interest. The students (those who participated in the modeling-simulation classes and those who participated in traditional ones) completed a questionnaire and a cognitive test at the end of the course. Students that participated in modeling-simulation classes got a better score than students that participated in traditional classes. Therefore, the study showed the improvement in the understanding of the biorefinery concepts and the students improved their grades. Finally, students’ perception about the proposed modeling-simulation learning was also analyzed and they rated the efficiency of this new learning methodology as satisfactory. There are very few studies providing information about educational experiences regarding the development of skills for the formulation, interpretation, simplification, and use of mathematical models based on mass balances and simple microbial kinetics in biochemical engineering courses. The experience described in this work can be used by professors to plan and conduct courses based on the modeling of biochemical engineering problems.