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Applying Challenge Based Learning to Teach Mass Transfer

Applying Challenge Based Learning to Teach Mass Transfer

Authors :
Barrera Puigdollers, Cristina
Castelló Gómez, María Luisa
Seguí Gil, Lucía
Heredia Gutiérrez, Ana Belén
García Hernández, Jorge
Source :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Publication Year :
2022
Publisher :
TEMPUS PUBLICATIONS, DUBLIN INST TECHNOLOGY, BOLTON ST, DUBLIN, IRELAND, 2022.

Abstract

[EN] In order to enhance undergraduates' understanding of mass transfer unit operations, Challenge-Based Learning (CBL) was applied in two courses on Transport Phenomena in the Food Industry. The courses are part of Agrifood Engineering Degree program at the Universitat Politecnica de Valencia (UPV). After the lecturers explained the topic to the fourth-year students, they were given the challenge of preparing and solving cases of mass transport phenomena dealing with solid-liquid extraction and food drying. Students were divided into six groups of three or four students; each group chose a product to work with, and each group designed a flowchart with the main stages of the process based on the information gathered from varied bibliographical sources. The corresponding mathematical models were applied to characterize the flow and estimate the performance and efficiency. After that, students wrote short reports of the main steps followed to complete the task. The reports were presented to a panel of expert lecturers to provide feedback and recommendations. Specifically designed rubrics were employed by the panel to assess the impact of the methodology on students' subject-specific skills in addition to collaborative work, problem solving, time management and oral presentation skills.<br />This work was supported by the Universitat Politecnica de Valencia with the Grant PIME/20-21/208.

Details

Language :
English
Database :
OpenAIRE
Journal :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Accession number :
edsair.dedup.wf.001..12b675ef964915ee6c2eef0cc4d1e227