Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.procs.2020.05.107
Title: An authentic learning approach to engage solid waste engineering students
Authors: Lefebvre, O. 
Luo, J.
Keywords: Authentic learning
Blended learning
Evaluation methodology
Flipped classroom
Research in engineering education
Issue Date: 2020
Publisher: Elsevier B.V.
Citation: Lefebvre, O., Luo, J. (2020). An authentic learning approach to engage solid waste engineering students. Procedia Computer Science 172 : 748-759. ScholarBank@NUS Repository. https://doi.org/10.1016/j.procs.2020.05.107
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Abstract: With solid waste management being such a crucial and tangible issue in the XXIst century, a blended learning environment was fashioned in a solid waste engineering module for graduate students. The emphasis was in creating authentic projects in partnership with the National Environment Agency (NEA) and the Ministry of Education to increase waste awareness and promote the circular economy across various schools in Singapore. The connection between engagement and authentic learning was verified empirically by means of focus group interviews and questionaires, followed by statistical analysis. A Pearson correlation coefficient of 0.86 and linear regression coefficient of 0.73 (p value = 0.093) demonstrated the positive correlation between these two factors. Finally, a Bayesian bootstrap approach helped overcome the small sample size and confirmed the satisfying positive relation found between authentic learning and engagement. From focus group interviews, it appeared that most students found that the authentic projects accurately reflected the real world problems. One student commented: “I particularly found the NEA project meaningful and certainly appreciate the effort put in with NEA and the schools to prepare the class for this project. I'm beginning to look for ways as to how I can reduce solid waste myself!”. © 2020 The Authors. Published by Elsevier B.V.
Source Title: Procedia Computer Science
URI: https://scholarbank.nus.edu.sg/handle/10635/197794
ISSN: 18770509
DOI: 10.1016/j.procs.2020.05.107
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
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