Design, Experimentation and Statistical Validation of a Methodology to Solve Complex Engineering Problems in Higher Education

This article proposes a methodology that addresses the problem that many university professors often have with their students when facing complex engineering problems, causing frustration and desertion (abandonment of the problem to be solved). Although there are antecedents of works that emphasize...

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Published inSustainability Vol. 14; no. 4; p. 2240
Main Authors Rosales-Torres, Conrado, Gijón-Rivera, Carlos, Garay-Rondero, Claudia Lizette, Castillo-Paz, Álvaro, Domínguez-Ramírez, Gerardo
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.02.2022
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ISSN2071-1050
2071-1050
DOI10.3390/su14042240

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Abstract This article proposes a methodology that addresses the problem that many university professors often have with their students when facing complex engineering problems, causing frustration and desertion (abandonment of the problem to be solved). Although there are antecedents of works that emphasize the relevance of the realistic context in engineering problems and the importance of being structured in solving problems, we did not find measured effectiveness from the study of a group of students. This methodology focuses on engineering problems, in such a way that the decomposition of the problems in four steps responds to the solution process of the profiles of the analyzed subjects. The process followed in the preparation, implementation, validation, and reliability of this methodology is detailed. The experiment was designed to test both the effectiveness and reliability of the methodology. Four control groups for three different courses and periods were analyzed before and after the training of the four-step methodology. The observed factor was the variable score (0–100 points). The statistical analysis comprises descriptive statistics; Normality test for each population group; Paired t-Test/Wilcoxon test, and General linear model ANOVA (2 factors). The statistical analysis and tests show how the groups involved in the experiment obtained a significant benefit when the methodology for academic performance evaluations was applied.
AbstractList This article proposes a methodology that addresses the problem that many university professors often have with their students when facing complex engineering problems, causing frustration and desertion (abandonment of the problem to be solved). Although there are antecedents of works that emphasize the relevance of the realistic context in engineering problems and the importance of being structured in solving problems, we did not find measured effectiveness from the study of a group of students. This methodology focuses on engineering problems, in such a way that the decomposition of the problems in four steps responds to the solution process of the profiles of the analyzed subjects. The process followed in the preparation, implementation, validation, and reliability of this methodology is detailed. The experiment was designed to test both the effectiveness and reliability of the methodology. Four control groups for three different courses and periods were analyzed before and after the training of the four-step methodology. The observed factor was the variable score (0–100 points). The statistical analysis comprises descriptive statistics; Normality test for each population group; Paired t-Test/Wilcoxon test, and General linear model ANOVA (2 factors). The statistical analysis and tests show how the groups involved in the experiment obtained a significant benefit when the methodology for academic performance evaluations was applied.
Audience Academic
Author Domínguez-Ramírez, Gerardo
Gijón-Rivera, Carlos
Garay-Rondero, Claudia Lizette
Rosales-Torres, Conrado
Castillo-Paz, Álvaro
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SubjectTerms Academic achievement
Access to information
Analysis
Cognition & reasoning
Cognitive ability
College teachers
Education, Higher
Engineering education
Engineers
Higher education
Learning
Methods
Problem solving
STEM education
Students
Teaching
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