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Direct linkGerardo Ibarra-Vazquez; María Soledad Ramírez-Montoya; Hugo Terashima – Education and Information Technologies, 2024
This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following…
Descriptors: Foreign Countries, College Students, Private Colleges, Gender Bias
J. E. Tait; L. A. Alexander; E. I. Hancock; J. Bisset – European Journal of Engineering Education, 2024
Engineering students enter a challenging sector in higher education and are potentially at risk of poor mental health and or mental wellbeing and less likely to seek help when experiencing poor mental health or wellbeing. We carried out a scoping review using Joanna Briggs Institute scoping review methodology. Ten databases were searched over a…
Descriptors: Engineering Education, College Students, At Risk Students, Mental Health
