Critical Control Points Course Detection Methodology at University Education


The research presents an innovative study based on adding value to the university educational process. Currently, there is no clear definition to detect at which stage of a career students lag behind after failing a specific subject or activity. An educational innovation proposal, based on the extrapolation of the Hazard Analysis and Critical Control Point System coming from the industrial setting to the university education context, is presented: the Critical Control Point Detection System concerning the curriculum and students' trajectories. The purpose of this work is to generalise a Critical Control Points Detection Methodology, in higher education, through the localization of courses that have greater incidence in the curriculum and identifying the negative result through student performance due to failure. For the curriculum analysis, indicators related to centrality measures were built with a directed network based on the curriculum subjects. Courses were classified as Critical-Control-Point candidates when the numerical values of measures exceed or equal to a minimum threshold value. For student performance, a measure of course failure was used. Those candidate courses exceeding a predefined failure threshold were classified as Critical Control Points. Critical-Control-Points courses implied at least one semester of lagging for any student failing on it. The Critical Control Point Detection Methodology was performed for Chemical Engineering and Law curriculums at the University of the Republic (Uruguay) using a (55 ± 5)% threshold of failure for more than two years during five years. The Critical-Control-Point courses match previous perceptions from university lecturers.

Author Information
Martín Pratto Burgos, University of the Republic, Uruguay

Paper Information
Conference: BCE2023
Stream: Educational policy

This paper is part of the BCE2023 Conference Proceedings (View)
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To cite this article:
Burgos M. (2023) Critical Control Points Course Detection Methodology at University Education ISSN: 2435-9467 – The Barcelona Conference on Education 2023: Official Conference Proceedings
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Posted by James Alexander Gordon