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Permanent URI for this collectionhttps://hdl.handle.net/11285/345355
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- Data analytics to predict dropout in a MOOC course on energy sustainability(2021-09-20) Riofrío Calderón, Gioconda; Ramírez Montoya, María Soledad; Rodríguez Conde, María José; Instituto Tecnológico y de Estudios Superiores de Monterrey; University of BarcelonaMassive open online courses (MOOCs) offer multiple advantages and vast training possibilities in diverse topics for millions of people worldwide to continue their education. However, dropout rates are high; thus, it is important to continue investigating the reasons for dropout to implement new and better strategies to increase course completions. The present study aimed to analyze the data of a MOOC class on energy sustainability to know why students drop out, identify causes, and predict dropouts in future courses. The method used was Knowledge Discovery in Databases to analyze association rules in the data. Using the Mexico X platform, an initial, validated survey instrument was applied to 1506 students enrolled in the MOOC course "Conventional Clean Energy and its Technology." The results indicated that association rules allowed identifying participants' behavior according to the type of responses with a determined confidence level. Also, the association rules were appropriate for working with a large amount of data. In the present case, results of up to 86% confidence were obtained based on the rules. This research can be of value to decision-makers, teachers, researchers, designers, and those interested in large-scale training environments
- Theoretical and Methodological Proposal on the Development of Critical Thinking through Mathematical Modeling in the Training of Engineers(2019-10-16) Acebo, Claudia Jaqueline; Rodríguez Gallegos, Ruth; Instituto Tecnológico de MonterreyThe present work constitutes a research advance, which takes up previous work where the teaching of Mathematics in higher education is modified through experimentation in the classroom using the modeling of real phenomena and / or simulation. The idea is to rethink Mathematical modeling as a didactic strategy that aims to develop not only disciplinary but also transversal competencies such as Critical Thinking. A review of ideas around Critical Thinking is shown, and this is intended to show that Mathematical modeling can help develop this competency in the Mathematics classroom. A theoretical proposal of how we conceive Mathematical modeling and methodological proposals is presented along with elements to look at these processes in the classroom. Considering that this study focuses on the study of the articulation of mathematical modeling as a didactic strategy and on critical thinking, based on mathematical modeling activities, the level of critical thinking of engineering students who perform these modeling activities in a Differential Equations course will be evaluated.