ABSTRACT

University dropout is a phenomenon of growing interest due to the high financial costs that it involves for both families and states. Various variables have been studied in order to understand why this problem occurs. Satisfaction with the degree choice, study self-regulation and social adaptation within the university are some of the variables that are most important when studying the dropout intention. However, studying these variables is not an easy task and Fuzzy Inference Systems have helped by reducing the subjectivity of language. Therefore, the objective of this research is to adapt Fuzzy Inference Systems to improve knowledge about the intention to remain at university. We performed descriptive analyses, a classification tree and Multiple-criteria Decision-Making based on Analytic Hierarchy Process (AHP) and Fuzzy Inference Systems (FIS) on a sample of 1912 students from different universities in Spain. We saw a relationship between the three variables studied and the intention to remain. In conclusion, there is no single variable for understanding the phenomenon of university dropout, but several variables that interact within a holistic model.

摘要

大学辍学是一种越来越引起人们关注的现象，因为它涉及家庭和州的高昂财务成本。为了理解为什么会出现这个问题，已经研究了各种变量。在研究辍学意愿时，对学位选择、学习自我调节和社会适应的满意度是一些最重要的变量。然而，研究这些变量并不是一件容易的事，模糊推理系统通过降低语言的主观性而有所帮助。因此，本研究的目的是调整模糊推理系统，以提高对留在大学意图的了解。我们进行了描述性分析，分类树和基于层次分析过程 (AHP) 和模糊推理系统 (FIS) 的多标准决策对来自西班牙不同大学的 1912 名学生的样本。我们看到了所研究的三个变量与留下的意图之间的关系。总之，理解大学辍学现象并没有单一变量，而是在一个整体模型中相互作用的几个变量。