Future of Education on Pre-university Studies

被引:0
作者
Bezerra, Rita [1 ]
Lacerda, Beatriz [2 ]
Duraes, Dalila [2 ]
Novais, Paulo [2 ]
机构
[1] Polytech Cavado & Ave Inst, Barcelos, Portugal
[2] Univ Minho, Algorithm Ctr, LASI, Braga, Portugal
来源
TOWARDS A HYBRID, FLEXIBLE AND SOCIALLY ENGAGED HIGHER EDUCATION, VOL 2, ICL2023 | 2024年 / 900卷
关键词
Pre-university Education; Machine-Learning Models; Gender Prediction;
D O I
10.1007/978-3-031-52667-1_28
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
By incorporating technology into education, students' skills can be enhanced while still recognizing the importance of personal and social abilities. Therefore, it is crucial for pre-university education to prioritize the development of self-awareness, empathy, teamwork, and leadership skills. This will enable students to become more productive members of society and make positive contributions to the world at large. To explore the academic achievements of different courses and the subjects chosen by students before entering higher education, we analyzed a dataset containing student information. Our goal was to examine the relationship between these variables and other factors like gender, socioeconomic background, and parents' education. It is widely recognized that certain outcomes are influenced by gender and the selection of academic fields. As a result, there are academic programs that tend to be predominantly chosen by males, while others are preferred by females. To obtain predictive results, we employed machine learning algorithms that have proven successful in similar studies.
引用
收藏
页码:278 / 289
页数:12
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