Using Virtual Learning Environment Data for the Development of Institutional Educational Policies

Applied Sciences

Vinicius Faria Culmant Ramos¹  Cristian Cechinel¹  Virgínia Rodés Paragarino²  Carolina Rodríguez Enríquez³  Alén Perez Casas⁴  Emanuel Marques Queiroga⁵  Luciana Regina Bencke⁶ 

[1] Centro de Ciências, Tecnologias e Saúde (CTS), Universidade Federal de Santa Catarina, UFSC, Araranguá 88906072, Brazil;Comisión Sectorial de Enseñanza, Universidad de la República, Udelar, Montevideo 11200, Uruguay;Facultad de Enfermería, Universidad de la República, Udelar, Montevideo 11600, Uruguay;Facultad de Información y Comunicación, Universidad de la Republica, Udelar, Montevideo 11200, Uruguay;Instituto Federal do Rio Grande do Sul, IFSul, Pelotas 96015560, Brazil;Instituto de Informática, Universidade Federal do Rio Grande do Sul, UFGRS, Porto Alegre 91501970, Brazil;

关键词: classification;    educational strategies;    higher education;    learning analytics;   

DOI  :  10.3390/app11156811

来源: DOAJ

【 摘 要 】

This paper describes the application of Data Science and Educational Data Mining techniques to data from 4529 students, seeking to identify behavior patterns and generate early predictive models at the Universidad de la República del Uruguay. The paper describes the use of data from different sources (a Virtual Learning Environment, survey, and academic system) to generate predictive models and discover the most impactful variables linked to student success. The combination of different data sources demonstrated a high predictive power, achieving prediction rates with outstanding discrimination at the fourth week of a course. The analysis showed that students with more interactions inside the Virtual Learning Environment tended to have more success in their disciplines. The results also revealed some relevant attributes that influenced the students’ success, such as the number of subjects the student was enrolled in, the students’ mother’s education, and the students’ neighborhood. From the results emerged some institutional policies, such as the allocation of computational resources for the Virtual Learning Environment infrastructure and its widespread use, the development of tools for following the trajectory of students, and the detection of students at-risk of failure. The construction of an interdisciplinary exchange bridge between sociology, education, and data science is also a significant contribution to the academic community that may help in constructing university educational policies.

【 授权许可】

Unknown