Gabriela Mancilla

Gabriela Mancilla


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 January 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
AOAurora Sanchez Ortiz
Aurora Sanchez Ortiz
CVCristian L Vidal-Silva
Cristian L Vidal-Silva
GMGabriela Mancilla
Gabriela Mancilla
MTMiguel Tupac-Yupanqui
Miguel Tupac-Yupanqui
JRJosé-Miguel Rubio
José-Miguel Rubio
People are increasingly open to using online education mainly to break the distance and time barriers of presential education. This type of education is sustainable at all levels, and its relevance has increased even more during the pandemic. Consequently, educational institutions are saving large volumes of data containing relevant information about their operations, but they do not know why students succeed or fail. The Knowledge Discovery in Databases (KDD) process could support this challenge by extracting innovative models to identify the main patterns and factors that could affect the success of their students in online education programs. This work uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to analyze data from the Distance Education Center of the Universidad Católica del Norte (DEC-UCN) from 2000 to 2018. CRISP-DM was chosen because it represents a proven process that integrates multiple methodologies to provide an effective meta-process for data knowledge projects. DEC-UCN is one of the first centers to implement online learning in Chile, and this study analyses 18,610 records in this period. The study applies data mining, the most critical KDD phase, to find hidden data patterns to identify the variables associated with students’ success in online learning (e-learning) programs. This study found that the main variables explaining student success in e-learning programs are age, gender, degree study, educational level, and locality.

1 December 2020 in Formación universitaria
Verified
Journal Article
Open access
PDF file
GMGabriela Mancilla
Gabriela Mancilla
PLPaola Leal-Gatica
Paola Leal-Gatica
AOAurora Sanchez Ortiz
Aurora Sanchez Ortiz
CVCristian L Vidal-Silva
Cristian L Vidal-Silva
Este estudio determina las variables asociadas al éxito de los estudiantes en programas con modalidad de aprendizaje en línea (e-learning). La minería de datos es una fase del descubrimiento de conocimiento en las bases de datos (KKD, por sus siglas en inglés) que corresponde a la aplicación de algoritmos para encontrar patrones ocultos en los datos. El método utilizado es basado en el modelo CRISP-DM (proceso cruzado estándar de la industria para la minería de datos) aplicado a los programas de e-learning impartidos por el Centro de Educación a Distancia de la Universidad Católica del Norte (CED-UCN) en Chile. La muestra utilizada fue de 18.610 sujetos participantes en dichos programas durante 19 años. Los resultados obtenidos indican que las variables que permiten explicar mejor el éxito de los alumnos en programas a distancia son edad, sexo, profesión, nivel de escolaridad y región. Se concluye que estos resultados contribuyen al entendimiento de los factores críticos en la educación a distancia.