Work

Data analytics and Artificial Neural Network framework to profile academic success: case study

Year: 2024

Type: article

Abstract: Academic success in higher education has attracted interest from the scientific community because of its implications for personal development and societal progress. Programmes such as Tecnologico de Monterrey’s Leaders of Tomorrow aim to nurture students’ potential and promote academic success. This study examines the attributes from participating students associated with academic success. The focus is on personality and socio-demographic factors that influence academic excellence. The research contribution of this work is data analysis supported by artificial neural networks to establish the relationship between personality tests and background information with academic performance. The findings were: (a) high school GPA predicts university success; (b) first-generation degree status is associated with higher GPA; (c) gender differences in academic performance vary by context; and (d) personality profiles are not associated with academic performance. The role of socio-demographic and personality factors in predicting the academic success of prospective students is discussed.

Source: Cogent Education

DOI: 10.1080/2331186x.2024.2433807

Authors: Lorena Quintero-Gámez, Rasikh Tariq, Pedro Sánchez-Escobedo, Jorge Sanabria-Z

Institutions: Tecnológico de Monterrey, Autonomous University of Yucatán

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,165