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Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made during the Pandemic

Author

Listed:
  • Jorge Maluenda-Albornoz

    (Facultad de Psicología, Universidad San Sebastián, Sede Concepción, Concepción 4080871, Chile)

  • Valeria Infante-Villagrán

    (Programa de Doctorado en Psicología, Departamento de Psicología, Universidad de Concepción, Concepción 4070386, Chile)

  • Celia Galve-González

    (Departamento de Psicología, Universidad de Oviedo, 33003 Oviedo, Spain)

  • Gabriela Flores-Oyarzo

    (Investigadora Independiente, Concepción 4080871, Chile)

  • José Berríos-Riquelme

    (Departamento de Ciencias Sociales, Universidad de Tarapacá, Iquique 1113749, Chile)

Abstract

Social and academic integration variables have been shown to be relevant for the understanding of university dropout. However, there is less evidence regarding the influence of these variables on dropout intention, as well as the predictive models that explain their relationships. Improvements in this topic become relevant considering that dropout intention stands as a useful measure to anticipate and intervene this phenomenon. The objective of the present study was to evaluate a predictive model for university dropout intention that considers the relationships between social and academic variables during the first university semester of 2020. The research was conducted using a cross-sectional associative-predictive design, with a convenience sampling ( n = 711) due to the restrictions of the pandemic period. The results showed a good fit of the proposed hypothetical model that explained 38.7% of dropout intention. Both social support and perceived social isolation predicted the sense of belonging and, through it, engagement. Previous academic performance predicted early academic performance and, through it, engagement. The set of variables predicted the intention to quit through engagement. These results are a contribution both to the understanding of the phenomenon and to guide potential interventions in the early stages of the university experience.

Suggested Citation

  • Jorge Maluenda-Albornoz & Valeria Infante-Villagrán & Celia Galve-González & Gabriela Flores-Oyarzo & José Berríos-Riquelme, 2022. "Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made during the Pandemic," Sustainability, MDPI, vol. 14(2), pages 1-18, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:831-:d:722934
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    Citations

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    Cited by:

    1. Jack Vidal & Raquel Gilar-Corbi & Teresa Pozo-Rico & Juan-Luis Castejón & Tarquino Sánchez-Almeida, 2022. "Predictors of University Attrition: Looking for an Equitable and Sustainable Higher Education," Sustainability, MDPI, vol. 14(17), pages 1-27, September.
    2. Jorge Maluenda-Albornoz & José Berríos-Riquelme & Valeria Infante-Villagrán & Karla Lobos-Peña, 2022. "Perceived Social Support and Engagement in First-Year Students: The Mediating Role of Belonging during COVID-19," Sustainability, MDPI, vol. 15(1), pages 1-10, December.
    3. Miguel Angel Valles-Coral & Luis Salazar-Ramírez & Richard Injante & Edwin Augusto Hernandez-Torres & Juan Juárez-Díaz & Jorge Raul Navarro-Cabrera & Lloy Pinedo & Pierre Vidaurre-Rojas, 2022. "Density-Based Unsupervised Learning Algorithm to Categorize College Students into Dropout Risk Levels," Data, MDPI, vol. 7(11), pages 1-18, November.

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