Research suggests that the combination of demographic, socioeconomic, cognitive, and non-cognitive factors may better explain and predict the intention to drop out of college.
Research has established that college dropout is strongly associated with factors such as student university and preuniversity academic performance, socio-economic status, as well as institutional and student personal characteristics (Bowles & Krivoshey, 2014; Cabrera et al., 2006; García-Ros et al., 2019; Scheele, 2015; Torrado, 2012). Although students’ socio-demographic and academic performance characteristics continue to correlate with dropout, research suggests that the combination of demographic, socio-economic, cognitive, non-cognitive, and integration factors may better explain and predict intention to drop out of college (Davidson et al., 2009; Farruggia et al., 2018; García-Ros et al., 2019; Kyllonen, 2012; Lau, 2003; Lotkowski et al., 2004; Morelli et al., 2021; Myers, 2009; Robbins et al., 2004).
Figure 1
Combining Multiple Psychosocial and Study Skill Factors (PSFs) and Traditional Predictors to Predict Retention
Note. Own elaboration based on Robbins et al., 2004.
While college dropout has been widely described and analyzed in specialized literature, there are still multiple gaps to be addressed, mainly the predominance of studies based primarily on cognitive and socio-demographic data previously available in mostly selective tertiary institutions.
While college dropout has been widely described and analyzed in specialized literature, there are still multiple gaps to be addressed, mainly the predominance of studies based primarily on cognitive and socio-demographic data previously available in mostly selective tertiary institutions.
Researchers need to create theoretical models […] to determine the linkages between motivational, social, and institutional constructs within the context of academic preparation and performance.
Firstly, studies attempting to determine variables most influencing college dropout tend to coincide in their results because they are fundamentally based on student information available in institutional databases. Therefore, they constitute data-driven analyses, i. e., they are the product of applying statistical methods to large volumes of data already available in information systems, regardless of whether the theoretical reflection considers them to be relevant data related to the problem in question. Secondly, while research suggests that the combination of demographic, socio-economic, cognitive, and non-cognitive factors may better explain and predict the intention to drop out of college (Davidson et al., 2009; Farruggia et al., 2018; Lotkowski et al., 2004; Morelli et al., 2021; Myers, 2009; Robbins et al., 2004), there are no empirical studies on the relationship between psychosocial, non-cognitive variables and student retention in Chile. Thirdly, most of the studies on college dropout in Chile have been carried out in State-owned institutions (Celis et al., 2015; Henríquez & Escobar, 2016; Miranda & Guzmán, 2017; Navarrete et al., 2013; Soria-Barreto & Zúñiga-Jara, 2014), which in general have better retention rates than private universities.
Figure 2
First-year retention rates v/s type of university (2014 – 2022)
Note. Own elaboration based on data from Consejo Nacional de Educación, n.d.
