Abstract:

Even though the importance of education is increasingly recognized worldwide, as a significant factor of societal sustainable development and individual well-being, the phenomenon of academic dropping remains a constant concern for many educational institutions. Dropping out from higher education is particularly problematic, because it reduces the number of potentially highly productive individuals who can contribute to society after graduation. Similar to many complex phenomena, dropping out is also the result of a combination of factors, ranging from personal (e.g., attitudes, self-beliefs, goals) to institution-related (resources, instructor and administrative support, etc.). Therefore, many education institutions implement remedial actions, including preparatory and/or complementary support classes, aimed at students at risk of dropping out. However, to date, there is still a need for research that take comprehensive approaches to these possible risk factors, especially considering the increasing pressure placed on the teachers to maintain high graduation rates.

Against this backdrop, and based on the theoretical framework developed by Rumberger and Rotermund, our study’s research questions investigated whether the drop out intention is associated with the type of student (‘at-risk’ vs ‘not-at-risk’). We used an associative, one-time, cross-sectional research design, in which we conceptualized the drop-out intention as the outcome variable, and several individual and institutional factors as predictors. The latter included the type of motivation, the perceived usefulness of each type of resources, and the frequency of good and bad experiences in school contexts, and the overall satisfaction with the university. The study included N = 574 students (N_female = 429), with mean age M_age = 21.93, SD_age = 5.27, enrolled in undergraduate courses at The Technical University of Cluj-Napoca. Of these, N_(at-risk) = 201 were students considered ‘at-risk’ and, during the research, were included in remedial courses, including individual and collective tutoring activities. The students’ perceptions were collected during the first term of the academic year, via a web-form disseminated during courses. The respondents provided their answers to 7-step Likert scales, measuring agreement vs disagreement, on items inquiring into the main constructs.

We modeled the hypothesized relationships using partial least squares path modeling, based on a prior exploratory factor analysis. The model explained R^2 = 29% of the variance in drop-out intention, and indicated significant differences between ‘at-risk’ and ‘not-at-risk’ students, in terms of the importance of perceived support from the university, type of motivation, and overall satisfaction with the university. For instance, while the overall satisfaction with the university was a significant predictor of the drop-out intention for the ‘at-risk’ students (β = .31, p < 0.05), it wasn’t statistically significant for the ‘not-at-risk’ students. Our findings emphasize the crucial role of the institutional support, and the need to consider a comprehensive approach when investigating the academic dropping out. These findings also provide further empirical support to the theory and can be used by school administrators, educational strategists, and policy- and decision-makers, to better understand the students at risk of dropping out and guide their intervention and remedial programs.

Keywords:

Academic dropping out, partial least squares path modeling, higher education, remedial programs, academic underachievement.