This study seeks to investigate the relationship between dropout intent, the weekly work duration of student employees, and university social capital by analysing empirical evidence from three European countries, including Estonia, Lithuania, and Poland. This exploratory study utilised Eurostudent-VII survey data and employed cross-tabulation and exhaustive Chi-square Automatic Interaction Detection (CHAID) to achieve its objectives. Findings indicate that student employees who believe they get along well with their teachers and have more connections with fellow students to discuss subject-related issues are less likely to intend to drop out of university. In addition, the results show that students’ likelihood of abandoning their higher education increases in the presence of difficulties caused by an inapt academic programme. Regarding employment duration, for the Estonian and Lithuanian markets, there is no difference between working more than 20 hours per week or less than that with the intention of dropping out of university. In Poland, however, the disparity in working hours interacts with other factors related to social capital to explain dropout intent. These findings provide novel insights into the dropout literature by refreshing thoughts on the role of teacher-student and peer relations in the dropout intentions of student employees. In addition to reviving the relevance of university social capital, which has received too little attention lately, they have also sparked a recent debate on whether or not combining work and university actually affects the intention to drop out.

University students may encounter situations where they perform poorly in a course and contemplate dropping out. This intention to drop out of a course manifests not only in thoughts or ideas but also in a cognitive self-evaluation of their performance and skills, enabling them to reflect on the possibility of dropping out. In this sense, there is a shortage of instruments that evaluate the intention to drop out of a course, so the aim was to develop and validate the Course Dropout Intention Scale (CDIS). Data from two samples (N1 = 198; N2 = 675) were used; the first was for the EFA, and the second was for the CFA, GRM, and SEM. The one-factor model was derived from the EFA and confirmed in the second sample, exhibiting appropriate goodness-of-fit indices. Similarly, the GRM obtained adequate fit indices; all items discriminated adequately, and the difficulty parameter had a monotonic increase. The SEM model of the effect of satisfaction with studies on the CDIS showed a negative and statistically significant effect. Thus, it was demonstrated that the CDIS is a robust instrument in its psychometric properties and empirical evidence with other variables.

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.

University dropout is a multidimensional and multicausal problem that affects every university around the world. The aim of this article is to conduct a bibliometric review of the scientific literature on the main factors that influence university dropouts in scientific publications between 2018 and 2022. The methodology is based on systematic searches using the Web of Science (WoS) and Scopus databases. We analysed 417 and 498 articles, respectively, applying inclusion/exclusion criteria. The main factors of university dropout were identified: problems in the academic and social world of students, student stress, health reasons, the role of teachers, and changes in the education system. Among the countries with the highest scientific output, Spain stands out, along with the United States, the United Kingdom, Australia, and China. This would provide a more complete view of the historical evolution and multifactorial causes of this educational phenomenon.

The concept of student workload has become central in European university discourse through the implementation of the Bologna Process. Through the European Credit Transfer and Accumulation System (ECTS), it aims to standardize the measurement of student workload across European higher education. Scholars have highlighted limitations in this approach, particularly its inability to fully capture the complexities of student workload. Departing from such a response, we conducted a mixed-method case study, building our analysis on perspectives from Posthumanism and Actor-Network Theory, which offer a holistic and nuanced framework for understanding student workload. By conceptualising workload as a dynamic network of relational actants, this approach moves beyond previous conceptions. It also foregrounds the student as a complex individual whose agency is central to the construction of workload. Through this lens, student workload is not a fixed entity but a process of becoming, shaped by interactions both within and beyond the formal learning environment. Posthumanist perspectives thus allow for a richer understanding of the student as a whole person. This model provides valuable insights for institutional and educational discourse, as well as future research, highlighting the need for a more nuanced understanding of student workload.