Dropout. How to effectively minimize the phenomenon of dropping out of university studies?

OECD research indicates that 30% of students do not complete their chosen course before obtaining a diploma. While this phenomenon is not new and has been present in the education sector for many years, it has become a significant problem given the declining overall student population. Universities are finding it increasingly difficult to fill abandoned courses with new candidates, which has serious consequences. Therefore, combating dropouts is crucial, and thanks to new technologies and AI, th

Dropout refers to a situation in which a student withdraws from their studies before completing them and can occur at any time after entering a university. Its scale and causes vary depending on the region, university, field of study, and the student themselves, who may decide to do so based on various factors. While it doesn't always mean abandoning their studies altogether, but rather a change of university, specialization, or deferment of studies, for the institution losing a student, it means a lower completion rate, financial losses, and reputational damage.

Individual diagnosis of the situation at the university

The biggest challenge in combating dropouts isn't a lack of knowledge about their causes, as numerous and reliable studies provide these. It's the relatively early acquisition of information about their occurrence at a given university and their relationship to a specific student. The goal is to predict and respond appropriately to the cause to prevent them from withdrawing from their studies. This is possible by monitoring and analyzing the status of each student, taking into account data collected from multiple sources. A specially designed dropout monitoring application, along with a mentoring support module for students at risk, helps achieve this. It continuously monitors the likelihood of the phenomenon occurring, and if it does occur, alerts students and suggests appropriate preventative measures. It then monitors and reports the effects of implemented initiatives. What does this look like in practice?

The application interfaces with university systems (e.g., the dean's office, attendance monitoring, library, e-learning, and many others), from which it retrieves data about students from the moment they are accepted to the program and throughout their studies. Based on strictly defined criteria, artificial intelligence algorithms analyze this information and present it in the form of easy-to-interpret statistics. Based on these data, the coordinator verifies that a given student is at risk of dropping out and can recommend specific actions to prevent them from withdrawing from their studies. For example, if it turns out that a student has stopped attending classes or their grade point average has dropped, a solution could be an individualized curriculum or remote learning using an e-learning platform. After implementing corrective measures, the student's status is still monitored to realistically assess the final impact of the initiatives taken.

This is a comprehensive approach to the problem of drop out, as it not only helps diagnose the causes of this phenomenon at a given university, but also highlights them in the context of individual students, providing the possibility of real prevention. This new technology is thus becoming an effective tool for universities in combating the long-standing, and recently increasing, phenomenon of dropping out.

Grants for investments in the fight against dop out

Given the growing dropout, universities have been given the opportunity to fund projects and implement solutions designed to prevent students from interrupting their education. The National Center for Research and Development has announced the "Effective University Management to Minimize Dropout, FERS 1.05" competition, which provides PLN 194 million in funding. The maximum value of a single project is PLN 5 million, and universities can apply independently or in collaboration with another higher education institution. The application process has already begun, and the deadline for submitting applications is January 31, 2025. This makes it all the more worthwhile to consider available opportunities and technologies that will provide universities with the necessary tools to minimize the risk of early school leaving.

This involves both the ability to efficiently diagnose dropout factors and effectively eliminate them. Therefore, in addition to analytical applications for prediction, solutions that align with preventive initiatives will be useful, such as e-learning platforms enabling remote learning, virtual assistants facilitating communication, multi-portal platforms for communication management, subject-specific websites for implementing e-services, academic career services systems that help build students' professional competencies, survey systems enabling satisfaction surveys, and many other tools dedicated to higher education. Effective verification of student status at the university is the starting point in combating dropouts, but well-organized corrective actions are an integral part of this.

Disturbing drop-out statistics

Dropout is a global problem and has been presented as such in numerous studies, which highlight a certain trend visible in the higher education market. An analysis by experts from the Information Processing Center (OPI PIB), based on data from the POL-on system, indicates that the dropout rate between 2012 and 2020 is estimated at 40%. This conclusion seems to be confirmed by a report by the OPI PIB Statistical Analysis Laboratory, which indicates that most dropouts occur within the first year of enrollment, and nearly two-thirds of these individuals decide not to continue their education in higher education. Referring to the detailed data from the OPI report, we can conclude that men are more likely to drop out of college than women. The dropout tendency is greater in part-time programs (54%) than full-time programs (32%), and in fields that are easily accessible and require less financial resources. These are just a few examples, likely well-known to the academic community.

These and other studies undoubtedly provide a thorough analysis of the dropout phenomenon. They identify its main causes and the areas most affected, thus providing a better understanding. However, although the authors approached the topic insightfully and comprehensively, they presented it in the context of the entire higher education sector. Unfortunately, this general approach is insufficient for universities. To minimize the dropout phenomenon, each higher education institution must consider it individually, focusing not so much on a representative group of students, but on each individual student. This is difficult to achieve without dedicated tools.

Comprehensive and long-term actions

Dropout is a problem with complex causes and serious consequences. It stems from individual factors, such as lack of motivation, financial problems, difficulties adapting to new situations, or finding a job, as well as institutional factors related to the university's administrative and educational operations. Furthermore, there are social factors that influence students' decisions to continue or terminate their higher education. This multifaceted nature of this problematic phenomenon requires a completely new approach, both in terms of methodology and technology, which together can effectively counteract the growing trend of dropping out. Preventing dropout involves a series of long-term actions that take into account the diversity of students' needs and situations within the context of a given university's services. Investments in support tools and innovative approaches to academic education can not only reduce the incidence of this phenomenon but also contribute to building a more inclusive and effective higher education system.


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