This study examines how applicant profiles, prior experiences, and motiva-tion relate to admission decisions and early study persistence in informatics programs at Tallinn University of Technology (TalTech), Estonia (2020–2025). Drawing on Tinto’s integration model, Person–Environment Fit theo-ry, and Social Cognitive Career Theory, it analyzes how technical prepared-ness, institutional engagement, and self-efficacy shape enrollment and drop-out. The study combines qualitative content analysis of 168 applicant portfo-lios (2023–2025) with institutional enrollment and dropout data from 2020–2025, coding portfolios across five domains, including IT preparedness, en-gagement with TalTech, and extracurricular activities. Results show that prior engagement with the university, systematic IT experience, and bal-anced profiles combining technical and interpersonal competencies are the strongest predictors of both acceptance and persistence. The introduction of portfolio-based admissions was associated with reduced dropout by improv-ing alignment between applicants’ capabilities, motivations, and program expectations. At the same time, limited technical preparation and weak self-regulation increased the risk of withdrawal. Overall, the findings indicate that content-focused admissions can serve as an anti-dropout mechanism, with implications for equitable, data-informed admissions design in compu-ting education.

In the fast-evolving world of technology, is hard for education's system to keep the pace. The curricula for a 3-year study program is established at the enrolment of the students. After 3 years ,the students present their bachelor's thesis usually as an application with the topic related to what they studied and the expertise of the supervisor.

In order to observe the student’s approach to the topic of the bachelor thesis, we let the student to choose their own topic.

Nearly a quarter of the students from the promotion of 2025 volunteer to do their bachelor thesis in this way. The supervising was done in a laissez-faire manner. In the first semester, the communication with all 60 students was done via email exclusively. In the second semester, the supervisors organized one online meeting, two times a week.

Regarding the topics chosen by the students, we saw that there were topics that were not studied at the university, like applications using AI large language models or quantum computing technologies.

OpenAI launched ChatGPT in November 2022. In October 2022, the students began the university and finished in 2025. The curriculum of the study program did not contain any large language model topics. In this study we discovered that nearly 20% of the student implemented their bachelor thesis application that use a large language model (either hosted or using API).

The average grade for these students under our supervision was on the same level as the rest of the students.

By their choices, we see that students are more likely to tackle topics that go with the technology trends than remaining only by the supervisor’s proposals. Also, the students are willing to learn beyond university’s curricula in order to fulfill the market’s needs.

There are many myths surrounding women in IT, as well as the reasons for the lower representation of women compared to men. Several theories exist as to why women do not pursue studies in IT. For example, a common belief is that women are not interested in IT, that they are too afraid to study it, that people perceive it as a field for men, and that women are not considered intelligent enough to study it. Even though companies are expecting more women in IT, schools are reluctant to pursue female student candidates, as they fear that diversity will lower student quality and that an increase in women will result in lower timely graduation rates. The goal of this paper is to address some of these issues through the studies conducted among IT students at Tallinn University of Technology. Despite the growing emphasis on workplace diversity, higher education has been slower to respond to these biases. We aim to determine whether it is possible to identify gender-based differences in study motivation, entry pathways, and perceptions of study quality, and to translate these findings into institutional recommendations that can enhance women’s participation and success in IT education.

This paper is based on two institutional studies conducted at the Institute of Information Technology, Tallinn University of Technology (TalTech): a bachelor’s student survey carried out in autumn 2024 and a master’s student survey conducted in spring 2025. The surveys were designed to explore diversity and gender-related experiences among IT students, as well as to understand differences in study motivation, learning pathways, and perceptions of inclusion.

The surveys reveal clear gender- and study-level differences in students’ experiences and motivations in IT programs at Tallinn University of Technology. While both male and female students share a strong intrinsic motivation—namely, an interest in technology and problem-solving—their pathways into IT and perceptions of study quality differ notably.

The outcomes of the studies provide the basis for policy recommendations for TalTech as well as other IT institutions in Estonia and possibly elsewhere. The recommendations also take into account the broader Estonian educational context and existing research. The paper also seeks to align its insights with national and European gender equality policies in STEM education.

With software engineering courses taught in higher education gaining considerable ground in the past decade, teaching related ethical aspects has become an essential part of educating future software engineers. This short paper will be based on the experience of teaching a computer ethics course to a multicultural group of graduate computer science students. The paper will attempt to answer the following question: to what extent does culture influence ethical views of students in relation to different software development aspects?

Observations and conclusions will be drawn based on class reflection activities, questionnaires and empirical observations gathered during classes. The lessons learned during teaching this course can contribute to clarifying the relationship between cultural background and approaches to particular ethical aspects in software engineering. They can provide valuable guidance for future computer ethics classes, contributing to the essential education that future software engineers need.