This work investigates the automatic evaluation of open-ended questions, the challenge of which is how to deal with natural language data. This opens up opportunities to explore Intended Learning Outcomes (ILO) more broadly. It is particularly beneficial for MOOCs, given the general lack of an instructor. We use Named Entity Recognition (NER), an NLP (natural language processing) approach, anchored in Bloom's taxonomy with rubrics. A pilot test of a recently developed MOOC at LUT University in Finland was used as a case study. A total of 107 student responses were analyzed, with hit rates generally above 95%. Examples of using the NER system for student feedback in an adaptive learning environment are shown. Personalized pathways improve student learning and engagement, which also benefits MOOC completion.

We aim to test the hypothesis that delivering empathy & challenges to adult learners can boost their enthusiasm and academic performance, creating a supportive and enriching learning environment. Preliminary findings show that negative recommendations of the module (evaluation with 0) are related to the facilitator's attitude and skills (theme domain, teaching skills, attention to the needs of the students), course requirements, and expectations (relevance of the content, alignment with learner expectations, applicability to professional life) and technical and logistical aspects (technical issues during sessions, use of digital tools). The findings of this study are expected to contribute significantly to the existing literature on adult education by shedding light on the most valued aspects of continuing education programs, as perceived by the participants. Furthermore, the study will generate recommendations for effective group management based on the principles of the ZPD & Flow theories. By doing so, the study aims to provide practical insights to educators and policymakers and develop more empathy, which can help them design and implement more effective continuing education programs that cater to the needs and aspirations of adult learners.

This paper is part of a research project on the transition to higher education in basic mathematics courses and identifying factors that ease this transition. At the University of Tartu, we offered calculus courses for first-year students from the science and technology faculties in their first semester. Many students drop out of these courses in the first half or fail despite their best efforts. To better understand the reasons behind this issue, we created a questionnaire and asked students to complete it at the end of each course over two years. A total of 684 students responded. This paper analyzes their feedback to examine their difficulties transitioning from secondary to tertiary mathematics, how quickly they adjust to the course, how this adjustment affects their grades, the topics they find challenging to understand, and the materials they use the most. The main goal is to simplify the transition and find more learning tools to help students understand difficult topics better.

Effective communication and teamwork skills are paramount, particularly in engineering fields where collaboration is essential. Educational approaches have evolved, moving from traditional lecture-based teaching to more active methods like Problem/Project-Based Learning (PBL), which simulates real-world challenges. Various strategies have emerged to enhance teamwork. Notably, the team formation process stands out as a crucial factor for fostering positive interdependence and individual accountability, especially in long-term projects.

The primary objective of this study is to investigate the implementation of problem-based learning (PBL) in higher education, with a particular focus on its effectiveness in improving student learning and outcomes using self-selected and Big Five Personality Traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) test groups.

PBL was implemented within the course "Manufacturing processes and logistics", involving 37 graduate students in the fall semester of 2022 and 2023. During the course, the students were tasked with preparing a sustainability plan for an existing company, cooperating in teams (4-6 members in a team). While in the fall of 2022, the teams were self-selected by students, in the fall of 2023 teams were created by a lecturer using the Big Five Personality Traits (OCEAN model) test to ensure a balanced team dynamic. The results of the study participants were compared based on the final grade. The final grade was formed from the grade of the group work, the grades of the group members, and the exam grade. In addition, feedback and opinions were collected from students about their experiences with both teams.

The results showed that the OCEAN teams formed in the fall of 2023 outperformed the self-selected teams of the previous year. Students on OCEAN teams had higher attendance rates and needed less time to work on a given task outside of the classroom. They reported that working in OCEAN teams facilitated improvements in social skills and individual responsibility. In addition, they expressed a heightened awareness of their own and their teammates' strengths and weaknesses, thereby more effectively understanding each member's role in the team.

OCEAN teams demonstrated improved performance with higher attendance and reduced study time, suggesting structured team formation enhances student engagement. Additionally, students in OCEAN teams noted enhanced social skills, individual responsibility, and awareness of team dynamics. This indicates the OCEAN approach fosters personal growth and accountability. Overall, the study underscores the effectiveness of structured team formation in boosting academic performance, and personal development in higher education, emphasizing the importance of collaborative learning environments.

The article summarises the experience of creating and implementing the software tools, methods and approach gained within the international project “V4 Educational Academic Portal for Integrating IT into Education”, EDUPORT (2022-2023), and provides new insights for using them. Educational software WPadV4 developed in the project (author S.Svetsky) proved to be a promising tool for creating educational packages for teachers automatically produced. The article analyses and prospects for the further implementation of the project results for the field of integrating AI into education. The idea is to use IT tools to make different kinds of learning packages for teachers’ support. The packages may contain a lot of patterns for solving mathematical problems with AI for searching, evaluation and comparison. These patterns may be reasonably used by teachers for selecting the proper learning tasks for students, comparing the learning results and evaluating the students’ performance. In the outcome of the study, the educational packages for teachers containing dozens of learning materials for solving mathematical tasks were built using the Chat GPT, Bing and Gemini. The proposed tool helps teachers select and evaluate the learning tasks according to the level of complexity, improve teaching methods and support the process of assessment.

KEYWORDS

AI, Learning Tools, Teachers, Mathematics, Evaluation.

Dual training is a particular form of primary education in Hungary, where students meet the University's requirements for their studies and complete the company's training programme by partnering with the institution. Students who achieve certain points in the central admission procedure and are admitted to the relevant NJE degree programme while successfully competing for a company can be dual students. The training is based on a combination of general theoretical knowledge acquired at the University and additional skills acquired in practice in the company. The effectiveness of the training can be assessed based on several criteria and indicators. For example, by examining students' non-cognitive skills, labour market expectations, students' self-reflection, student satisfaction, student motivation, and student drop-out. in the present study, dual education has been represented in a strategic partnership framework in which three partners work together over many years, the university, and the company. For this system to work effectively and satisfy the participants, continuous measurement and monitoring of all three actors is necessary. At John von Neumann University, dual training has been in place for more than ten years, during which time it has been examined in many aspects to determine how effectively the system works. The present research presents the experiences of the last ten years from the perspective of the actors involved, with a focus on the University. The university satisfaction relationship has been mapped, and the results have been used to make recommendations for further improvement.