Gudelis, Dangis

Sustainable development requires a holistic approach and calls for the update in environmental, security, economic and social life of our societies. Climate change and global ecological crises, conventional industry and business patterns, wars and social unrest, technological advancements and the rise of AI make universities worldwide rethink their role in the society. Universities need to be at the forefront for Agenda 2030, act as a catalyst and to help societies to find solutions to overcome SDG implementation gaps of binding commitments, enforcement mechanisms, and legal accountability. Traditionally centred on education and research, today universities have to focus on their social responsibility providing service to society by shifting from closed specialized knowledge hubs into experimentation and life-long learning, society problem solving, and placing greater emphasis on security, resilience and critical thinking.

This article examines the integration of artificial intelligence (AI) in the public sector, highlighting its transformative potential and associated challenges. AI has the capacity to revolutionize public admin- istration by enhancing service delivery, decision-making, and operational efficiency through advanced data analysis, predictive analytics, and automation. Despite these opportunities, the adoption of AI in government faces significant obstacles, including technical limitations, ethical concerns, legal constraints, and organizational resistance. Key issues such as data privacy, system security, algorithmic bias, and accountability for AI-driven decisions are explored. This study employs a theoretical framework based on literature analysis, document review, and value interpretation. The article also discusses the varying levels of AI deployment, from simple automation to fully autonomous systems, and the strategic approaches needed for successful implementation. The research objectives are to identify the principal challenges and opportunities associated with AI integration in public administration and to answer key questions regarding effective governance, ethical management, and policy formulation. The study also aims to contribute to both academic discourse and policy practice by proposing actionable recommendations for optimizing AI deployment in the public sector. It emphasizes the need for robust governance frameworks, ethical guidelines, and international cooperation to ensure AI technologies enhance public value while preserving trust and democratic principles. The findings underscore the importance of a balanced approach to AI integration, promoting innovation while safeguarding societal interests.

Aim. The aim of the study is to empirically assess the motivational structure of teachers working in Kalvarija municipality by analysing the relative importance of internal and external motivational factors. The study examines teachers’ priorities regarding working conditions, municipal support measures, and professional development opportunities, as well as their attitudes toward the application of generative artificial intelligence in pedagogical practice. Methods. A standardised questionnaire based on established motivation theories was used. The instrument consisted of 114 items covering sociodemographic characteristics, motivational factors, working conditions, recognition, professional development, and attitudes towards artificial intelligence. The survey was administered online in June 2025. Data from 86 teachers was analysed using descriptive statistics, non‑parametric tests, reliability analysis, and ranking methods. Results. The findings show that teachers’ motivation is primarily supported by opportunities for professional development, meaningful work, and recognition. According to Herzberg’s model, internal motivators were rated highest, whereas external hygiene factors such as job security and health insurance received lower evaluations. Ranking analyses revealed stable priority patterns (Kendall’s W = 0.31–0.56; Friedman p < 0.001). Conclusions. The results of the study indicate that teachers’ motivation in Kalvarija municipality is shaped by a combination of internal motivators and external hygiene factors. Job satisfaction and professional involvement are most strongly supported by opportunities for professional development, recognition, and a clear sense of meaning in pedagogical work.

In the field of education, considerable attention is devoted to strategies for enhancing the attractiveness of careers within educational institutions. In Lithuania, demographic and economic shifts present significant challenges: the proportion of older teachers within the teaching workforce is steadily increasing, while a relatively small number of young individuals are entering the profession. Notably, fewer than 15% of graduates from initial teacher education programs pursue careers in teaching (Education and Training Monitoring Bulletin Lithuania, 2019). According to the Lithuanian Employment Service (2023), the need for preschool and primary education teachers, especially those who can work with students with special needs, is growing significantly, especially in South-West Lithuania. Mitchell (2020) emphasizes that the effectiveness of a school is closely linked to the nature of its community, which should be inclusive, collaborative, supportive—marked by positive interpersonal relationships—and oriented toward continuous learning and reflection. However, the current situation in Lithuania, characterized by a shortage of teachers and the low retention of young graduates in pedagogical careers, underscores the necessity of examining factors that influence school effectiveness. Such an examination is essential to understand the underlying causes of low teacher motivation and to develop strategies for enhancing it. Motivation is a well-established area of inquiry within contemporary psychology, management, and educational sciences. It is commonly defined as a complex interplay of beliefs and emotions that guide and influence human behaviour (Martin & Dowson, 2009), as well as the processes that initiate, sustain, and direct such behaviour (Sinclair, Dowson, & McInerney, 2006). This presentation outlines the findings of a teacher focus group grounded in the theoretical framework of Herzberg’s motivation-hygiene theory (Herzberg, 1968). According to this theory, job satisfaction arises primarily from intrinsic motivational factors—such as recognition and opportunities for advancement—whereas job dissatisfaction stems from extrinsic hygiene factors, including salary, working conditions, and administrative support, particularly when these are insufficiently addressed. The aim of this presentation is to analyse and discuss the results of focus group research investigating teacher motivation. Specifically, it seeks to identify effective motivational tools that support the retention of current teachers and enhance the appeal of the teaching profession to younger cohorts. The results of a focus group study with 80 graduates of the pedagogical study field in South-West Lithuania in June 2025 showed the following effective motivational measures for teachers: internal motivational factors (vocation, love for children, desire to feel needed) and external factors (increasing salary, financial and moral encouragement, improvement of working conditions, assistance in inclusive education, mentoring, etc.). The most effective factors are also noted as the emotional microclimate at school, conditioned by teamwork, formal and informal communication. The study revealed the incentive measures of the municipality and school leaders. Respondents identified negatively factors, what made effect on the prestige of pedagogical work in society.

The aim of the current research is to investigate the feasibility of identifying offensive language in Lithuanian by utilising the Simplified Offensive Language Taxonomy (SOLT). The key principle behind this taxonomy is its ability to complement existing offensive language ontologies and tagset systems, with the ultimate goal of integrating it into publicly accessible Linguistic Linked Open Data (LLOD) resources. The dataset used in the current study is a publicly available corpus of user-generated comments collected from a Lithuanian portal (Amilevičius et al. 2016). The study identified that offensive language predominantly focuses on collective derogatory language rather than individuals. The most common category of offensive language is related to physical and mental disabilities, followed by ideological offenses, xenophobic and sexist remarks, and less frequent categories like ageism, classism, homophobia, and religious discrimination. These results highlight the diverse range of offensive language online and underscore the need to combat discrimination and promote respectful discourse, particularly concerning marginalised groups.

The goal of the paper is to present a Simplified Offensive Language (SOL) Taxonomy, its application and testing in the Second Annotation Campaign conducted between March-May 2023 on four languages: English, Czech, Lithuanian, and Polish to be verified and located in LLOD. Making reference to the previous Offensive Language taxonomic models proposed mostly by the same COST Action Nexus Linguarum WG 4.1.1 team, the number and variety of the categories underwent the definitional revision, and the present typology was tested in the annotation on the publicly available offensive language datasets of each of the four languages. The results of the annotation are presented and as they are contained within the accepted statistical values on the inter-annotator agreement in the SOL categories and their aspects, we propose this taxonomy as a core ontology which represents the encoding of the supported offensive languages and justify its use on new data in terms of a more universal Linguistic Linked Open Data (LLOD) schema.

Research conducted on public administration in Lithuania covers various subjects related to different fields and activities within the public sector. However, most research focuses only on challenges associated with the civil service and local self-government in Lithuania. This research aims to define public administration research and improve understanding of the progress and trajectory of contemporary public sector research in Lithuania. The research methods include document analysis, qualitative descriptive approaches, and historical data analysis. Moreover, the triangulation method verifies research results by integrating data and observations from many sources. The research results found that in the development of public law in Lithuania, researchers in the field of Lithuanian public administration focused on the goals of government reform, civil service modernization, creative solutions, and trends and reforms in central and regional administration. They also concentrate on social policy procedures, improving public governance, and intelligent examination of public administration. Lithuanian authors also focus on improving public governance through the use of the concepts of cooperation, participation, and teamwork. The study of Lithuanian public administration is closely related to the evolution of traditional public administration, focusing on evaluating new public management practices and implementing various public management innovations in government sector organizations since the start of state restoration. Future directions of public administration research in Lithuania will focus on addressing the challenges faced by the public sector and society in other countries. These challenges include sustainable development, climate change, gender equality, and other contemporary issues that directly or indirectly impact the public sector.

Recently, there has been significant conversation surrounding the issue of a lack of teachers and the difficulties in retaining them. One question being asked is how to make teaching positions more appealing in order to attract educators. This is a concern in multiple countries, specifically in Lithuania, where there is a lack of educators in schools, and a higher proportion of older teachers compared to the European average (per Eurostat data). Although Lithuanian municipalities pay a monthly bonus of €300-500 in the first year and provide housing benefits to attract teachers, these measures do not sufficiently motivate teachers. The aim of this paper is tohighlight the measures that motivate teachers to work as teachersin relation tothe recognition of teachers' competence, communication and cooperation. The authors of the article conducted a study to find out what motivates teachers to do pedagogical work (Stasiukynas, Zemaitaityte, Gudelis, Zibeniene, 2020). The paper presents results of the part of this large study, which involved 873 teachers. In April and May of 2020, a survey of teachers in the city of Vilnius was conducted using the online survey platform Qualtrics. The research adhered to principles of ethical scientific conduct. Participants were given the freedom to participate and withdraw at any time, were informed of the study's purpose, data usage, and their anonymity was protected. The researchers also committed to upholding ethical standards and safeguarding participants from any potential harm. The survey data analysis showed that teachers considered working collaboratively with their peers within the educational institution as a crucial factor in motivating them in their teaching roles. Leisure time with colleagues in joint outings outside the educational institution and the opportunity to meet colleagues from different countries to share good practices were also highly rated by respondents. Reducing the administrative burden on teachers and protecting and safeguarding teachers' rights were also highlighted as important motivational factors. In order to retain already working teachers and attract new ones, teachers expressed the expectation that confidence in teachers' opinions and professional competence would be increased.