This study develops and validates the Digital Transformation Management Scale to assess teachers’ perceptions of digital transformation in education. Findings reveal a three-factor structure with high reliability. The scale provides a valid tool for evaluating digital transformation management and supporting evidence-based practices.
his article analyses trends in Deaf education in Lithuania in relation to inclusive education policy, the provision of linguistic rights, and different types of educational settings. The aim of the study is to determine which educational environments Deaf students in Lithuania are educated in, how they evaluate educational conditions, and what their expectations are regarding these conditions. To achieve this aim, two interrelated methods were employed: secondary data analysis, which enabled the assessment of actual trends in Deaf education, and a quantitative survey revealing the attitudes of different groups of respondents. The findings indicate that Lithuanian Sign Language is a fundamental condition for Deaf students’ inclusion as well as for their social and academic development. It was found that the provision of sign language interpreting services alone is not sufficient to ensure full participation in the educational process, as it does not replace direct communication and may limit active student engagement. Differences between Deaf and hearing participants’ attitudes towards the role of Lithuanian Sign Language also emerged, potentially posing challenges for the implementation of inclusive education. The study highlights the need for systemic changes oriented towards the development of linguistically accessible and culturally inclusive educational environments, ensuring the use of Lithuanian Sign Language throughout the entire school community.
The COVID-19 pandemic posed unprecedented challenges to school leadership worldwide, requiring rapid adaptation and effective crisis management. This study examines the crisis response actions of school leaders (N = 226) in Lithuania, focusing on how they managed the immediate challenges posed by the pandemic. Drawing on qualitative data from a larger study, in this article, we analyse the principals’ and vice-principals’ educational decisions and actions through the lens of crisis management theory. For data analysis, the inductive version of thematic analysis was employed. The analysis of the research data revealed a central theme – Crisis management in schools during COVID-19, as well as six themes and each with two sub-themes. Study results show a dynamic and multifaceted response by school leaders, reflecting both immediate action and the evolution of strategies as the pandemic unfolded. The study results confirmed that school leaders made targeted and crisis-responsive management decisions to cope with the consequences of the challenging period. This research provides critical insights into the role of school leaders during crises.
The development of social skills in children with behavioral difficulties presents considerable challenges for both educators and parents. Social competence is crucial for a child’s future, as it fosters self- and social awareness, encourages positive self-expression, and promotes constructive interaction within the community. Acquired social skills shape adaptive and purposeful behavior that is recognized as appropriate by both the individual and other persons. Furthermore, social competence facilitates the achievement of personal goals. Children with behavioral difficulties often lack these essential skills, which limit their ability to make appropriate behavioral choices and engage in socially acceptable conduct. The aim of the study is to evaluate the impact of participation in a physical activity group on the development of social skills in children with behavioral difficulties. The study revealed that, although school communities recognize their responsibility to support the social development of children with behavioral challenges, current programs are often inconsistent short-term and fail to engage the majority of students. Participation in a structured physical activity group provides opportunities for individualized observation and creates a supportive environment for social skill development. A systematic, consistent physical activity group is an excellent practice for developing social skills in children with behavioral difficulties, such as their relationship with themselves, others, and with activities. It’s an opportunity for these children to fully integrate into the community as well.
The paper presents the experience of a family with an autistic child as a case study, highlighting the challenges and best practices of interdisciplinary assistance. The study is based on qualitative narrative methodology and an ecological systematic theoretical approach. Data were collected using interviews and analyzed by combining an ecological systematic analysis approach with Barkhuizen’s (2020) narrative space analysis and Braun and Clarke’s (2006; 2013) inductive thematic analysis. The results of the study show that when a child is diagnosed with autism spectrum disorder (ASD), the family experiences complex emotions, ranging from shock to acceptance of the child, clarification of expectations, and the search for strategies for coping with everyday experiences. The dilemma of choosing a school emerges in this context. The family’s success is determined by daily communication with the school, the role of a student assistant, an appropriate classroom microclimate, and the support of the school community. The study emphasized the limited availability of public services, fragmented educational assistance, and a lack of support specialists. Also, the study highlighted the need for and importance of case management to ensure appropriate and accessible interdisciplinary and interinstitutional assistance for autistic children and their families.
The study aims to identify the areas in which Lithuanian learners use generative artificial intelligence (GenAI) tools across different educational institutions (universities, colleges, and vocational schools) and to assess the relationship between these areas of use and learners’ ethical awareness in terms of plagiarism, privacy, and misinformation. To achieve this goal, a literature review was conducted, and an empirical quantitative study was carried out among 803 learners from various educational institutions in Lithuania. The study examined the relationship between the use of GenAI for academic purposes and learners’ ethical awareness. The results revealed that most respondents use GenAI primarily for information search and learning, while fewer apply it for writing assignments or research activities. A positive association was identified between more active use of GenAI and higher levels of ethical awareness. The highest level of ethical awareness was observed among university students, while the lowest was found among vocational school respondents. These findings highlight the need to strengthen GenAI ethics guidelines and promote academic integrity.
The article presents a qualitative study that investigates the real in-class collaboration experiences of speech and language therapists and classroom teachers and reveals the possibilities and challenges of applying co-teaching strategies to support the inclusion of students with speech and language disorders in six different schools across five municipalities in Lithuania. Semi-structured interviews were used for data collection. The data were analysed using thematic analysis, following the methodology of Braun and Clarke (2006, 2021) and adapted for the interpretation of qualitative data. The study involved 12 participants who met the established selection criteria – 6 speech and language therapists and 6 classroom teachers working in pairs in mainstream classrooms and applying co-teaching strategies. The study identified a positive impact of the strategy on the personal and professional growth of educators, on learners, and on the institution: personal and teamwork competencies improve; the inclusion of students with speech and language disorders increases; and a culture of inclusive education is fostered within the school community. However, challenges arise due to insufficient teacher competence in applying the strategy in practice, limited support from school leadership, and a lack of necessary resources (e.g., an adequate number of specialists).
This study examines the DIY makerspace at the National Library of Lithuania through staff interviews and activity observations. The results show that the makerspace supports children’s creativity, autonomy, and practical skills through maker-centred, social constructivist learning. Furthermore, it emphasizes fostering children’s identities as makers, reinforces family and social bonds through social interactions and embodies the cultural tradition of self-reliance, a heritage of Lithuanian society.
Traditionally, early-stage non-formal music education with melodic percussion instruments has relied almost exclusively on the two-mallet technique, especially when introducing young learners to the vibraphone. The aim of this paper is to assess the impact of introducing the four-mallet technique in early non-formal music education by comparing its effectiveness to the traditional two-mallet approach among young vibraphone students. This study represents the first quasi-experimental research in this area.
Goals: The paper compares texts created by GPT models trained on the works of prominent Czech authors and the pieces of literature they actually wrote. The goal is to find out (1) whether there are any differences between the two; and if so, (2) in what sphere of language these differences are the most prominent. Methods: The authors used for building GPTs are Karel Čapek, Jaroslav Hašek, Franz Kafka, and Vladislav Vančura. The corpus contains 40 1,000-word text samples per each, 20 of them produced by the respective GPT and 20 taken from the original works. Two investigations are carried out – the first includes calculating 30 morphological, syntactic, and lexical markers for each text; the second is based on most-frequent-element analyses. The results of the first set are tested on statistical significance via Mann–Whitney U Test. Results: The chatbots do not reflect colloquiality of style and conversation interaction very well, and tend to make texts more narrative. The best results are obtained for Karel Čapek, the worst for Franz Kafka. The stylometric analyses almost always distinguish the AI- and human-generated pieces of language. Conclusions: The texts produced by the author-trained GPTs are still very well distinguishable from those produced by real writers.
Objectives: This study examines how contemporary generative language models can support archival and historical work with Czech handwritten texts, focusing on transcription and basic preliminary analysis, and it outlines key limitations and ethical implications for educational use in archival science and digital humanities. Methods: A qualitative case study was conducted using seven modern personal handwritten Czech texts from the 1980s and 1990s (a poem written by a child, love poems, a school test, and study notes). Three widely available tools in their free versions (ChatGPT, Claude, and Copilot) were tested using identical task instructions. Outputs were comparatively evaluated with regard to transcription accuracy, content and stylistic interpretation, and recognition of selected formal features of the texts. The empirical comparison was complemented by a critical review of relevant scholarly literature and reflection on authenticity, data integrity, epistemic security, and personal data protection. Results: Claude achieved the best overall performance, followed by ChatGPT, while Copilot produced substantially weaker results in the tested tasks. Across tools, interpretation and analysis proved more challenging than transcription, and outputs included errors and over-interpretations that require expert verification. Conclusions: Generative language models can function as supportive tools for transcription, preliminary analysis, and didactic work, but they cannot replace professional archival or historical expertise. Responsible use requires critical human supervision and explicit attention to ethical and data-protection considerations.
The study explores and highlights the direct relationship between contemporary knowledge, paradigms, aims, and public expectations in the field of artificial intelligence (AI) and its definitions. For the purpose of this research, the division of the stages of the development of AI was used for analogies to the seasons; spring to winter of AI. The history of AI is covered here only in the range necessary to point out this relationship with the possibilities of deriving the resulting definitions. Examples of period-typical AI definitions are given for each period. This historical excursion is then used as a background for thinking about the form (not the content) of the definition of AI that is appropriate to the current state of the field and its paradigm, focus, and use. The current discussion on the shape of the definition of AI within the framework of EU legislation is outlined. The form of a suitable definition of AI for the present is examined from the perspective of interested parties, such as multinational entities, business organisations, and other stakeholders, and is compared with some already valid definitions of these entities. A paradox in the definitions of AI, which are always too “narrow and broad at the same time” from a certain point of view, is pointed out. Finally, the possibility of deploying a fractal defi nition with a fixed rational-moral core but changing content with respect to the levels at which it is applied is explored within a conceptual ideation. This operational fractal definition could, in principle, resolve the ever-present “broadness-narrowness” paradox.
Článek se zabývá omezeními umělé inteligence při řešení klasických logických úloh, konkrétně úloh „Vlk, koza a zelí“ a „O třech kanibalech a třech misionářích“, včetně její modifikace „O čtyřech kanibalech a čtyřech misionářích“. Následně je analyzována schopnost jazykového modelu ChatGPT vyřešit tyto úlohy a jsou zdůrazněny obtíže, které AI má při dodržování logických pravidel a strategií. V analogii k těmto obtížím je zmíněn tzv. „Argument čínského pokoje“, který ilustruje limity algoritmických přístupů k problémům, které vyžadují hlubší porozumění a strategické myšlení. Na závěr je konstatováno, že přestože má AI s některými složitějšími logickými úlohami problémy, může být velmi efektivně využita pro zpracování a analýzu velkých objemů data.
This study investigates the impact of AI-generated songs on vocabulary acquisition and learner motivation in foreign language education. Conducted at a secondary vocational school in Prague, the research involved learners of German as a second foreign language from the third-year classes. Using a quasi-experimental design with 60 observations – 30 in the experimental conditions and 30 in the control conditions – the study compared conventional vocabulary learning methods with an innovative approach involving the AI music platform Suno. In the experimental conditions, the learners achieved a significantly higher mean post-test score (6.2) compared to the control conditions (4.2), with a statistically significant difference confirmed at p < 0.001 and a large effect size (Cohen’s d > 0.8). The survey data revealed that the learners preferred the song-based activity, citing increased engagement and enjoyment. These findings suggest that AI-generated songs can significantly enhance both vocabulary retention and student motivation, particularly in contexts requiring the acquisition of specialised terminology, which is often more challenging because of its complexity and the limited availability of learning resources.
This is a conference report summarizing a two-day international academic event titled GenAI in Higher Education: New Perspectives for Research and Teaching, held at the University of Warsaw in May 2025. The report addresses the central theme of generative artificial intelligence (GenAI) and its implications for higher education, focusing on teaching, research, academic integrity, and institutional policy. The text follows the structure of the conference, beginning with keynote speeches and debates that framed GenAI as both a promising and problematic innovation. It then outlines the content of parallel sessions, which explored ethical, pedagogical, institutional, and philosophical dimensions of GenAI. Particular attention is given to how students and researchers engage with GenAI tools, the challenges of authorship and originality, and the evolving role of educators. The report concludes by emphasizing the need for universities to move beyond superficial solutions and develop thoughtful strategies for responsible AI integration. It calls for future research into inclusive and ethical uses of GenAI in academic contexts.
Generative Artificial Intelligence (GenAI) poses major challenges for the field of education and so-called big language models are increasingly being applied in the work of education both in their pedagogical training and in their teaching. In our paper, we analyze how AI can be used to support the achievement of different types of cognitive goals defined within the framework of Bloom's taxonomy, which has been revised several times, while offering educators and researchers an overview of useful prompts that can be effectively used to support teaching, as well as to support students' classroom or home preparation (we specifically focus on the use of AI in language education). In doing so, we draw on concepts defined by researchers at Oregon State University, the SAMR model, and we also leverage our experience with the development and use of the Khanmigo AI application. We address both simple and complex AI prompt creation, the creation of personalized AI assistants, AI-enabled gamification, and other ways AI can be used to effectively support learning. We also focus on the requirements for constructing functional prompts – minimizing hallucinations or biases.
The educational landscape of K-12 classrooms is undergoing changes because of the emerging influence of Generative Artificial Intelligence (GenAI). The tools are driving educational transformation through personalised learning experiences, streamlined teacher workflows, and improved curriculum design, which is leading educators and policymakers to challenge conventional educational methods in the digital age. The rapid informal adoption of these technologies by students, teachers, and parents has accelerated urgent discussions on how K-12 education systems should respond. At the same time, meaningful integration of GenAI requires more than technological readiness. It relies on coherent national policies, high-quality teacher preparation, strong ethical principles, and equitable access to digital infrastructure. This study explores how four countries, namely the Czech Republic, Israel, Latvia, and Slovakia, are responding to these demands. Through a qualitative comparative approach, the paper identifies shared directions, country-specific challenges, and emerging opportunities. The findings highlight differing levels of preparedness and coordination and offer practical insights for policymakers, educators, and stakeholders working to support the responsible and inclusive adoption of GenAI in schools.
This text investigates how Generation Z art students are reconceptualising portraiture by exploring the fluid boundaries between nature, humanity, and machine using Artificial Intelligence (AI) and new media. Employing an art-based research methodology, the “Human Boundaries” project revealed that students value human error, imperfection, and fallibility as uniquely human traits that fuel creativity, distinguishing them from machines. The research demonstrates a shift in artistic focus, where AI is utilised not only as a technical tool but also as a co-creator and conversational partner, fostering critical thinking, planning, and interdisciplinary skills. The findings offer innovative didactic approaches for integrating AI into art education, promoting the development of essential soft skills that are relevant across various disciplines.
This article critically examines the negative aspects of integrating generative artificial intelligence (AI) into education from pedagogical, philosophical and ethical perspectives. Although AI offers the potential for many benefits to enhance the effectiveness of teaching, it can also weaken the teacher-student relationship. The text highlights the negative consequences of using AI tools in pedagogy. The author emphasizes that the teacher should remain the key figure in teaching as a human and ethical mediator of the educational process. The article calls for a prudent and balanced use of AI in education, which should support, not replace, human interaction and creativity.
