Generative artificial intelligence applications enriched with multimodal capabilities are underpinned by vast amounts of data—digital or digitized—computational power, and mathematically simulated neural networks operated through computing technologies. The combined presence of these factors produces a synergistic effect, enabling faster, more efficient, and potentially innovative processing, organization, and interpretation of information. Pattern recognition surpasses all previous scales and levels of accuracy, making it possible to automate and outsource mechanical tasks.
The user operation of large language models differs from earlier forms of information carriers, as they generate grammatically and conversationally appropriate responses to prompts. Owing to natural language processing, questions and instructions can also be effectively applied. Interactions–particularly in the case of chatbots–exhibit signs of apparent personality, and, together with their user-friendly design, provide an immersive experience. Generative AI systems write, speak, and engage in conversation, while also producing new content. This verbal mode of operation inevitably points toward anthropomorphization.
Communication networks and environments in education and research are now jointly shaped by human and machine agents, while a multitude of hybrid knowledge-production characteristics, processes, and interactions unfold. This is not a projection but a description of the current situation. The perspectives of development are difficult to foresee. All this entails numerous opportunities for knowledge production, knowledge transfer, and pedagogy, but also carries various cognitive, verification-related, psychological, mental, data security, and other risks.
Artificial intelligence not only supports and accelerates research processes but also lays the groundwork for new research questions and contributes to the emergence of new scientific paradigms. In the field of education, it enables personalized and experience-based learning while simultaneously influencing the relevant domains and refining the curriculum. At the same time, the acquisition and development of fundamental communicative and intellectual competences remain of paramount importance. Finding a balance that is human-centered and oriented toward human values becomes a key issue.
Educational and research methodologies must respond to these challenges. The AI-driven transformation is unfolding inexorably, and applications have already become part of everyday practices of accessing and processing information. Therefore, their conscious, goal-oriented, and effective implementation is essential.
These changes affect not only the processes of education and research but also the status of knowledge deemed worthy of acquisition and transmission. Novel and productive forms of human–machine co-thinking and collaboration are emerging. Identifying effective forms of cooperation requires scientific reflection, investigation, and the formulation of both theoretical and practical questions. This is the aim of the scientific conference organized by the Hungarian Language Teacher Training Faculty.
Given the interdisciplinary nature of the conference, we invite presentations in the following thematic areas (without claiming completeness):
– applications of artificial intelligence in education (with special regard to teacher and early childhood educator training)
– transformation of learning processes, teacher roles, and competences in AI environments
– generative AI and communication: media content production, language use, verification
– human–machine interaction and communication patterns
– the impact of AI on knowledge production and research methodologies
– development of digital and AI literacy
– ethical, psychological, and data security issues
– social and institutional impacts of AI in education
– curriculum development and instructional material design supported by AI
– transformation of assessment and evaluation methods in AI environments
– adaptive and personalized learning environments
– fostering critical thinking and media literacy in the age of AI.
Publication:
Abstracts of conference presentations are going to be published in a book of abstracts, while complete papers will be published in an e-book.
Conference fee:
Conference fee is 100 EUR (or the equivalent in Serbian dinar), which includes conference materials (book of abstracts, e-book) and catering. Upon payment, transfer expenses are to be covered by the applicant.
Conference registration:
Participants are invited to submit their e-applications which also include the title and abstract of their papers (no longer than 1000 characters) as well as (maximum 5) keywords in one of the conference languages (Hungarian, Serbian, Croatian, English).
REGISTRATION
We accept applications to July 15, 2026. After completed Google registration form https://forms.gle/4BsKNQtmdcc8yhfN7 the conference fee payment form should be sent to the e-mail: conf@magister.uns.ac.rs (we can only issue a pro forma invoice to institutions, individuals can only pay on the day of the conference at the Faculty)
It is possible to attend the conference as an observer. Please indicate by email which package you choose:
1. observer only (free of charge, but participation must be confirmed via email)
2. observer with lunch and dinner vouchers, conference package, and certificate of attendance (€50)
Deadlines:
Application: July 15, 2026
Sending conference fee payment forms: September 15, 2026
Conference fee payment: October 1, 2026
Conference November 26, 2026
Submitting full papers: November 15, 2026
