The arrival of artificial intelligence in education is not simply about adding another digital device or creating a separate subject, argued Szőke‑Milinte Enikő, an educational scientist, on the podcast “A nagy AI‑sztori.” The program’s regular expert guest, Aczél Petra, a communication researcher and professor at Széchenyi István Egyetem, joined the discussion. They said the key question is what we mean by learning in a world where a student can get a ready answer with a single prompt.
Szőke‑Milinte Enikő, head of the Pedagogy Department at Eszterházy Károly Katolikus Egyetem and program director of the Neveléstudományi Doktori Iskola, emphasized that AI is no longer a distant phenomenon: pupils, teachers, school leaders and families are increasingly encountering it in everyday life.
Where AI currently appears in Hungarian curricula and vocational training
The conversation noted that AI has already appeared in formal Hungarian education. Within the subject of digital culture there is a curricular unit dealing with artificial intelligence, and in principle the topic may appear in the curriculum from the age of ten. There were also vocational training pilots: an AI course was introduced first in sixty institutions, with plans for wider rollout.
However, Szőke‑Milinte questioned whether creating another separate subject is the right solution. Instead, she argued, digital technology and AI should be treated as a horizontal cultural change to be integrated into the pedagogy of existing subjects.
AI as a tool and method — not a replacement
Pedagogically, AI is an instrument and ideally a method. This means teacher education should do more than explain AI; it should demonstrate how to use it in concrete subject teaching. At the same time, traditional learning forms cannot be discarded: human learning practices have evolved over millennia, and cognition does not switch overnight to purely digital operation. In several countries initial enthusiasm for digital tools was later balanced by a return to notebooks and books.
Szőke‑Milinte said AI’s real value is when systems do not supply ready answers for the student, but rather engage in the process of knowing: asking questions, giving feedback, prompting, and supporting learning in a personalized way.
Personalized learning and access — risks and limits
One of AI’s major promises is personalized, adaptive learning: systems that monitor a student’s reactions, pose prompts, provide feedback and tailor support. The podcast referenced an experiment comparing a simple chatbot with a more socio‑emotionally advanced, active system; unsurprisingly, the latter performed better.
Yet Szőke‑Milinte pointed out practical limits: access to such systems is a matter of funding, which risks widening educational inequality. Students who already have good tools stand to gain more, while those without access may fall further behind.
The teacher’s role in the AI era: teaching how to question and verify
The guests stressed that AI does not make the teacher redundant, but transforms the role. Teachers now must not only transmit content but also teach students to ask good questions: what to ask AI, which questions advance understanding, and how to evaluate answers. A competent AI user can question, verify, doubt, place responses in context and interpret them — this, Szőke‑Milinte argued, is one of the highest levels of AI competence.
Assessment and exams: how to integrate AI?
Assessment poses delicate issues. Szőke‑Milinte did not rule out the possibility that AI could eventually be allowed in exams, similar to calculators, but stressed that it depends on how tasks are framed. One proposed approach is to require students to submit not only a final answer but also the full dialogue with the AI: which questions they asked, how they handled the responses, and how they arrived at their conclusions.
Conclusions
According to the podcast, AI can serve as a teacher’s aide, a method, a tool and a partner in thinking, but it cannot replace the internal work that makes learning real. The central task is a change in educational mindset: treat AI not as another standalone subject but as part of renewing teaching and learning, while safeguarding equitable access and preparing teachers methodologically.
Main segments of the conversation (timestamps)
- AI in schools: subject or mindset change? (05:38)
- The teacher’s role in the AI era (07:19)
- Why not everything can be digitized (10:21)
- Personalized learning and educational inequalities (16:54)
- Learning or ready answers? (22:22)
- Performance, assessment and AI use (24:05)
- What should not be delegated to AI? (28:12)
- Why knowledge is needed to use AI (34:26)
(The full episode of “A nagy AI‑sztori” is available for listening.)
