Developing Algorithmic Thinking in the Hungarian Language Course – ICT and Chatbots in Teacher Education Cover Image

Developing Algorithmic Thinking in the Hungarian Language Course – ICT and Chatbots in Teacher Education
Developing Algorithmic Thinking in the Hungarian Language Course – ICT and Chatbots in Teacher Education

Author(s): Orsolya DŐRYNÉ ZÁBRÁDI, Szilvia PETZNÉ TÓTH, Bernadett Pápai, József REIDER, Judit Sipos
Subject(s): Language studies, Language and Literature Studies
Published by: Scientia Kiadó
Keywords: ICT; chatbot; algorithmic thinking; languages; lifelong; learning;

Summary/Abstract: Today, education, the teaching-learning process, is undergoing many changes. 21st-century skills increasingly emphasize the importance of collaboration, self-development, and lifelong learning. In addition, new information and communication technologies are emerging, and the potential for using artificial intelligence in education is growing. Open-ended questioning is also coming to the fore as one of the modern theories of learning and teaching. The information gained through self-construction helps to develop one’s own appropriate representations for deeper learning. The learner reorganizes his/ her own existing knowledge for understanding and learning. Linked to quality education as a sustainability guideline, we rethink our subjects year by year and use methodological and technical innovations to strengthen and enrich teaching-learning processes. In teacher training, we have combined the teaching of semantics and grammar (vocabulary, morphology, syntax) in the Hungarian language course with the development of algorithmic thinking in mathematics. This gives scope for integration between subjects and the theory of multiple intelligences. Furthermore, using modern technological advances and rethinking the traditional frontal, paper-based teaching, we redesigned our lessons based on the SAMR model, giving students the task of playing the role of a chatbot and creating flowcharts and mind maps using a computer application. After the theoretical introduction, students were introduced to the decision tree and how NLP-based chatbots work. Then, they were given two fictitious topics to choose from (making an appointment at school or at the study department), based on which, after defining the goals, they had to create the thinking algorithm, flowchart, and decision tree of the chatbots. A basic prerequisite for all these complex tasks is a thorough understanding of the structure of the language, which we wanted to illustrate with this course adaptation. The description and results of this experimental research, and within it the complex development, are summarized in this presentation and article.

  • Issue Year: 17/2025
  • Issue No: 2
  • Page Range: 67-87
  • Page Count: 20
  • Language: English
Toggle Accessibility Mode