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• The Role of Artificial Intelligence in Research Support

  7-17

  Krisztián Hajdu

  Views:

  214

  The application of artificial intelligence (AI) in scientific research is becoming increasingly widespread, offering significant potential to enhance the efficiency of researcher work and improve the quality of research. This study examines the role of artificial intelligence in research, with particular attention to literature search and analysis (Tolner et al., 2023), data processing and evaluation (Bessenyei, 2020), and content generation (Szűts & Námesztovszki, 2023). Employing the method of hermeneutic analysis (Bos & Tarnai, 1999), we explore the opportunities that AI offers in these areas, while also presenting the associated challenges and ethical considerations. Our results demonstrate that AI can lead to significant time savings and increased efficiency, as well as aid in the discovery of complex patterns. However, it is important to consider the limitations of AI, such as the lack of deeper understanding, potential biases, and questions regarding the reliability of generated content. The study concludes that artificial intelligence does not replace the human researcher, but rather functions as a knowledge support tool (Z. Karvalics, 2024), the responsible and ethical application of which is crucial to ensure scientific progress.

• AI-Based Autonomous Language Learning: Reality or Utopia?

  89-100

  Lili Sotkovszky

  Views:

  128

  In the literature, self-regulatory or autonomous learning is invariably defined using active, action-oriented verbs (e.g. direct, control, regulate), thus highlighting the importance of decision-making responsibility — a factor that results in a particularly complex process when it comes to language learning, as it involves both oral and written skill sets. Written and listening comprehension, speech production, written composition, grammatical knowledge, and vocabulary need to be practised. With the rise of AI-based learning support tools, many people feel that autonomous language learning is 100% feasible. In this paper, 19 studies are examined using the methods of hermeneutic analysis and critical discourse analysis to determine whether language learners are indeed ready for fully autonomous AI-based learning. In addition, the study will also seek to find out whether teachers are prepared to support this process with appropriate methods.

• Do We Need an AI History? : Historical Perspectives of Artificial Intelligence in Hungarian Digital Pedagogy Literature

  19-26

  Gábor Képes

  Views:

  209

  Is there a historical dimension to digital pedagogy? The evidence suggests yes! Is the IT historical aspect an immanent part of a digital pedagogical study on the use of artificial intelligence? This question is more complex to answer. A multifaceted theoretical analysis that approaches the studies from a bird's eye view reveals that knowledge of the historical background is essential for presenting even the most modern topics. We cannot look at artificial intelligence otherwise than as a product group of IT sciences that makes its user think: in what way and to what extent is it human, in what way and to what extent is it helpful, where are the limits of its artificiality. This study aims to prove, primarily by grasping at some of the helpful handholds of the rich methodology of hermeneutic reading, that without quality historiography there is no theory – and without the dialectic of theory and historicity– without this fertile duality – there is no practically usable science supporting education. The Hungarian digital pedagogical literature is a diverse repository of the use of the historical aspect – and our analysis also reveals that AI does not have a unified history so much as „stories”. Traditions without which the current tendencies would be incomprehensible.