2nd International Conference on Education & Technology (EDUT 2024)

September 13- 14, 2024, Virtual Conference

Accepted Papers

Transformation of Printed Teaching Materials Into Digital Form

Natalia Hrkotáčová and Adriana Kičková, Department of Pedagogy, University of Constantine the Philosopher, Nitra, Slovakia


The study focuses on the identification of criteria for the transformation of printed teaching texts and materials into digital form. Based on the identified criteria, the goal is to upgrade the form of printed teaching texts, in accordance with the needs of education in the 21st century, into a digital form. In order to increase the level of competence of teacher students in the field of handling digital platforms, work with digital resources was included in a specific subject in their undergraduate preparation for higher education. The output of the study is a concrete demonstration of the transformation of printed content into digital form and the presentation of data of a group of students educated in the field of handling digital resources during their undergraduate training in a specific subject.


Education for the 21st century, digital learning materials, print learning materials, digitization, undergraduate training.

Leveraging Genai for on-demand Tutoring as a New Paradigm in Education

Maikel Leon, Department of Business Technology, Miami Herbert Business School, University of Miami, Florida, USA.


Traditional education often fails to provide personalized, immediate support to all students, leading to gaps in understanding and learning inequality. Generative Artificial Intelligence (GenAI) offers a scalable, cost-effective solution for on-demand tutoring, providing personalized, 24/7 support. This paper explores the application of GenAI as an on-demand tutoring system, addressing the critical need for personalized, immediate educational support. Using GenAI to create an on-demand tutoring system that offers personalized, real-time student support is vital to today’s academic needs. Crucial components of this approach include advanced natural language processing to understand and respond to student queries, machine learning algorithms to adapt to individual learning styles, and a scalable cloud-based infrastructure to ensure 24/7 availability. This approach’s expected scientific surplus value lies in its potential to significantly enhance educational outcomes by providing scalable, personalized learning experiences. This paper outlines a pathway for future research and development in this area, highlighting the potential of GenAI to revolutionize education and improve learning outcomes for all students.


Generative AI, On-Demand Tutoring, and Education.