Panel I.10 — The pervasive-persuasive relationship between education and technologies

Convenors Loredana Perla (Università degli Studi di Bari Aldo Moro, Italy); Marisa Michelini (Università degli Studi di Udine, Italy); Laura Agrati (Università degli Studi di Bergamo, Italy); Mariassunta Zanetti (Università degli Studi di Pavia, Italy); Alessia Scarinci (Università Mercatorum, Italy)

Keywords Teacher training; Artificial Intelligence (AI); physics research methodologies; Gamification;personalized learning


Increasing digitalisation has revolutionized approaches to education, with new multimedia and communication technologies becoming more and more integrated into teaching and learning processes. This integration is characterized by a double aspect: pervasiveness and persuasion.

Pervasiveness refers to the pervasive diffusion of technologies, which are becoming increasingly predominant in educational contexts, both physical and virtual. This change has been amplified by the pandemic, which has highlighted the need to design and manage technologically mediated learning environments.

On the other hand, persuasion means gaining approval and trust through a gradual and methodical process of convincing. In the educational context, it is important to ensure that the use of technologies is ethical and effective. The challenge lies in balancing the pervasive approach of technologies with the need to engage students in an ethical, responsible and motivating way.

In the context of this challenge, the advent of Artificial Intelligence (AI) represents a significant turning point in the global educational landscape. Rapid evolutions in AI are transforming and redefining education and instruction around the world. This development catalyzed a series of advances and innovations that have been influencing different aspects of human life. Among these, education has tangibly benefited from AI discoveries and implementation.

The integration of AI into education systems is currently rewriting how students learn, teachers deliver lessons and institutions operate. By personalizing learning experiences, automating administrative responsibilities, and providing real-time feedback, AI is revolutionizing the educational landscape. It is filling previously encountered gaps, encouraging a more inclusive and effective learning environment.

Given the profound implications of integrating AI into education, it is imperative to think carefully about its consequences. This involves cautious consideration of the challenges and opportunities emerging from this AI-driven educational revolution.

This panel aims to foster an informative and constructive discussion about the future of technology education and the impact of AI on learning. Experts and participants will share knowledge and research to identify best practices, address challenges related to the use of technologies and AI in education and reflect on the opportunities they offer. It aims to promote collaboration between academics, researchers and education professionals to proactively address challenges and create a more inclusive and effective learning environment.

Furthermore, the panel wants to start a debate between academics, researchers and school operators to explore the complex relationship between education and technologies. Some of the key topics of discussion are:

• Pervasiveness-persuasion in the relationship between education and technologies: opposition, complementarity, antitheticality;

• Hybrid environments as contexts in which the “necessary” and “sufficient” elements of educational relationships emerge;

• The epistemological role in physics research methodologies;

• Gamification and learning: persuasive use of technology;

• The role of technologies and AI as an object of reflection within the curricula of primary and secondary schools;

• Teacher training in technologies, on technologies, with technologies: exploring training programs for educators on the use of AI in teaching; what skills are necessary for the use of technologies and AI;

• Technologies and AI for personalized learning;

• Strategies and challenges in using AI to promote inclusion and equity in education.


Guidelines and abstracts submission