Technological convergence in education: meaningful learning, neural networks, and metaverse

This study investigated the convergence between meaningful learning, artificial neural networks, and the metaverse in 21st century education. The main objective was to understand how this convergence affected the educational experience. The mixed-approach methodology combined qualitative and quantitative methods. Surveys, interviews, and content analysis were employed, addressing 497 undergraduate students. The results revealed a high familiarity with the technologies analyzed and a positive correlation between active participation in virtual environments and meaningful learning. Factors such as technological accessibility and the quality of social interaction significantly influenced the effectiveness of technological convergence. Variability in technology adoption highlighted the need for contextualized strategies, and student concerns emphasized the importance of balancing technology with human interaction. Conclusions highlighted the importance of participation and engagement in educational strategies, the need for ongoing teacher training, and the importance of adapting technological implementation to disciplinary diversity.

• Автор: Ruiz Muñoz, Geovanny Francisco (author)
• Формат: article
• Мова: spa
• Опубліковано: 2025
• Предмети: aprendizaje significativo; redes neuronales artificiales; metaverso; tecnologías educativas; meaningful learning; artificial neural networks; metaverse; educational technologies
• Онлайн доступ: https://revistas.uteq.edu.ec/index.php/csye/article/view/933