Ontological model for intelligent assessment in collaborative environment based on serious games.

Autor: Rjiba, Ameny, Belcadhi, Lilia Cheniti, Kasperiuniene, Judita
Předmět:
Zdroj: Procedia Computer Science; 2024, Vol. 246, p3158-3167, 10p
Abstrakt: In today's collaborative learning environments, effective assessment plays an important role in assessing knowledge acquisition and fostering skill development. The integration of serious games adds an interactive and engaging dimension to these environments, offering opportunities for immersive learning experiences. This combination not only evaluates learners' progress but also enhances their engagement and motivation, contributing to more effective educational outcomes. This research proposes an innovative ontological model specifically designed for intelligent assessment scenarios with serious games in collaborative environments. Our research aims to enhance learning experiences and skill development by integrating artificial intelligence, education, and serious games. The suggested ontological model incorporates stealthy assessment methods, personalization, and adaptivity to accurately represent the dynamics of collaborative serious gaming. Our approach fills in the gaps in the research by integrating personalized instruction, stealth assessment, and adaptive gameplay in a collaborative environment. We validate the model to make sure it is accurate and consistent and to make sure there are no logical conflicts. This work creates paths for future research, focusing on intelligent assessment and collaborative learning within the context of educational serious games. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index