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An adaptive virtual reality game for programming education using fuzzy cognitive maps and pedagogical models

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Publicado en:Smart Learning Environments vol. 12, no. 1 (Dec 2025), p. 62
Autor principal: Marougkas, Andreas
Otros Autores: Troussas, Christos, Krouska, Akrivi, Sgouropoulou, Cleo
Publicado:
Springer Nature B.V.
Materias:
Sony Computer Entertainment America Inc
Students
Computer & video games
Educational technology
Learning management systems
Virtual reality
Flow theory
Online instruction
Technology Acceptance Model
Real time
Education
Flow mapping
Computer programming
Pedagogy
Feedback
Skills
Learning
Artificial intelligence
Educational objectives
Cognitive models
Literature reviews
Customization
Cognitive maps
Gamification
Adaptive learning
Computer Simulation
Curriculum Development
Environment
Cognitive Processes
Academic Achievement
Coding
Instructional Effectiveness
Fundamental Concepts
Autism Spectrum Disorders
Constructivism (Learning)
Educational Games
Educational Strategies
Competence
Influence of Technology
Distance Education
Educational Methods
Cognitive Style
Cognitive Mapping
Blended Learning
Creativity
Educational Experience
Educational Facilities Improvement
Acceso en línea:Citation/Abstract
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Resumen:Virtual Reality has proven to be highly promising within the field of learning. Most VR learning methods do not effectively implement pedagogical models or adapt to the individual's learning style. This research aims to bridge this gap by integrating Fuzzy Cognitive Maps (FCMs), Flow Theory and Gamification within an educational Virtual Reality video game to introduce and teach learners to Java programming. This new integration offers real-time accommodation to the learners' performance through dynamically balancing challenges and competencies (Flow Theory) and personalized, data-driven feedback (FCMs) and motivational stimulation through interactive gamified mechanisms (Gamification). With the use of FCMs to enable real-time personalization, this approach offers the ideal balance between competence and challenge to ensure deeper understanding of the subject matter. A comprehensive analysis verified significant improvements to the task performance, knowledge outcomes, along with the reduction of errors, validating the effectiveness of this adaptive VR method. The future of a more efficient and adaptive learning VR is made possible through this research that offers new knowledge about the integration of cognitive engagement, motivational aspects, and adaptive AI-powered learning.
ISSN:2196-7091
DOI:10.1186/s40561-025-00392-3
Fuente:Education Database