CONFERENCES
E&PDE 2026 - 28th International Conference on Engineering & Product Design Education
The Conference will bring together representatives from education and industry interested in sharing new perspectives on design education.
Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
AI-ENHANCED GAMIFICATION IN ERP SIMULATION: THE MXREP AND VIRTUAL PLANT APPROACH
Gonzalez Almaguer, Carlos Alberto; Berglund, Anders; Saavedra Gastelum, Veronica; Frias Reid, Natalia; Rivera Aguirre, Anna Sofia; Cervantes Pérez, Leonardo; Pacheco Hernández, Rommel
Type:
Year:
2026
Editor:
Buck, Lyndon; Brisco. Ross; Bohemia, Erik
Author:
Gonzalez Almaguer, Carlos Alberto; Berglund, Anders; Saavedra Gastelum, Veronica; Frias Reid, Natalia; Rivera Aguirre, Anna Sofia; Cervantes Pérez, Leonardo; Pacheco Hernández, Rommel
Series:
E&PDE
Institution:
Tecnologico de Monterrey; Mälardalen University
Page(s):
487 - 492
DOI number:
ISBN:
978-1-912254-24-8
ISSN:
3005-4753
Abstract:
The growth of Artificial Intelligence (AI) has profoundly impacted educational innovation, particularly in refining the teaching of complex, integrated industrial concepts such as Enterprise Resource Planning (ERP) and supply chain dynamics, which typically demand extensive practical experience. To address these pedagogical challenges, researchers from Tecnológico de Monterrey and Mälardalen University collaborated to integrate AI into gamified educational simulations. Their joint methodology uses the MxREP ERP process simulator to model assembly processes within a fictional manufacturer. MxREP incorporates Virtual Reality (VR) and Augmented Reality (AR) modules—collectively referred to as the “Virtual Plant”—to capture rich, granular data on student behavior, including assembly sequences and task completion times. The collaboration’s core objective is to transform this simulation data into actionable learning intelligence. AI is leveraged for dual functions: predictive modeling, exemplified by refining demand-prediction algorithms and predicting quality failures, and providing a personalized learning experience. By analyzing student performance against expert models, the embedded AI provides adaptive feedback, suggesting optimal strategies and highlighting subtle signals that are often overlooked. Crucially, the system evaluates the application of disciplinary and transversal competencies during decision-making in real-world scenarios posed by instructors. In conclusion, the research validates that AI-enhanced gamification, coupled with the robust Virtual Plant simulation model, significantly improves undergraduate learning outcomes by transforming a passive tool into a dynamic, adaptive resource that bridges theoretical knowledge with the practical development of essential professional competencies.
Keywords:
