Generating adaptive learning paths in e-learning environments
Irma Gámez Suazo, César Garita Rodríguez, Mario Peña Chacón · 2012
This work proposes an adaptive system using Bayesian networks to generate learning activities for students based on their course performance evaluation. Different learning activities are combined into learning paths in order to reinforce student knowledge on specific course contents. The proposed system was used in a b-learning course offered at the Computer Science School of Instituto Tecnológico de Costa Rica (TEC). For this purpose, a prototype was developed and integrated with TEC e-learning platform - TEC Digital. Test results indicate that Bayesian networks are an adequate adaptive mechanism for generation of learning paths in this context.