Expert system to Engage CHAEA learning styles, ACRA learning strategies and learning objects into an e-learning platform for higher education students

Abstract

The present work proposes to increase a student learning style on which he is weaker and to accelerate his learning process through a solution based on an expert system (ES) to engage CHAEA learning styles, ACRA learning strategies and learning objects (LO), into an e-learning platform for higher education students. The main expert system activity is to select a learning objects block that allows shaping a learning strategy and present this strategy in an e-learning platform, taking as a reference the CHAEA questionnaire. To develop our solution we use set theory and conceptual graphs (CG) for designing the knowledge base (KB) and the inference engine (IE), to solve learning objects interoperability we take the “Norma mexicana para la interoperabilidad entre entornos de objetos de aprendizaje”, finally we construct the learning strategy considering a previous work which recommends a block of ACRA learning tactics according to the CHAEA learning styles.