Applying the genetic encoded conceptual graph to grouping learning

Abstract

The continual development of information technology in recent years has ensured its increasingly widespread use in many domains. Recent developments pertaining to the Internet and in computer technology have resulted in e-learning—a pedagogy that is free from time and space constraints. The issues of helping learners to study efficiently through lecturing procedures and using learning systems are now becoming increasingly important. Learning strategy based on a combination of the concept graphs learning system and cooperative learning is an important trend in computer and network aided instructions. The first step in cooperative learning activities is to divide learners into groups. This study proposes a grouping strategy to divide learning activities into several phases. The concept graph diagnostic system is adopted to assess learners’ learned concept nodes after each learning phase. The results of the assessment are encoded to learning genes and used to calculate the group complementary score. The genetic algorithm is used to group the learners into learning groups according to the group complementary score.