Generating Intelligent Remedial Materials with Genetic Algorithms and Concept Maps

This study proposes an intelligent remedial learning framework to improve students’ effectiveness. Basically, this combines a genetic algorithm with concept map in order select set of units according weaknesses concepts. In the proposed algorithm, serves represent knowledge structure concepts, and performs iteratively evolutionary procedure establish materials based on understanding these also conducted simulations validate using artificially generated data sets, problematic issues regarding generalizing special case are further discussed. The can be generally-employed e-learning, providing for generating all kinds fields.