Designing intelligent agent in multilevel game-based modules for e-learning computer science course

Abstract

Nowadays, game-based learning environments are very common environments for studying major scientific fields such as mathematics, computer science, electronics and electrical engineering. This chapter presents a game-based modules system called the game-based modules (GBMs). It combines the characteristics of computer game elements with the existing interactive multimedia environments for learning mathematics, physics and electronics. This module presents a new type of game-learning environment for teaching units of Computer Science courses. Bearing in mind that the GBMs includes interactive tasks as a form of a multi-level approach to problem solving, we have also shown an approach to evaluating student's knowledge necessary for upgrading him/her to the higher level of learning. To assess a student's knowledge level needed for the next game level in the GBMs, we have developed an intelligent agent. This illustrates how intelligent agents and fuzzy logic can help increase the quality and quantity of the most important element of e-learning and that is making a decision. The results of student's knowledge diagnosis by means of agent within the GBMs e-learning system demonstrate the possibility of applying the presented agent model in various game-based learning systems for the determination of the knowledge level performance. On the basis of the data obtained through the exams, as well as through the use of statistical reasoning methods, we have shown the efficiency of the GBMs in the learning process. © 2014 Springer-Verlag Berlin Heidelberg.