Development of an intelligent simulation-based learning environment to design and tutor neural networks

The earliest applications of AI in education developed intelligent tutoring system (ITS). For the greatest part, ITS have attempted to implement traditional methods of learning and teaching, train-and-practice, in which the student solves relatively simple problems chosen by the teacher. However, to develop flexible learning systems, educational simulation systems are considered as the new strategy of teaching/learning. This paper reports the development of an Intelligent Simulation-Based Learning Environment To design and TutoR Neural networks (ISABLETOTRAIN). The system is based on the concept that neural networks can be broken down into a fundamental set of neural components. The user constructs his/her theoretical knowledge in the environment where he/she can choose some components and find the pattern of relationships among those components, and try to build his/her neural network Components are graphical representations of the neural network functions. In terms of simulation, these functions are built as objects using object-oriented modeling in which each component is a separate object that sends and receives messages.