Increasing student numbers lead to new needs in the education sector. New systems are needed due to expert numbers that are insufficient in specialties, such as instructors, directors, and advisors. Type, goal, and specialty of intelligent systems programmed to satisfy this need are being developed with each passing day. The aim of this chapter is to develop an intelligent system that provides support with schedule, academic orientation, choice of profession, and career planning to students. To make a regular schedule for students would generally cause an inappropriate program, which is hardly followed by students in case they were indiscriminately prepared without any information about students' characteristics. Instead of this method, it is the point to be familiar with the academic success, study, resting, and even meal time of the student, and to know which lessons are studied on which days and to make an appropriate schedule for studying. According to the teachers, it is time-consuming and difficult to perform this method for all students. Within this scope, an intelligent system preparing a study schedule is developed considering the students' characteristics and study habits.
The stages of Knowledge Acquisition are present to take the conclusion by configuring information in the intelligent system. Within the context of this study, the system was programmed in line with these processes. They are: Acquisition, Representation, Validation, Inferencing, Explanation.
These stages in the system include revealing the rules and procedures used during problem solving and collaboration of knowledge engineer and leading expert to code. Knowledge Acquisition includes obtaining information from people, books, documents, sensors, and computer files. Representation is the stage that obtained information is organized. It includes formation of knowledge map and to code in knowledge base. Validation is to validate and confirm the information in knowledge base by using test conditions until the quality reaches acceptable level. Inferencing includes interpretation by using database by using database and then, it includes design of software that provide to present suggestion about certain points. Explanation is the stage that includes explaining and presenting the inferences in line with information and rules (Jones, 2008).
Intelligent Systems contain two sub-systems (Lee & Kim, 1998). Knowledge Base and Inference Mechanism. Knowledge base can be organized according to one or more configurations (schemes) such as databases, associative, hierarchal, network etc. Created knowledge representative schemes have 2 basic features: They are recorded to computer memory by coding with current programming languages. The facts and contents of representative schemes are designed in such a way that other information can be reconsidered (Jones, 2008).
In intelligent systems, information should be represented properly for effective study of knowledge inference mechanism. For this purpose, some representative schemes were determined.