Designing and application of web-based adaptive intelligent education system

Even though the applications developed by using adaptive intelligent instructional technology improve the efficiency of the education comparatively to traditionally developed applications, it is obvious that they do not become sufficiently widespread. The reason for that are the problems faced by the educators during the development process of the adaptive intelligent instructional applications. There are other problems to be solved apart from these problems faced by the educators during the adaptive intelligent instructional applications. A rapid and efficient adaptive effect should be ensured in order to prevent users from getting lost or interruption of their motivation in hypermedia environment. The purpose of this study is to design a web based adaptive intelligent instructional system which solves the problems and meets also the requirements of both educators and students in a general-purpose adaptive intelligent instructional environment. For this purpose, firstly, a generic educational hypermedia object model designed by using object oriented programming techniques is introduced. A form-based domain model management system has been developed to develop domain models without any need of software support which is one of the most important problems that educators come across in an adaptive instructional environment. A student model analysis system has been developed for another problem faced by the educators which is analysis of the user knowledge status. A user modeling server has been designed to construct user models rapidly and efficiently which are the main component of the adaptation. The designed user modeling server converts the gathered data from following up the students after processing it into a rule based inference mechanism. Naive Bayes classifier dynamically updates the user models by classifying these data. User modeling server can update user models online by using different modeling strategies for different users with different former experiences and it can provide the real time adaptation effect in a short time period. Lastly there is an experimental study to test the designed system. The domain model of the experimental study has been developed by using management tool of the designed system. The results of the experimental study have still been analyzed by using another tool of the system which is student model analysis tool. In the consequence of the analysis it is observed that students those have never taken ?DC Electrical machines? lecture before have been more successful in reaching the instructional target in intelligent instructional environment than in traditional instructional environment. It is also observed those students that have taken and passed the lecture before have shown similar success in both of instructional environments. The accuracy level of adaptive intelligent instruction users to follow an instructional target-related page has obviously been higher than the accuracy level of traditional instructional application users. Generally, the students studying in adaptive intelligent instructional environment have used their more efficiently and beginner level students have been more successful in adaptive intelligent instructional environment comparing to the ones in traditional environment.