Research On Personalized Online Learning System Model Based On Genetic Algorithm

At present, teaching resource adaptive selection problem exists generally in online learning system.This article has carried on the analysis to the related literature and the related basic theory of online learning system. How to provide the appropriate learning content according to the learners’ personalized features is studied.Personalized online learning system model based on genetic algorithm is given in the study,which dynamically adjusts and recommends learning resource according to realize the personalized features. Personalized online learning system includes learning interest model and learning resource model.Learning interest model is dynamically updated with using genetic algorithm.At the same time,an application example is given,and the computer simulation is carried out.The data showed that, to solve the model proposed is effective for problems.Personalized online learning system solutions developed based on open source software platform Sakai are given.The main work as follows:1.The establishment of initial interest model of users.2.The uses’ initial interest model is dynamically updated.After the initial interest model is established,the model is dynamically updated with using genetic algorithm.As the static model is not fully reflect the preferences of the learners,this users’ model update the student interest vector by tracking students’ learning behavior, and using the experience of other users’ resources choice, so as to update the students’ interests.In order to verify the validity of the model,model updating processes were tested with examples.3.Building the learning resources’ model.Learning resource model includes resource model representation and determining resource difficulty coefficient.4.The matching mechanism between the users’interest model and learning resource’ model to realize the personalized recommendations.The object which is recommended to the user by recommendation system cannot just watched by users.At the same time,the object is not too similar to the users or irrelevant,or even repeatedly with users.To solve the randomness,genetic algorithm is introduced to make the algorithm converge to global optimal or approximate global optimal, thereby the more appropriate learning content is provided for learners. 5.Personalized online learning system solution developed based on open source software platform Sakai is given. Personalized online learning system developed based on open source software platform Sakai is analyzed and designed.The overall architecture and personalized online learning system model of the system are given.Recommended resources is specifically analyzed.The difficulty and innovation points lie in the implementation of the users’ interest model’s updating dynamically to avoid repetitive learning resources recommendation and wrong recommendation.