MOOC System Designing Based Faulty Diagnosis

Internet technology is increasingly shaping the way of general knowledge spreading such as education and teaching.MOOC(Massive Open Online Course)is an online course,which has the feature of open and wide audience.It is the most successful and common application mode of Internet education so far.Most of the existing MOOC systems are concerning about the openness of knowledge acquisition channels and the enrichment of knowledge content.While few of them pay attention on learning effectiveness evaluation and feedback.This research based on the new design method of MOOC system and the evaluation of the learning effect are carried out.(1)A new type of architecture with testing function is put forward,as well as a matching explanation,the requirement and method of test question design,and applied to the C programming language.(2)In view of the students' answer data,the Bayesian weighted probability and fault tree diagnosis are used to infer the learners' problems and omissions,and to find out the common problems in the teaching.(3)Designed and implemented a MOOC platform software and applied the platform to C language MOOC.A large number of data in this system shows that the design and implementation of MOOC system Designing based on data analysis and faulty diagnosis is feasible,and has a good effect on improving learning efficiency.In the future,how to improve the learning efficiency and teaching quality will become the main direction of the future development of MOOC.The teaching evaluation based on data analysis and faulty diagnosis will provide a possible way of closed-loop course learning route for learners,which will greatly improve the learning efficiency and the teaching quality.