Teaching Framework Design And Learning Behavior Analysis In Online Education

At present,the human society has entered the "Internet plus" era,and online teaching is not only the main teaching mode of the Open University,but also one of the important auxiliary teaching methods in full-time ordinary universities.How to improve the quality of online teaching is also an important issue that the Open University needs to solve.In this paper,the big data analysis technology is adopted to discuss this issue from two aspects: teaching framework design and learning behavior analysis.The main work of this paper is as follows.First,construct an online teaching framework system for the Shaanxi Branch of the Open University of China.The framework system includes the design of learning behavior measurement indicators,data collection of online teaching,data preprocessing through merging,cleaning and standardization,and online teaching feedback.The purpose of applying this framework is to identify the characteristics of different learning groups,to grasp the teaching rules of teachers and teaching institutions more accurately,so as to provide more effective feedback for the release of learning early warning,personalized teaching implementation and teaching resource allocation.The advantage of this framework is that,compared with the previous data statistics method adopted by Shaanxi Branch of the Open University of China,it is the first time to apply big data-related educational analysis techniques to the design of the online teaching framework system.Second,based on the learning process data of Shaanxi Branch of the Open University of China,the learning process data in online teaching is analyzed.There are a large number of teaching institutions and teacher groups in the Open University,and each teaching institution has its own characteristics in terms of teacher allocation and teaching resources;and students’ learning foundation,learning preference and learning effects are also quite different.This paper constructs measurement indicators based on the learning process data of the Open University,builds an analysis model,adopts the python language to implement the K-means clustering algorithm,and uses the algorithm analysis results to carry out model evaluation.At the same time,based on the course learning data,the course popularity analysis is carried out and the Item-based Coordinated Filtering Algorithm is applied to carry out course recommendation for users.Based on the above research results,this paper aims to classify and identify groups of teaching institutions,teacher groups,and student groups of the Open University and provides more data-supported management suggestions for teaching designers and teaching managers.The online teaching framework system constructed in this paper has been incorporated into the construction of teaching quality evaluation system of Shaanxi Branch of the Open University of China.The analysis results of learning process data have been preliminarily applied to the teaching management of learning support service center of Shaanxi Branch of the Open University of China,which provides a certain basis for the optimal allocation of teaching resources.