Research On Intelligent Learning Diagnosis In Distance Teaching

In distance learning, learning diagnosis is an important learning support services. How to achieve intelligent learning diagnosis, the learning diagnosis done mainly by the network teaching system, is a hot research issue. An accurate and efficient access to distance learners' knowledge state is the key to achieving intelligent learning diagnosis. On this basis, the network teaching system can determine the learning barriers of the learners and targets to provide them with content for further learning.Currently, research on intelligent learning diagnosis is not systematic. A variety of intelligent learning diagnosis methods have their certain advantages, but there are no mutual complementary advantages. In order to clarify the technical idea of intelligent learning diagnosis, this paper study on the basis of a large number of relevant literature, points out that intelligent learning diagnosis has two technical routes. One is based on knowledge space theory. This technology is committed to quickly access learner's knowledge state, organizes the testing process according to the logical relationship between questions. Learners must answer according to the procedures determined by order, which does not meet the learner's answer habits. Another route is based on the knowledge representation technology, characterized by that the learning diagnostic process is divided into two steps. First, by testing gets learners' knowledge level information, and then uses the logical structure of subject knowledge as the base for diagnostic reasoning, determines learners' weak knowledge links. This article describes these two technical routes, and analyzes and summarizes the intelligent learning diagnosis process based on these two technical routes.On the basis of a clear line of the two technical deficiencies, as well as the advantages of both, the paper analyzes the structure of subject knowledge, uses knowledge structure diagram to represent the logical structure of subject knowledge. On this basis, proposes an intelligent learning diagnosis strategy, the strategy has the following main aspects: First, build the knowledge structures of subject; Second, the diagnostic tests; Third, knowledge diagnosis, this aspect uses the logical structure of subject knowledge as the basis to determine learners' weak knowledge points set and learning pathways to be enhanced; Four, guiding feedback, this part introduces the fuzzy evaluation method, and visualization of knowledge points to the process of intelligent learning diagnosis, provides the learners with the diagnostic conclusions in a specific and vivid way. According to the diagnosis strategies, a model of intelligent learning diagnosis is given for implementation of the diagnosis strategies in distance learning systems. This article points out the two technical routes of intelligent learning diagnosis, and makes a detailed presentation, analysis and conclusion about them, which makes the focus of the research on intelligent learning diagnosis and the future direction of development clear; Uses the knowledge structure diagram shows the knowledge structure of subjects, which ensure a complete and efficient reasoning basis for learning diagnosis. On this basis a diagnostic strategy is designed, and an intelligent learning diagnosis model is given, which can further enhance the intelligence of remote network teaching platform; This paper also makes a try to introduce self-adaptation test paper technology, visualization techniques of knowledge points, fuzzy evaluation techniques to diagnostic process,which broadens the study vision and provides a new idea, helping to improve the performance of distance learners.