Research On The E-learning Interactive Behavior Evaluation Index System

At present, we have lacked the theory and practice of E-learning interactive behavior evaluation index system in distance education. It has restricted the development of distance learning evaluation to some extent.Based on the modern evaluation learning theory, we first integrated the feature of distance learning mode, analyzing the E-learning interactive behavior on the network, using questionnaire surveys, to understand the factors which influence the E-learning interactive behavior and its attributes features. On this basis, we defined the attributes features of E-learning interactive behavior and initially identified the category index, laying the foundation for the establishment of index system.Secondly, based on the form of Analytical Hierarchy Process (AHP), we voluntarily prepared and distributed the questionnaire named "E-learning interactive behavior Evaluation Index Weights Survey to the experts, teachers and staffs in the field of distance education. We used a software named yaahp to analyze the survey data, obtaining the weight coefficients of indicators at all levels, forming the draft of E-learning interactive behavior evaluation index system.Finally, we surveyed the students in reading of Southwest University by questionnaire, collecting students' learning behaviors in a certain course. We used SPSS statistical software to analyze the data, using principal component factor analysis to extract indicators at all levels, and according to factor loadings and the relative contribution of the main factors to calculate the weights at all levels. Then this result was compared with the previous, to determine the cause of the error and error range. Based on this, we revised and improved the E-learning interactive behavior evaluation index system.The study designed the index system that can be used to guide the practice of E-learning interactive behavior evaluation. The system contains two level indicators:"Person-Content" interactions and "People-People" interactions. Each level is divided into three secondary indicators, namely:operating interaction, information interaction, and concept interaction. Each secondary index has a relatively fixed distribution of the weight coefficients, and may include different numbers of the third level indicators. The weight coefficients of them can be made the appropriate adjustment by the actual situation of distance education. The operability of this E-learning interactive behavior evaluation index system is good. We can directly use this index system to guide the practice of distance education.