Research And Application Of Evaluation Model Based On Learner Epistemic Network Analysis

In the context of "Big Data",educational activities generate a large amount of diverse educational data and information,and it is difficult for traditional educational evaluation to effectively use these data to meet the needs of learners.How to reasonably use the rich data generated in a complex teaching environment,use appropriate evaluation methods to evaluate learners' knowledge and skill mastery,measure their thinking development level and the dynamic process of cognitive construction,and further use evaluation feedback information to teach students according to their aptitude,has become a hot topic in the field of education evaluation research.In order to evaluate learners' thinking level and cognitive construction process in a complex teaching environment,the consistency of each cognitive element in the learner's cognitive framework and the process of social practice training is tested,and to provide teachers and students with timely and dynamic Teaching feedback,this research takes the "evidence-centered" educational evaluation design model and cognitive framework theory as the theoretical basis,and integrates visual analysis technologies such as Epistemic Network Analysis to design and build a learning-based Epistemic Network Analysis(Evaluation Based on Epistemic Network Analysis,eferred to as EBENA mode).The evaluation model makes up for the shortcomings of the traditional education evaluation model,such as too much emphasis on results,single source of evaluation data,too old analysis tools,and neglect of individual learners.The research on education evaluation has been improved and enriched.In order to test the evaluation effect of the EBENA model,this study implements and applies this evaluation model in teaching practice.First,design teaching activities in natural and real classrooms,implement student mutual evaluation,collect peer evaluation data as the data source for evaluation under the EBENA model;then,based on the cognitive framework theory and curriculum evaluation indicators,construct the cognitive coding of evaluation Finally,use statistical analysis and Epistemic Network Analysis to explore learners' evaluation discourse quality and cognitive structure characteristics,and analyze and evaluate different learners' thinking,cognitive development changes and differences.Based on the analysis results,this study gives the evaluator,the evaluator and the teacher corresponding evaluation feedback,and provides teaching suggestions and learning guidance for teachers and students.Application practice has proved that the EBENA model is more suitable for evaluation based on discourse and text data.The combination of statistical analysis and visual analysis can well present the teaching quality of teachers and the learning effect of learners,and test learners with different learning experiences and different levels of learning.The quality of discourse,the level of thinking development,and the cognitive structure in order to improve the teaching model and promote learner learning,and can provide model references and theoretical guidance for educators to implement accurate educational evaluation and feedback in complex teaching environments.