From The Perspective Of Learner Experience Research On MOOC Curriculum Quality Evaluation

In recent years,with the further development of “Internet plus education”,online education in China is showing a situation of continuous warming.In particular,the sudden arrival of COVID-19 in 2020 brought new development and opportunities for online education in China,which made the teaching advantages of online education more prominent.MOOC has become one of the most sought after and influential learning channels in the online education platform by virtue of its open and shared curriculum advantages.However,with the development of MOOC curriculum,the phenomenon of high registration rate and low completion rate derived from curriculum quality is becoming more and more common.Therefore,clarifying the problems existing in MOOC courses and improving the quality of MOOC courses and learners’ learning viscosity are the key tasks that MOOC platform should complete.MOOC learners are the direct users and perceptors of the curriculum.In the process of MOOC learning,the curriculum comments written by learners can clearly reflect the learners’ subjective emotional attitudes towards teachers,platforms,curriculum resources and other dimensions,These comments are effective reference data for MOOC curriculum quality evaluation.However,there are few studies on the construction of MOOC curriculum evaluation system from the perspective of learners’ experience.This paper is based on the subject education theory,user experience theory and curriculum evaluation theory,and takes the comment text written by learners in MOOC website as the analysis object,and uses text analysis technology to explore the innovative research of MOOC curriculum quality evaluation method from the perspective of learners’ experience.The specific process is as follows: Firstly,using Python programming language to obtain the content of course comments on the website of “Chinese University MOOC”,and preprocing the text of course comments;Secondsly,Based on TF-IDF and K-Means clustering algorithm to extract and classify the elements affecting MOOC curricuum quality,and combined with the research results of online curriculum indexes at home and abroad,integrating and forming the MOOC currculum quality evaluation index system;Then,Based on the optimized emotion dictionary to calculate the emotion values of evaluation indexes at all levels,and combined with coeffcient of variation method to allocate the weight of each index and form a complete MOOC curriculum evaluation system;Finally,the MOOC curriculum quality evaluation system is applied to test its feasibility and the related problems affecting the curriculum quality,and put forward relevant suggestions to improve the MOOC curriculum quality and enhance learners’ learning stickiness from the three levels of curriculum,teachers and platform.