Text Mining And Analysis In MOOC Adaptive Learning

Applying machine learning,deep learning and adaptive learning techniques to online learning platforms can promote the development of online learning activities in an adaptive and personalized way.Since 2012,MOOC has set off a global frenzy and has been highly regarded and valued by universities,educational institutions,researchers,scholars,educators and learners.However,these days,adaptive learning service support is still a shortcoming of many MOOC learning platforms.The MOOC learning platform does not fully exploit the vast learning records of learners,or fully grasp the learner's learning status,hence cannot provide learners with learning guidance and help that suits their specific needs.Therefore,it is strongly necessary to apply text mining and analysis in adaptive learning technology to the MOOC learning platform.This research puts forward the ideas and methods of text mining and analysis based on Python for the application of text data mining and analysis technology in Chinese university MOOC learning platform.10144 pieces of text data were mined,and 10144 pieces of text data were quantitatively analyzed and qualitatively analyzed.The texts of learners in the MOOC course discussion area are divided into content,exercises,techniques,evaluations,emotions,and six other categories.The specific work of this paper is as follows:First,make a literature review of relevant concepts,theories and practical applications,and give a summary of the characteristics of the adaptive learning of the MOOC learning platform.Then,sort out the tools which are used in education data mining and analysis.And in order to provide theoretical and practical basis for this research,we need to analyze the reasons why these tools are selected.Second,sample the Chinese university MOOC platform and the specific courses in edX,and compare and analyze the current situation of curriculum interaction in the two learning platforms.According to the analysis results of the status quo,the text mining ideas and methods based on Python are proposed to mine and quantify the texts in the Chinese university MOOC learning platform.The purpose of the experiment is to understand the situation of text utilization in the current MOOC course and to provide an objective data basis for text content analysis.Third,the paper puts forward the ideas and methods of text analysis based on Python,and uses the jieba library for word segmentation,keyword extraction,text classification and visualization results.Then conduct case analysis,analyze the text content of learners in different types of courses,and compare and analyze the texts of learners in the same type of courses.Finally,summarize and reflect on the analysis process and results,and provide teaching reference for MOOC learning platform and teachers.Fourth,summarize and reflect on the whole research process,and propose text mining and analysis strategies applicable to the MOOC learning platform.