Research On The Application Of Blue Ink Cloud-Based Data Analysis In The Personalized Learning Mode Of College Students

With the development of the Internet and the popularization of related application technology industries,it has brought new ideas and capabilities for people to solve various problems.For example,experts in related fields have penetrated this new Internet thinking into the education industry,quietly changing the teaching methods of educators and the learning methods of learners.In order to solve the problems of imperfect interfaces and inconsistent calibers,an education platform that enables related data to be managed uniformly also emerged.From the front-end use to the back-end analysis and feedback,an effective closed loop was formed,which truly connected the education industry.Improve work efficiency.In this process,educators are also provided with rich and high-quality data.After conducting a full research on a large number of literatures,this study summarizes the previous research in this field,and on this basis,puts forward some new research ideas in this field,and finally explores using mining programs supported by data science.A personalized learning model with obvious teaching advantages is developed to enable learners to actively and effectively participate in the learning process.The purpose of this study is to provide a perspective for analyzing data.Based on the "Blue ink cloud" education platform,the natural attributes of the learner's original learning state are mined and analyzed,and used to form a more efficient personalized education model.The main work is concentrated in the following parts:(1)Based on the "Blue ink cloud" education platform,a preliminary basic data analysis is carried out on the learner behavior data of the "Appreciation of Educational Films and TV Films" course to explore the hidden information behind;(2)Use the feature extraction method in the field of statistics,with more scientific mathematical theory as the support,propose an extraction plan for personalized learning mode;(3)Use the real learning behavior data of learners in the course of "Appreciation of Educational Theme Films and Videos",use statistics Principles,machine learning algorithms and other data sciences to mine and analyze personalized learning models;(4)Finally,a personalized learning model that makes learning better is based on the learning duration and non-existence of video resources in the "Blue ink cloud" educational platform The superposition of four effective learning methods,such as the number of video resource learning,the better performance in the brainstorming session,and the number of participation in the class discussion and answering questions,has enabled the learner to achieve better learning results in the real teaching process.In this process,focus on solving the problem of feature selection,for example:(1)Through the analysis of data distribution and related labels,the Min-Max Scaling method needs to be used;(2)The use of multi-model experiments,integrated analysis of the results of the integrated model,and the final model is finalized.