{"title":"基于大数据分析方法的教育计划研究——基于聊天GPT的学习任务数据反馈研究","authors":"Bo-ho Seo","doi":"10.37736/kjlr.2023.06.14.3.07","DOIUrl":null,"url":null,"abstract":"This study discusses exploring and materializing educational methods that can be used in actual classes with the analysis and visualization of learning task data. In education, big data analysis technology has been used for analyzing the environment outside class, and this study finds a way to utilize this method in an offline classroom. In particular, it was expected that if learners' assignments were processed through topic modeling, sentiment analysis, and network analysis methods and then visualized and given feedback, it would be helpful for interactive classes. \nIn addition, this study focuses on collecting and pre-processing the learner's assignment data so this knowledge can be utilized in a class environment unrelated to computer science. This is based on the spread of big data analysis methods and the development of artificial intelligence technologies such as Chat GPT. Through this, instructors can use computer science technology easily in their class environment. \nThis study presents the analysis and visualization of learning task data as a specific example. If this discussion is used, it will be possible for instructors to process and process learning data in a more automated way, even in educational environments where data analysis is not generalized. This is an example of opening the possibility of convergence between computer science and other disciplines.","PeriodicalId":372781,"journal":{"name":"Korean Association for Literacy","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Study on Education Plans Using Big Data Analysis Methods: Focusing on the Feedback of Learning Task Data Using Chat GPT\",\"authors\":\"Bo-ho Seo\",\"doi\":\"10.37736/kjlr.2023.06.14.3.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study discusses exploring and materializing educational methods that can be used in actual classes with the analysis and visualization of learning task data. In education, big data analysis technology has been used for analyzing the environment outside class, and this study finds a way to utilize this method in an offline classroom. In particular, it was expected that if learners' assignments were processed through topic modeling, sentiment analysis, and network analysis methods and then visualized and given feedback, it would be helpful for interactive classes. \\nIn addition, this study focuses on collecting and pre-processing the learner's assignment data so this knowledge can be utilized in a class environment unrelated to computer science. This is based on the spread of big data analysis methods and the development of artificial intelligence technologies such as Chat GPT. Through this, instructors can use computer science technology easily in their class environment. \\nThis study presents the analysis and visualization of learning task data as a specific example. If this discussion is used, it will be possible for instructors to process and process learning data in a more automated way, even in educational environments where data analysis is not generalized. This is an example of opening the possibility of convergence between computer science and other disciplines.\",\"PeriodicalId\":372781,\"journal\":{\"name\":\"Korean Association for Literacy\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korean Association for Literacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37736/kjlr.2023.06.14.3.07\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Association for Literacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37736/kjlr.2023.06.14.3.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study on Education Plans Using Big Data Analysis Methods: Focusing on the Feedback of Learning Task Data Using Chat GPT
This study discusses exploring and materializing educational methods that can be used in actual classes with the analysis and visualization of learning task data. In education, big data analysis technology has been used for analyzing the environment outside class, and this study finds a way to utilize this method in an offline classroom. In particular, it was expected that if learners' assignments were processed through topic modeling, sentiment analysis, and network analysis methods and then visualized and given feedback, it would be helpful for interactive classes.
In addition, this study focuses on collecting and pre-processing the learner's assignment data so this knowledge can be utilized in a class environment unrelated to computer science. This is based on the spread of big data analysis methods and the development of artificial intelligence technologies such as Chat GPT. Through this, instructors can use computer science technology easily in their class environment.
This study presents the analysis and visualization of learning task data as a specific example. If this discussion is used, it will be possible for instructors to process and process learning data in a more automated way, even in educational environments where data analysis is not generalized. This is an example of opening the possibility of convergence between computer science and other disciplines.