C. U. Ezeanya, F. U. Onu, I. J. Ezea, Omo-Okhirelen Obabueki
{"title":"利用长短期记忆递归神经网络增强远程开放教育学生支持系统","authors":"C. U. Ezeanya, F. U. Onu, I. J. Ezea, Omo-Okhirelen Obabueki","doi":"10.46792/fuoyejet.v8i1.955","DOIUrl":null,"url":null,"abstract":"Open and distance education provides access to education to all categories of learners. Learners in Open and Distance education system face the problem of inadequate support services especially when they encounter issues on their studies that need urgent attention. The educational services offered in open and distance education system can only be effective if there is an effective student support system. This study explores the need to enhance the open and distance student support system using Long Short Term Memory neural network. The approach of machine learning was adopted in the area of issue and complaint resolution whereby the issues/complaints are raised in the form of a ticket which is categorized based on their priority. The Last Short Term Memory neural network was used in the prediction of the best solution based on previous input. The enhance student support system was able to provide effective and timely feedback on student issues and complaints. This in turn lowers the rate of student dropout from the system and also provides enabling learning environment for the learners. Machine learning-based student support services improve the effectiveness of the service rendered thereby making the learners improve their academic performance.","PeriodicalId":323504,"journal":{"name":"FUOYE Journal of Engineering and Technology","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Student Support System in Open and Distance Education Using Long Short Term Memory Recurrent Neural Network\",\"authors\":\"C. U. Ezeanya, F. U. Onu, I. J. Ezea, Omo-Okhirelen Obabueki\",\"doi\":\"10.46792/fuoyejet.v8i1.955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Open and distance education provides access to education to all categories of learners. Learners in Open and Distance education system face the problem of inadequate support services especially when they encounter issues on their studies that need urgent attention. The educational services offered in open and distance education system can only be effective if there is an effective student support system. This study explores the need to enhance the open and distance student support system using Long Short Term Memory neural network. The approach of machine learning was adopted in the area of issue and complaint resolution whereby the issues/complaints are raised in the form of a ticket which is categorized based on their priority. The Last Short Term Memory neural network was used in the prediction of the best solution based on previous input. The enhance student support system was able to provide effective and timely feedback on student issues and complaints. This in turn lowers the rate of student dropout from the system and also provides enabling learning environment for the learners. Machine learning-based student support services improve the effectiveness of the service rendered thereby making the learners improve their academic performance.\",\"PeriodicalId\":323504,\"journal\":{\"name\":\"FUOYE Journal of Engineering and Technology\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FUOYE Journal of Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46792/fuoyejet.v8i1.955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FUOYE Journal of Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46792/fuoyejet.v8i1.955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced Student Support System in Open and Distance Education Using Long Short Term Memory Recurrent Neural Network
Open and distance education provides access to education to all categories of learners. Learners in Open and Distance education system face the problem of inadequate support services especially when they encounter issues on their studies that need urgent attention. The educational services offered in open and distance education system can only be effective if there is an effective student support system. This study explores the need to enhance the open and distance student support system using Long Short Term Memory neural network. The approach of machine learning was adopted in the area of issue and complaint resolution whereby the issues/complaints are raised in the form of a ticket which is categorized based on their priority. The Last Short Term Memory neural network was used in the prediction of the best solution based on previous input. The enhance student support system was able to provide effective and timely feedback on student issues and complaints. This in turn lowers the rate of student dropout from the system and also provides enabling learning environment for the learners. Machine learning-based student support services improve the effectiveness of the service rendered thereby making the learners improve their academic performance.