{"title":"程序设计专业学生预测模型研究","authors":"Maryam Zaffar, M. Hashmani, K. Savita","doi":"10.1109/ICCOINS.2018.8510571","DOIUrl":null,"url":null,"abstract":"Educational Data Mining (EDM) is very appealing research area which can mine valuable information from educational databases. The mined information from educational data can be used to give assistance to educational decision makers to plan strategies according for different academic courses. The main objective of this paper is to provide an overview of existing models for predicting performance of students who are taking programming course. This paper also focuses on the important attributes of students taking programming courses used by some of the existing studies. Furthermore, the paper also highlights the different classification prediction algorithms to predict the performance of students taking programming courses. The study tries to provide some highlight for new researchers in building a prediction model for programming students. This paper is the step towards improving the quality of education and could bring assistance and impacts to all the educational stakeholders.","PeriodicalId":168165,"journal":{"name":"2018 4th International Conference on Computer and Information Sciences (ICCOINS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A Study of Prediction Models for Students Enrolled in Programming Subjects\",\"authors\":\"Maryam Zaffar, M. Hashmani, K. Savita\",\"doi\":\"10.1109/ICCOINS.2018.8510571\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Educational Data Mining (EDM) is very appealing research area which can mine valuable information from educational databases. The mined information from educational data can be used to give assistance to educational decision makers to plan strategies according for different academic courses. The main objective of this paper is to provide an overview of existing models for predicting performance of students who are taking programming course. This paper also focuses on the important attributes of students taking programming courses used by some of the existing studies. Furthermore, the paper also highlights the different classification prediction algorithms to predict the performance of students taking programming courses. The study tries to provide some highlight for new researchers in building a prediction model for programming students. This paper is the step towards improving the quality of education and could bring assistance and impacts to all the educational stakeholders.\",\"PeriodicalId\":168165,\"journal\":{\"name\":\"2018 4th International Conference on Computer and Information Sciences (ICCOINS)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 4th International Conference on Computer and Information Sciences (ICCOINS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCOINS.2018.8510571\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Computer and Information Sciences (ICCOINS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCOINS.2018.8510571","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study of Prediction Models for Students Enrolled in Programming Subjects
Educational Data Mining (EDM) is very appealing research area which can mine valuable information from educational databases. The mined information from educational data can be used to give assistance to educational decision makers to plan strategies according for different academic courses. The main objective of this paper is to provide an overview of existing models for predicting performance of students who are taking programming course. This paper also focuses on the important attributes of students taking programming courses used by some of the existing studies. Furthermore, the paper also highlights the different classification prediction algorithms to predict the performance of students taking programming courses. The study tries to provide some highlight for new researchers in building a prediction model for programming students. This paper is the step towards improving the quality of education and could bring assistance and impacts to all the educational stakeholders.