{"title":"将学生反应时间和导师教学干预纳入学生建模","authors":"Chen Lin, Shitian Shen, Min Chi","doi":"10.1145/2930238.2930291","DOIUrl":null,"url":null,"abstract":"Bayesian Knowledge Tracing (BKT) is one of the most widely adopted student-modeling methods. It uses performance (incorrect,correct) to infer student knowledge state (unlearned, learned). However, performance can be noisy and thus we explored another type of observations -- student response time. Furthermore, we proposed Intervention Bayesian Knowledge Tracing (Intervention-BKT) which can incorporate multiple types of instructional interventions into the conventional BKT model. Our results show that for next-step performance predictions, Intervention-BKT is more effective than BKT; whereas to predict students' post-test scores, including student response time would yield better result than using performance alone.","PeriodicalId":339100,"journal":{"name":"Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Incorporating Student Response Time and Tutor Instructional Interventions into Student Modeling\",\"authors\":\"Chen Lin, Shitian Shen, Min Chi\",\"doi\":\"10.1145/2930238.2930291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bayesian Knowledge Tracing (BKT) is one of the most widely adopted student-modeling methods. It uses performance (incorrect,correct) to infer student knowledge state (unlearned, learned). However, performance can be noisy and thus we explored another type of observations -- student response time. Furthermore, we proposed Intervention Bayesian Knowledge Tracing (Intervention-BKT) which can incorporate multiple types of instructional interventions into the conventional BKT model. Our results show that for next-step performance predictions, Intervention-BKT is more effective than BKT; whereas to predict students' post-test scores, including student response time would yield better result than using performance alone.\",\"PeriodicalId\":339100,\"journal\":{\"name\":\"Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2930238.2930291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2930238.2930291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Incorporating Student Response Time and Tutor Instructional Interventions into Student Modeling
Bayesian Knowledge Tracing (BKT) is one of the most widely adopted student-modeling methods. It uses performance (incorrect,correct) to infer student knowledge state (unlearned, learned). However, performance can be noisy and thus we explored another type of observations -- student response time. Furthermore, we proposed Intervention Bayesian Knowledge Tracing (Intervention-BKT) which can incorporate multiple types of instructional interventions into the conventional BKT model. Our results show that for next-step performance predictions, Intervention-BKT is more effective than BKT; whereas to predict students' post-test scores, including student response time would yield better result than using performance alone.