{"title":"在基于计算机的测试设施中建模学生调度偏好","authors":"Matthew West, C. Zilles","doi":"10.1145/2876034.2893441","DOIUrl":null,"url":null,"abstract":"When undergraduate students are allowed to choose a time slot in which to take an exam from a large number of options (e.g., 40), the students exhibit strong preferences among the times. We found that students can be effectively modelled using constrained discrete choice theory to quantify these preferences from their observed behavior. The resulting models are suitable for load balancing when scheduling multiple concurrent exams and for capacity planning given a set schedule.","PeriodicalId":20739,"journal":{"name":"Proceedings of the Third (2016) ACM Conference on Learning @ Scale","volume":"42 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Modeling Student Scheduling Preferences in a Computer-Based Testing Facility\",\"authors\":\"Matthew West, C. Zilles\",\"doi\":\"10.1145/2876034.2893441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When undergraduate students are allowed to choose a time slot in which to take an exam from a large number of options (e.g., 40), the students exhibit strong preferences among the times. We found that students can be effectively modelled using constrained discrete choice theory to quantify these preferences from their observed behavior. The resulting models are suitable for load balancing when scheduling multiple concurrent exams and for capacity planning given a set schedule.\",\"PeriodicalId\":20739,\"journal\":{\"name\":\"Proceedings of the Third (2016) ACM Conference on Learning @ Scale\",\"volume\":\"42 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third (2016) ACM Conference on Learning @ Scale\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2876034.2893441\",\"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 Third (2016) ACM Conference on Learning @ Scale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2876034.2893441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling Student Scheduling Preferences in a Computer-Based Testing Facility
When undergraduate students are allowed to choose a time slot in which to take an exam from a large number of options (e.g., 40), the students exhibit strong preferences among the times. We found that students can be effectively modelled using constrained discrete choice theory to quantify these preferences from their observed behavior. The resulting models are suitable for load balancing when scheduling multiple concurrent exams and for capacity planning given a set schedule.