{"title":"用随机分析定量解决群体问题","authors":"Wen Dong, A. Pentland","doi":"10.1145/1891903.1891954","DOIUrl":null,"url":null,"abstract":"Quantifying the relationship between group dynamics and group performance is a key issue of increasing group performance. In this paper, we will discuss how group performance is related to several heuristics about group dynamics in performing several typical tasks. We will also give our novel stochastic modeling in learning the structure of group dynamics. Our performance estimators account for between 40 and 60% of the variance across range of group problem solving tasks.","PeriodicalId":181145,"journal":{"name":"ICMI-MLMI '10","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Quantifying group problem solving with stochastic analysis\",\"authors\":\"Wen Dong, A. Pentland\",\"doi\":\"10.1145/1891903.1891954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantifying the relationship between group dynamics and group performance is a key issue of increasing group performance. In this paper, we will discuss how group performance is related to several heuristics about group dynamics in performing several typical tasks. We will also give our novel stochastic modeling in learning the structure of group dynamics. Our performance estimators account for between 40 and 60% of the variance across range of group problem solving tasks.\",\"PeriodicalId\":181145,\"journal\":{\"name\":\"ICMI-MLMI '10\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICMI-MLMI '10\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1891903.1891954\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICMI-MLMI '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1891903.1891954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantifying group problem solving with stochastic analysis
Quantifying the relationship between group dynamics and group performance is a key issue of increasing group performance. In this paper, we will discuss how group performance is related to several heuristics about group dynamics in performing several typical tasks. We will also give our novel stochastic modeling in learning the structure of group dynamics. Our performance estimators account for between 40 and 60% of the variance across range of group problem solving tasks.
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