{"title":"链接:什么是智能辅导系统?","authors":"Reva Freedman, Syed S. Ali, S. McRoy","doi":"10.1145/350752.350756","DOIUrl":null,"url":null,"abstract":"Professor Freedman's research focuses on reactive planning and theories of discourse and dialog processing with the goal of building better intelligent tutoring systems. T he term \" intelligent tutoring system \" (ITS) refers to any computer program that can be used in learning and that contains intelligence—this breadth has no doubt helped make ITS research the large and varied field that it is. ITS research is an out-growth of the earlier computer-aided instruction (CAI) model, which usually refers to a frame-based system with hard-coded links, that is, hypertext with an instructional purpose. The traditional ITS model has four components: the domain model, the student model, the teaching model, and a learning environment or user interface. ITS projects can vary significantly by the relative level of intelligence of the components. For example, a project focusing on intelligence in the domain model may generate solutions to complex and novel problems so that students can always have new problems on which to practice, but it might only have simple methods for teaching those problems. Or a system might concentrate on multiple or novel ways to teach a particular topic and therefore find a less sophisticated representation of that content sufficient. When multiple components contain intelligence, homogeneous or heterogeneous representations can be used. ITSs can also be classified by their underlying algorithm. One well-known category is the model-tracing tutor, which tracks students' progress and keeps them within a specified tolerance of an acceptable solution path. A theme underlying much of ITS research is domain independence, that is, the degree to which knowledge encoded in the teaching model can be reused in different domains. Although to the external observer domain independence seems like an essential characteristic of intelligence, many experts believe that some of the essential pedagogical knowledge in every domain is fundamentally domain dependent. For example, some analogies used in teaching physics, and even in teaching specific topics in physics, have no equivalents in other domains. Task independence, or the degree to which the knowledge in the system can be used to support a variety of tasks on the part of the student, has not yet been addressed by most systems. Journals The International Journal of Artificial Intelligence in Education (cbl.leeds.ac. uk/ijaied/), the official journal of the International AIED Society, is the preeminent journal in the field; it is published both in print and on the Web. Other journals that publish significant ITS research …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"9 1","pages":"15-16"},"PeriodicalIF":0.0000,"publicationDate":"2000-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"75","resultStr":"{\"title\":\"Links: what is an intelligent tutoring system?\",\"authors\":\"Reva Freedman, Syed S. Ali, S. McRoy\",\"doi\":\"10.1145/350752.350756\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Professor Freedman's research focuses on reactive planning and theories of discourse and dialog processing with the goal of building better intelligent tutoring systems. T he term \\\" intelligent tutoring system \\\" (ITS) refers to any computer program that can be used in learning and that contains intelligence—this breadth has no doubt helped make ITS research the large and varied field that it is. ITS research is an out-growth of the earlier computer-aided instruction (CAI) model, which usually refers to a frame-based system with hard-coded links, that is, hypertext with an instructional purpose. The traditional ITS model has four components: the domain model, the student model, the teaching model, and a learning environment or user interface. ITS projects can vary significantly by the relative level of intelligence of the components. For example, a project focusing on intelligence in the domain model may generate solutions to complex and novel problems so that students can always have new problems on which to practice, but it might only have simple methods for teaching those problems. Or a system might concentrate on multiple or novel ways to teach a particular topic and therefore find a less sophisticated representation of that content sufficient. When multiple components contain intelligence, homogeneous or heterogeneous representations can be used. ITSs can also be classified by their underlying algorithm. One well-known category is the model-tracing tutor, which tracks students' progress and keeps them within a specified tolerance of an acceptable solution path. A theme underlying much of ITS research is domain independence, that is, the degree to which knowledge encoded in the teaching model can be reused in different domains. Although to the external observer domain independence seems like an essential characteristic of intelligence, many experts believe that some of the essential pedagogical knowledge in every domain is fundamentally domain dependent. For example, some analogies used in teaching physics, and even in teaching specific topics in physics, have no equivalents in other domains. Task independence, or the degree to which the knowledge in the system can be used to support a variety of tasks on the part of the student, has not yet been addressed by most systems. Journals The International Journal of Artificial Intelligence in Education (cbl.leeds.ac. uk/ijaied/), the official journal of the International AIED Society, is the preeminent journal in the field; it is published both in print and on the Web. Other journals that publish significant ITS research …\",\"PeriodicalId\":8272,\"journal\":{\"name\":\"Appl. Intell.\",\"volume\":\"9 1\",\"pages\":\"15-16\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"75\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Appl. 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Professor Freedman's research focuses on reactive planning and theories of discourse and dialog processing with the goal of building better intelligent tutoring systems. T he term " intelligent tutoring system " (ITS) refers to any computer program that can be used in learning and that contains intelligence—this breadth has no doubt helped make ITS research the large and varied field that it is. ITS research is an out-growth of the earlier computer-aided instruction (CAI) model, which usually refers to a frame-based system with hard-coded links, that is, hypertext with an instructional purpose. The traditional ITS model has four components: the domain model, the student model, the teaching model, and a learning environment or user interface. ITS projects can vary significantly by the relative level of intelligence of the components. For example, a project focusing on intelligence in the domain model may generate solutions to complex and novel problems so that students can always have new problems on which to practice, but it might only have simple methods for teaching those problems. Or a system might concentrate on multiple or novel ways to teach a particular topic and therefore find a less sophisticated representation of that content sufficient. When multiple components contain intelligence, homogeneous or heterogeneous representations can be used. ITSs can also be classified by their underlying algorithm. One well-known category is the model-tracing tutor, which tracks students' progress and keeps them within a specified tolerance of an acceptable solution path. A theme underlying much of ITS research is domain independence, that is, the degree to which knowledge encoded in the teaching model can be reused in different domains. Although to the external observer domain independence seems like an essential characteristic of intelligence, many experts believe that some of the essential pedagogical knowledge in every domain is fundamentally domain dependent. For example, some analogies used in teaching physics, and even in teaching specific topics in physics, have no equivalents in other domains. Task independence, or the degree to which the knowledge in the system can be used to support a variety of tasks on the part of the student, has not yet been addressed by most systems. Journals The International Journal of Artificial Intelligence in Education (cbl.leeds.ac. uk/ijaied/), the official journal of the International AIED Society, is the preeminent journal in the field; it is published both in print and on the Web. Other journals that publish significant ITS research …