{"title":"用计算机模拟进行学习和教学","authors":"Ton de Jong","doi":"10.1016/0167-9287(91)80002-F","DOIUrl":null,"url":null,"abstract":"<div><p>Computer simulations are used in many contexts, such as what-if analyses, experimentation and instruction. The topic of the present volume is the use of computer simulations in instruction. Instructional use of computer simulations has four characteristics:</p><ul><li><span>•</span><span><p>Presence of a formalized, manipulable model;</p></span></li><li><span>•</span><span><p>Presence of learning goals (such as conceptual or operational knowledge);</p></span></li><li><span>•</span><span><p>Elicitation of specific learning processes (such as hypothesis generation and testing);</p></span></li><li><span>•</span><span><p>Presence of learner activity (learners may perform manipulations with the model). These four characteristics together confine our view on instruction and learning with computer simulations. The related topic of modelling shares the above mentioned characteristics with simulation, but has an additional one:</p><ul><li><span>•</span><span><p>Possibility of interfering with the properties of the underlying model. Applying simulations in instruction is important for a number of reasons, the most important of which is probably that learners will be engaged in active exploration and learning — an approach which is advocated in modern instructional/learning theories. Creating hypothetical realities or changing time scales in simulations might sustain this learning approach. Additional reasons for using simulations are a motivational aspect and the possibility of creating situations that are unacceptable in reality for reasons of danger, costs or time.</p></span></li></ul></span></li></ul><p>Learning through exploration puts high cognitive demands on learners. This may result in inefficient and ineffective learning behaviour, where students flounder and do not use the opportunities the simulation environment offers. Therefore, it seems that support is needed if learning from simulations is to be effective. This support can be given by a human teacher but also by a computer learning environment.</p><p>The present volume presents the results of an inventory of elements of such a computer learning environment. This inventory was conducted within a DELTA project called SIMULATE. In the project a learning environment that provides intelligent support to learners and that has a simulation as its nucleus is termed an Intelligent Simulation Learning Environment (ISLE).</p></div>","PeriodicalId":100393,"journal":{"name":"Education and Computing","volume":"6 3","pages":"Pages 217-229"},"PeriodicalIF":0.0000,"publicationDate":"1991-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0167-9287(91)80002-F","citationCount":"179","resultStr":"{\"title\":\"Learning and instruction with computer simulations\",\"authors\":\"Ton de Jong\",\"doi\":\"10.1016/0167-9287(91)80002-F\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Computer simulations are used in many contexts, such as what-if analyses, experimentation and instruction. The topic of the present volume is the use of computer simulations in instruction. Instructional use of computer simulations has four characteristics:</p><ul><li><span>•</span><span><p>Presence of a formalized, manipulable model;</p></span></li><li><span>•</span><span><p>Presence of learning goals (such as conceptual or operational knowledge);</p></span></li><li><span>•</span><span><p>Elicitation of specific learning processes (such as hypothesis generation and testing);</p></span></li><li><span>•</span><span><p>Presence of learner activity (learners may perform manipulations with the model). These four characteristics together confine our view on instruction and learning with computer simulations. The related topic of modelling shares the above mentioned characteristics with simulation, but has an additional one:</p><ul><li><span>•</span><span><p>Possibility of interfering with the properties of the underlying model. Applying simulations in instruction is important for a number of reasons, the most important of which is probably that learners will be engaged in active exploration and learning — an approach which is advocated in modern instructional/learning theories. Creating hypothetical realities or changing time scales in simulations might sustain this learning approach. Additional reasons for using simulations are a motivational aspect and the possibility of creating situations that are unacceptable in reality for reasons of danger, costs or time.</p></span></li></ul></span></li></ul><p>Learning through exploration puts high cognitive demands on learners. This may result in inefficient and ineffective learning behaviour, where students flounder and do not use the opportunities the simulation environment offers. Therefore, it seems that support is needed if learning from simulations is to be effective. This support can be given by a human teacher but also by a computer learning environment.</p><p>The present volume presents the results of an inventory of elements of such a computer learning environment. This inventory was conducted within a DELTA project called SIMULATE. In the project a learning environment that provides intelligent support to learners and that has a simulation as its nucleus is termed an Intelligent Simulation Learning Environment (ISLE).</p></div>\",\"PeriodicalId\":100393,\"journal\":{\"name\":\"Education and Computing\",\"volume\":\"6 3\",\"pages\":\"Pages 217-229\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0167-9287(91)80002-F\",\"citationCount\":\"179\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Education and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/016792879180002F\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education and Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/016792879180002F","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning and instruction with computer simulations
Computer simulations are used in many contexts, such as what-if analyses, experimentation and instruction. The topic of the present volume is the use of computer simulations in instruction. Instructional use of computer simulations has four characteristics:
•
Presence of a formalized, manipulable model;
•
Presence of learning goals (such as conceptual or operational knowledge);
•
Elicitation of specific learning processes (such as hypothesis generation and testing);
•
Presence of learner activity (learners may perform manipulations with the model). These four characteristics together confine our view on instruction and learning with computer simulations. The related topic of modelling shares the above mentioned characteristics with simulation, but has an additional one:
•
Possibility of interfering with the properties of the underlying model. Applying simulations in instruction is important for a number of reasons, the most important of which is probably that learners will be engaged in active exploration and learning — an approach which is advocated in modern instructional/learning theories. Creating hypothetical realities or changing time scales in simulations might sustain this learning approach. Additional reasons for using simulations are a motivational aspect and the possibility of creating situations that are unacceptable in reality for reasons of danger, costs or time.
Learning through exploration puts high cognitive demands on learners. This may result in inefficient and ineffective learning behaviour, where students flounder and do not use the opportunities the simulation environment offers. Therefore, it seems that support is needed if learning from simulations is to be effective. This support can be given by a human teacher but also by a computer learning environment.
The present volume presents the results of an inventory of elements of such a computer learning environment. This inventory was conducted within a DELTA project called SIMULATE. In the project a learning environment that provides intelligent support to learners and that has a simulation as its nucleus is termed an Intelligent Simulation Learning Environment (ISLE).