{"title":"空间适应:建模是一项关键的空间能力","authors":"A. Lovett, Holger Schultheis","doi":"10.1080/13875868.2020.1830994","DOIUrl":null,"url":null,"abstract":"ABSTRACT Spatial adaptation is the process of adjusting one’s mental representations for a task, so that spatial details necessary for performing the task are captured in the representations, whereas irrelevant details are ignored. We believe this process plays a critical role both in spatial ability tests and in STEM domains because it produces problem-tailored representations that can facilitate mental manipulation by representing only task-relevant details. Here, we present a computational model that illustrates the importance of spatial adaptation in a mental rotation task. The model automatically generates shape representations by segmenting objects into parts at concavities. It adjusts its representations in two ways: by varying the number of parts used to represent a shape, and by varying the types of information encoded for each part. Critically, the model can adapt to a mental rotation task by adjusting the degree of detail in its shape representations automatically, based on how much detail is needed to distinguish the shapes from distractors.","PeriodicalId":46199,"journal":{"name":"Spatial Cognition and Computation","volume":"110 1","pages":"89 - 113"},"PeriodicalIF":1.6000,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Spatial adaptation: modeling a key spatial ability\",\"authors\":\"A. Lovett, Holger Schultheis\",\"doi\":\"10.1080/13875868.2020.1830994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Spatial adaptation is the process of adjusting one’s mental representations for a task, so that spatial details necessary for performing the task are captured in the representations, whereas irrelevant details are ignored. We believe this process plays a critical role both in spatial ability tests and in STEM domains because it produces problem-tailored representations that can facilitate mental manipulation by representing only task-relevant details. Here, we present a computational model that illustrates the importance of spatial adaptation in a mental rotation task. The model automatically generates shape representations by segmenting objects into parts at concavities. It adjusts its representations in two ways: by varying the number of parts used to represent a shape, and by varying the types of information encoded for each part. Critically, the model can adapt to a mental rotation task by adjusting the degree of detail in its shape representations automatically, based on how much detail is needed to distinguish the shapes from distractors.\",\"PeriodicalId\":46199,\"journal\":{\"name\":\"Spatial Cognition and Computation\",\"volume\":\"110 1\",\"pages\":\"89 - 113\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2020-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spatial Cognition and Computation\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1080/13875868.2020.1830994\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PSYCHOLOGY, EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Cognition and Computation","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1080/13875868.2020.1830994","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
Spatial adaptation: modeling a key spatial ability
ABSTRACT Spatial adaptation is the process of adjusting one’s mental representations for a task, so that spatial details necessary for performing the task are captured in the representations, whereas irrelevant details are ignored. We believe this process plays a critical role both in spatial ability tests and in STEM domains because it produces problem-tailored representations that can facilitate mental manipulation by representing only task-relevant details. Here, we present a computational model that illustrates the importance of spatial adaptation in a mental rotation task. The model automatically generates shape representations by segmenting objects into parts at concavities. It adjusts its representations in two ways: by varying the number of parts used to represent a shape, and by varying the types of information encoded for each part. Critically, the model can adapt to a mental rotation task by adjusting the degree of detail in its shape representations automatically, based on how much detail is needed to distinguish the shapes from distractors.