{"title":"面对计算设计教学的挑战","authors":"N. Senske","doi":"10.52842/conf.caadria.2014.821","DOIUrl":null,"url":null,"abstract":"Many architects understand that learning to program can be a challenge, but assume that time and practice are the only barriers to performing well enough at it. However, research from computer science education does not support this assumption. Multinational studies of undergraduate computer science programs reveal that a significant number of students in their first and second year of full-time instruction still have serious misconceptions about how computer programs work and an inability to design programs of their own. If computer science students have trouble learning to think and express themselves computationally, what does this say about architects' chances of learning to program well? Moreover, if common problems have been identified, can architectural educators learn anything from findings in computer science education research? In order to determine if this research is relevant to architecture, the author conducted a pilot study of architecture students consisting of program analysis and conceptual knowledge tests. The study found that student performance was poor in ways similar to those revealed in the computer science education research. Because architects face similar challenges as computer science majors, this suggests that the discipline could benefit from more investment in educational collaborations. In addition, empirical research – from architecture as well as other fields – must play a more substantial role in helping architects learn computational thinking and expression.","PeriodicalId":281741,"journal":{"name":"CAADRIA proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Confronting the Challenges of Computational Design Instruction\",\"authors\":\"N. Senske\",\"doi\":\"10.52842/conf.caadria.2014.821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many architects understand that learning to program can be a challenge, but assume that time and practice are the only barriers to performing well enough at it. However, research from computer science education does not support this assumption. Multinational studies of undergraduate computer science programs reveal that a significant number of students in their first and second year of full-time instruction still have serious misconceptions about how computer programs work and an inability to design programs of their own. If computer science students have trouble learning to think and express themselves computationally, what does this say about architects' chances of learning to program well? Moreover, if common problems have been identified, can architectural educators learn anything from findings in computer science education research? In order to determine if this research is relevant to architecture, the author conducted a pilot study of architecture students consisting of program analysis and conceptual knowledge tests. The study found that student performance was poor in ways similar to those revealed in the computer science education research. Because architects face similar challenges as computer science majors, this suggests that the discipline could benefit from more investment in educational collaborations. In addition, empirical research – from architecture as well as other fields – must play a more substantial role in helping architects learn computational thinking and expression.\",\"PeriodicalId\":281741,\"journal\":{\"name\":\"CAADRIA proceedings\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CAADRIA proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52842/conf.caadria.2014.821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CAADRIA proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52842/conf.caadria.2014.821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Confronting the Challenges of Computational Design Instruction
Many architects understand that learning to program can be a challenge, but assume that time and practice are the only barriers to performing well enough at it. However, research from computer science education does not support this assumption. Multinational studies of undergraduate computer science programs reveal that a significant number of students in their first and second year of full-time instruction still have serious misconceptions about how computer programs work and an inability to design programs of their own. If computer science students have trouble learning to think and express themselves computationally, what does this say about architects' chances of learning to program well? Moreover, if common problems have been identified, can architectural educators learn anything from findings in computer science education research? In order to determine if this research is relevant to architecture, the author conducted a pilot study of architecture students consisting of program analysis and conceptual knowledge tests. The study found that student performance was poor in ways similar to those revealed in the computer science education research. Because architects face similar challenges as computer science majors, this suggests that the discipline could benefit from more investment in educational collaborations. In addition, empirical research – from architecture as well as other fields – must play a more substantial role in helping architects learn computational thinking and expression.