{"title":"Systems model for learning","authors":"P. Buriak, B. McNurlen, J. Harper","doi":"10.1109/FIE.1995.483022","DOIUrl":null,"url":null,"abstract":"Develops a model of learning that differs greatly from traditional or intuitive models. This hard system is specifically designed for the context of problem-solving/higher-order thinking, rather than automatic learning. Research in educational psychology and cognitive science provides the basis for the model. Learning is the integration of new knowledge/behaviors into a framework, and subsequently recalling what is relevant in the appropriate situation. To understand learning, we must consider how new information is received and the stages through which new information is processed as it progresses from immediate sensory experience to long-term storage. It is also important to understand how novices and experts organize, analyze or encode, and then retrieve necessary information. In this particular case, engineering students are the novices and engineering educators are the experts. Teaching consists of organizing, planning, delivering and evaluating the content of the subject area. Teaching problem-solving in science requires a deep understanding of the subject matter, as well as an appreciation of the characteristics of the students, of presentation skills, and of evaluation techniques. This study presents a soft systems model for the craft of teaching, and develops a hard systems model for the science of learning.","PeriodicalId":137465,"journal":{"name":"Proceedings Frontiers in Education 1995 25th Annual Conference. Engineering Education for the 21st Century","volume":"250 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Frontiers in Education 1995 25th Annual Conference. Engineering Education for the 21st Century","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FIE.1995.483022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Develops a model of learning that differs greatly from traditional or intuitive models. This hard system is specifically designed for the context of problem-solving/higher-order thinking, rather than automatic learning. Research in educational psychology and cognitive science provides the basis for the model. Learning is the integration of new knowledge/behaviors into a framework, and subsequently recalling what is relevant in the appropriate situation. To understand learning, we must consider how new information is received and the stages through which new information is processed as it progresses from immediate sensory experience to long-term storage. It is also important to understand how novices and experts organize, analyze or encode, and then retrieve necessary information. In this particular case, engineering students are the novices and engineering educators are the experts. Teaching consists of organizing, planning, delivering and evaluating the content of the subject area. Teaching problem-solving in science requires a deep understanding of the subject matter, as well as an appreciation of the characteristics of the students, of presentation skills, and of evaluation techniques. This study presents a soft systems model for the craft of teaching, and develops a hard systems model for the science of learning.
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学习系统模型
开发一种与传统或直觉模型大不相同的学习模型。这个硬系统是专门为解决问题/高阶思考而设计的,而不是自动学习。教育心理学和认知科学的研究为该模型提供了基础。学习是将新的知识/行为整合到一个框架中,然后在适当的情况下回忆起相关的内容。为了理解学习,我们必须考虑新信息是如何被接收的,以及新信息从即时感官体验到长期存储的过程中被处理的各个阶段。了解新手和专家如何组织、分析或编码,然后检索必要的信息也很重要。在这种特殊情况下,工程专业的学生是新手,而工程教育工作者是专家。教学包括组织、计划、传递和评估学科领域的内容。在科学教学中解决问题需要对主题有深刻的理解,也需要对学生的特点、表达技巧和评价技巧有深刻的理解。本研究提出了教学工艺的软系统模型,并开发了学习科学的硬系统模型。
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