混合教学作为在线学习的常态化路径,在自主学习阶段面临学习者认知投入不足的困扰。概念图能够通过帮助学习者在学习过程中有意识地从学习材料中提取新信息并与已有知识建立连接以促进认知投入。因此,围绕概念图工具在混合教学自主学习...混合教学作为在线学习的常态化路径,在自主学习阶段面临学习者认知投入不足的困扰。概念图能够通过帮助学习者在学习过程中有意识地从学习材料中提取新信息并与已有知识建立连接以促进认知投入。因此,围绕概念图工具在混合教学自主学习阶段的应用问题,本研究基于ICAP (Interactive,Constructive, Active, and Passive)学习方式分类学理论、有意义学习理论和活动理论双驱动认知投入干预策略,设计了指向交互建构的学习活动流程和促进有意义交互的学习策略。学习活动流程设计引导学习者在自主学习阶段从参与被动学习活动向参与交互学习活动发展;学习策略设计为学习者参与建构类和交互类学习活动过程提供可操作性的认知策略,确保在自主学习的过程中有意义交互的发生。同时,通过准实验研究验证基于干预策略的混合教学的有效性。实验结果表明,基于干预策略的混合教学对于学习者知识水平以及以元认知意识和沟通能力为代表的高阶思维能力具有促进作用。展开更多
With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such disti...With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.展开更多
目的:系统评价概念图对护生及临床护士的评判性思维能力的影响效果。方法:通过检索中国知网(CNKI)、万方数据库、维普数据库(VIP)、PubMed、Web of Science、the Cochrane Library、EMbase等数据库,检索时限为建库至2021年3月1日,根据En...目的:系统评价概念图对护生及临床护士的评判性思维能力的影响效果。方法:通过检索中国知网(CNKI)、万方数据库、维普数据库(VIP)、PubMed、Web of Science、the Cochrane Library、EMbase等数据库,检索时限为建库至2021年3月1日,根据EndNote软件进行文献筛选和查重,对纳入的随机对照试验(RCT)或类实验研究文献采用RevMan 5.3软件进行数据合并分析。结果:共纳入9篇文献,采用随机效应模型分析,Meta分析结果显示,试验组护生及临床护士的评判性思维能力高于对照组[SMD=0.98,95%CI(0.57,1.39),P<0.00001];亚组分析结果显示,无论是国内还是国外,概念图均可提高护生及临床护士评判性思维能力[国内:SMD=0.76,95%CI(0.28,1.25),P=0.002;国外:SMD=1.11,95%CI(0.53,1.69),P=0.0002]。结论:现有证据表明,概念图应用于护理教学和临床实践中,可以提高护生及临床护士的评判性思维能力,可以为护理教学提供一种更好的学习方法。展开更多
文摘混合教学作为在线学习的常态化路径,在自主学习阶段面临学习者认知投入不足的困扰。概念图能够通过帮助学习者在学习过程中有意识地从学习材料中提取新信息并与已有知识建立连接以促进认知投入。因此,围绕概念图工具在混合教学自主学习阶段的应用问题,本研究基于ICAP (Interactive,Constructive, Active, and Passive)学习方式分类学理论、有意义学习理论和活动理论双驱动认知投入干预策略,设计了指向交互建构的学习活动流程和促进有意义交互的学习策略。学习活动流程设计引导学习者在自主学习阶段从参与被动学习活动向参与交互学习活动发展;学习策略设计为学习者参与建构类和交互类学习活动过程提供可操作性的认知策略,确保在自主学习的过程中有意义交互的发生。同时,通过准实验研究验证基于干预策略的混合教学的有效性。实验结果表明,基于干预策略的混合教学对于学习者知识水平以及以元认知意识和沟通能力为代表的高阶思维能力具有促进作用。
文摘With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.
