建构主义分析:利用数据为更多的参观者提供更深入的博物馆体验——来自学习科学的教训

IF 1.6 Q3 HOSPITALITY, LEISURE, SPORT & TOURISM Visitor Studies Pub Date : 2017-01-02 DOI:10.1080/10645578.2017.1297116
M. Berland
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引用次数: 4

摘要

本文定义并概述了建构主义分析,这是一个框架,用于理解我们用高级数据分析构建的叙事如何、在何处以及何时能够影响非正式学习环境(如博物馆)中的积极社会变革。基于这个框架,我提出了三个核心问题:研究人员如何使用分析来了解不同的访问者认为有价值的东西?我们如何使用分析来帮助更多的访问者发现价值,并在他们发现价值时改善访问者的体验?我们如何以许多不同的利益相关者认为有价值的方式来呈现和构建分析?然后,我提出了可能的途径,既可以扩展当前的建构主义分析工作,又可以开发积极、有效和数据丰富的叙事的新角度。
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Constructivist Analytics: Using Data to Enable Deeper Museum Experiences for More Visitors—Lessons from the Learning Sciences
ABSTRACT This article defines and outlines constructivist analytics, a framework for understanding how, where, and when the narratives we construct with advanced data analysis can affect positive social change in informal learning environments (such as museums). I ask three core questions based on this framework: How can researchers use analytics to understand what different visitors find valuable? How can we use analytics to help more visitors find value and to improve visitors' experiences when they find value? How can we present and structure analytics in ways that many different stakeholders find valuable? I then suggest possible avenues for both expanding current work in constructivist analytics and developing new angles on positive, effective, and data-rich narratives.
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来源期刊
Visitor Studies
Visitor Studies HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
2.90
自引率
13.30%
发文量
9
期刊最新文献
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