Teaching Spatial Data Analysis: A Case Study with Recommendations

IF 2.2 Q2 PUBLIC ADMINISTRATION Nonprofit Policy Forum Pub Date : 2023-07-25 DOI:10.1515/npf-2022-0044
Duncan J. Mayer, R. Fischer
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Abstract

Abstract Learning from data is a valuable skill for nonprofit professionals and researchers. Often, data have a spatial component, and data relevant to the nonprofit sector are no exception. Understanding spatial aspects of the nonprofit sector may provide immense value to social entrepreneurs, funders, and policy makers, by guiding programmatic decisions, facilitating resource allocation, and development policy. As a result, spatial thinking has become an essential component of critical thinking and decision making among nonprofit professionals. The goal of this case study is to support and encourage instruction of spatial data analysis and spatial thinking in nonprofit studies. The case study presents a local nonprofit data set, along with open data and code, to assist the instructors teaching spatial aspects of the nonprofit sector. Pedagogical approaches are discussed.
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空间数据分析教学:个案研究及建议
从数据中学习对于非营利专业人员和研究人员来说是一项宝贵的技能。通常,数据具有空间成分,与非营利部门相关的数据也不例外。了解非营利部门的空间方面可以为社会企业家、资助者和政策制定者提供巨大的价值,通过指导规划决策、促进资源分配和发展政策。因此,空间思维已经成为非营利专业人士批判性思维和决策的重要组成部分。本案例研究的目的是支持和鼓励非营利研究中空间数据分析和空间思维的指导。本案例研究提供了一个本地非营利数据集,以及开放数据和代码,以帮助教师教授非营利部门的空间方面。讨论了教学方法。
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来源期刊
Nonprofit Policy Forum
Nonprofit Policy Forum PUBLIC ADMINISTRATION-
CiteScore
2.80
自引率
18.80%
发文量
23
审稿时长
7 weeks
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