Teaching Spatial Data Analysis: A Case Study with Recommendations

Autor: Mayer Duncan J., Fischer Robert L.
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Nonprofit Policy Forum, Vol 15, Iss 1, Pp 71-82 (2023)
Druh dokumentu: article
ISSN: 2154-3348
DOI: 10.1515/npf-2022-0044
Popis: 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.
Databáze: Directory of Open Access Journals
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