Evaluating museum exhibits: Quantifying visitor experience and museum impact with user experience methodologies

IF 1 4区 社会学 0 HUMANITIES, MULTIDISCIPLINARY
Ellie King, M. P. Smith, Paul F. Wilson, Janet Stott, M. A. Williams
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引用次数: 0

Abstract

Underpinned by the Model for Museum Exhibit User Experience (MEUX; King et al., Visitor Studies, 2023, 26, 59), this paper develops and presents an evaluation methodology for museum exhibits that utilizes existing methodologies from the user experience sector adapted for the museum and cultural heritage sectors. Two studies are presented: an in‐depth evaluation of the Meat the Future exhibition at Oxford University Museum of Natural History and then a comparative study between this exhibition and two other permanent exhibits at the museum. Quantitative and qualitative data provide a nuanced picture of each exhibit from the visitor perspective and showcase the benefits of the MEUX methods of evaluation. Results show how three different exhibits are constructed in different ways, providing different visitor experiences and outcomes. They are directly compared with identify statistical differences, but do not impose a judgment as to whether any exhibit is better than another. With detailed, nuanced and rigorous data capturing visitor experiences of engaging with exhibits, the MEUX evaluation methodology allows for more sophisticated, standardized and efficient evaluation practices within the sector, with results that directly support further development of exhibits and exhibitions.
评估博物馆展品:利用用户体验方法量化游客体验和博物馆影响
本文以博物馆展览用户体验模型(MEUX;King 等人,《游客研究》,2023,26,59)为基础,开发并介绍了一种博物馆展览评估方法,该方法利用了用户体验领域的现有方法,并将其适用于博物馆和文化遗产领域。本文介绍了两项研究:一项是对牛津大学自然历史博物馆 "肉食未来 "展览的深入评估,另一项是该展览与博物馆其他两个常设展览之间的比较研究。定量和定性数据从参观者的角度对每个展览进行了细致入微的描述,并展示了 MEUX 评估方法的优势。结果显示了三个不同的展品是如何以不同的方式进行构建,为游客提供不同的体验和结果。它们通过直接比较来确定统计差异,但并不强加判断任何展品是否优于其他展品。MEUX 评估方法提供了详细、细致和严谨的数据,记录了参观者与展品接触的体验,使行业内的评估实践更加成熟、规范和高效,其结果直接支持了展品和展览的进一步发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Curator: The Museum Journal
Curator: The Museum Journal HUMANITIES, MULTIDISCIPLINARY-
CiteScore
1.70
自引率
10.00%
发文量
63
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