ABSTRACT

This paper presents and illustrates Interpretive Clustering, an innovative and original method of qualitative analysis of Repertory Grid data. Repertory Grids are a popular and flexible method of research, but they have primarily been used to gather data that are analysed quantitatively. Although many researchers have used Grids more qualitatively, this is often limited to a content analysis of the elicited constructs across a sample of participants. Interpretive Clustering is a participant-led method which uses the grid data idiographically to explore how a participant’s construing may ‘cluster’ around one or more issues. We show how this is quite different from a thematic analysis, and discuss how Interpretive Clustering can provide insights that are complementary to those gained from methods like thematic analysis. We conclude with suggestions for how this method, which we argue bridges the qualitative/quantitative divide, might be used in future research.

摘要

本文介绍并说明了解释性聚类，这是一种对 Repertory Grid 数据进行定性分析的创新和原创方法。Repertory Grids 是一种流行且灵活的研究方法，但它们主要用于收集定量分析的数据。尽管许多研究人员更定性地使用了网格，但这通常仅限于对参与者样本中的引出结构进行内容分析。解释性聚类是一种参与者主导的方法，它使用表格数据来探索参与者的解释如何围绕一个或多个问题“聚类”。我们展示了这与主题分析有何不同，并讨论了解释性聚类如何提供与从主题分析等方法中获得的见解相辅相成的见解。