Núcleo básico en el análisis de datos cualitativos: pasos, técnicas de identificación de temas y formas de presentación de resultados

Pablo Ezequiel Flores Kanter
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引用次数: 9

Abstract

Within the research process, the analysis of the data emerges as one of the most important steps. In qualitative research, the analysis of data is a difficult task for even the most experienced researchers and often brings up many doubts about the way to implement it. It is therefore necessary to have material that facilitates the analysis process. Even though there are numerous manuals that focus on the analysis of qualitative data, researchers often can be confused with the large number of names that this type of analysis receives (e.g. Thematic Analysis, Content Analysis) or with the various qualitative methods (e.g. Phenomenology, Grounded Theory) that are available. Each of these qualitative approaches presents a particular language to detail the research process, which makes it difficult to recognize common aspects shared by these methods. Recently, the American Psychological Association has emphasized the need to identify, within the various qualitative methods and procedures, shared standards for reporting this type of work. In agreement with the above, several qualitative researchers have pointed out that beyond the aforementioned diversity it is possible to identify a basic core with regard to qualitative analysis, without having to match the different perspectives of the qualitative method, such as Grounded Theory, Ethnography ore Phenomenology. Focusing on this communality will facilitate a simpler and clearer approach to the data analysis process. The analysis process mainly involves 1) data condensation, and 2) presentation of results. Following this line, the present manuscript aims to: (a) develop what the basic core of data analysis consists of, (b) show the necessary steps to carry out this analysis process, (c) review specific techniques for the detection of categories, (d) present examples using the Atlas.ti software, and (e) show the possible ways of presenting the results. Researchers have realized the importance of having methodological works that facilitate the analysis of qualitative data, and allow answering the question: What does qualitative analysis look like in practice?. The development of this type of work pretends on the one hand to facilitate the understanding of the process of qualitative data analysis and, on the other hand, serve to shape better and in a more standard way which was the data analysis procedure applied in the respective investigations. This material should be taken as a first step in the understanding of the process, and it should not be understood that the qualitative analysis is reduced only to what is developed in this article. For example, in the first level grouping step or first coding cycle, the researcher can make use of 25 different types or forms of coding (e.g., live coding). Even so, the development of works such as the present manuscript is intended to facilitate the understanding and reporting the process of qualitative data analysis. Beyond the name with which the researcher calls the analysis procedure carried out, it is relevant to report in his works the basic steps (i.e. Identification, First and Second Level of Categorization), and the specific techniques used to detect categories or topics (e.g. repetition or similarities). Likewise, it is advisable to follow the guidelines recently published by the APA for the publication of qualitative research. We hope that this material will be useful especially for new researchers who need an introductory text to carry out the qualitative data analysis.
定性数据分析的核心:步骤、主题识别技术和结果展示形式
在研究过程中,数据分析是最重要的步骤之一。在定性研究中,即使是最有经验的研究人员,对数据的分析也是一项艰巨的任务,并且常常会对实施数据的方式产生许多疑问。因此,有必要提供便于分析过程的材料。尽管有许多手册侧重于定性数据的分析,但研究人员经常会被这种类型的分析所接受的大量名称(例如主题分析,内容分析)或可用的各种定性方法(例如现象学,扎根理论)所混淆。这些定性方法中的每一种都呈现出一种特定的语言来详细描述研究过程,这使得很难识别这些方法共享的共同方面。最近,美国心理学会强调,有必要在各种定性方法和程序中确定报告这类工作的共同标准。与上述观点一致,一些定性研究人员指出,除了上述多样性之外,有可能确定定性分析的基本核心,而不必匹配定性方法的不同视角,如扎根理论、民族志或现象学。注重这种共同性将有助于对数据分析过程采取更简单和更清晰的方法。分析过程主要包括:1)数据浓缩;2)结果呈现。沿着这条线,本手稿旨在:(a)发展数据分析的基本核心组成,(b)显示执行这一分析过程的必要步骤,(c)回顾类别检测的具体技术,(d)使用Atlas提供示例。Ti软件和(e)显示了显示结果的可能方法。研究人员已经意识到方法论工作的重要性,这些工作可以促进定性数据的分析,并允许回答以下问题:定性分析在实践中是什么样子的?这类工作的发展一方面是为了促进对定性数据分析过程的理解,另一方面是为了以更好和更标准的方式形成在各自调查中应用的数据分析程序。本材料应作为理解过程的第一步,不应理解定性分析仅局限于本文所阐述的内容。例如,在第一级分组步骤或第一个编码周期中,研究人员可以使用25种不同类型或形式的编码(例如,实时编码)。即便如此,诸如本手稿等作品的发展旨在促进对定性数据分析过程的理解和报告。除了研究人员称之为分析过程的名称之外,在他的作品中报告基本步骤(即识别,第一和第二级分类)以及用于检测类别或主题的具体技术(例如重复或相似性)是相关的。同样,遵循APA最近发布的关于发表定性研究的指导方针也是明智的。我们希望这一材料将是有用的,特别是新的研究人员谁需要一个介绍性的文本进行定性数据分析。
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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