A Comparison of SCAT and Ueno’s Qualitative Analysis as the Qualitative Data Analysis: A Study of Interview Data from a Kindergarten Director

DOI IR Web Site Open Access

Bibliographic Information

Other Title
  • 質的データ分析法としてのSCATとうえの式質的分析法の比較 : 幼稚園長のインタビューデータから
  • シツテキ データ ブンセキホウ ト シテ ノ SCAT ト ウエ ノ シキ シツテキ ブンセキホウ ノ ヒカク : ヨウチエンチョウ ノ インタビューデータ カラ

Search this article

Abstract

The purpose of this study is to compare the characteristics of SCAT (Steps for Coding and Theorization) and Ueno’s qualitative analysis as a form of qualitative data analysis applied to interview data from a kindergarten director. The subject and methods of the study are as follows. (1) We interviewed the director of Kindergarten A. (2) The research question asked why he started to run the child-based kindergarten. (3) We analyzed the interview data using SCAT. (4) We also analyzed the interview data using Ueno’s qualitative analysis. (5) We compared their characteristics. The analyses made the following points clear. First, the SCAT is characterized by the decontextualisation of the segmented text, step by step. By contrast, Ueno’s qualitative analysis is marked by its recontextualization through the mapping and charting of metadata. Second, when we use SCAT, we need to understand the theory of qualitative inquiry and must read the text over and over, analyzing it over time. However, the intellectual excitement when we discover the inherent meaning in the text is great. However, Ueno’s qualitative analysis is superior in terms of cost performance, time saved, and energy savings, though it does not convert qualitative data into words. With this approach, the intellectual excitement we felt when we discovered the meaning inherent in a text was not as great as when using SCAT.

Journal

Keywords

Details 詳細情報について

Report a problem

Back to top