A New Application of Raymond Padilla’s Unfolding Matrix in Framing Qualitative Data and the Follow-Up Activities for Educational Research

Abstract

This article introduces the new application of Raymond Padilla's unfolding matrix in setting boundaries for postcollection qualitative data in educational research. It focuses on displaying the sample ways of using Padilla's technique to solve the common problems of qualitative research when the researcher may have collected unnecessary data or may have missed important data in certain research. Using the sample of a real educational research aims to illustrate how this technique is used and modified to be different from its original versions. This article would call for attention and be helpful to any researchers with qualitative data of similar research contexts and designs.Keywords unfolding matrix, Padilla's unfolding matrix, technique for qualitative data, framing qualitative data, post-data collection What Is Already Known?In qualitative research, researchers tend to design and make appropriate estimation for their samples, data, and how the data would be analyzed. The collected data in a research are usually framed before the completion of the collecting process. This protocol is popular and commonly used among the researchers. What This Paper Adds?This paper adds a new solution for the case when the data collection turns to be too huge and exceeds the estimation before conducting the research. When the researchers collect a lot of data and the scale of these data exceeding all the possible slots. The researchers should find a way to frame the data so that they will not miss any pieces of information during the analysis process. The new application, described in this paper, would facilitate the process of framing data in the stage of post-collection data. The newbie researchers of qualitative methods would have one more option for their academic practices.The inquiry of learning about Raymond Padilla's unfolding matrix arose during the stage of sorting and framing the collection of qualitative data for my doctoral studies. The problem was not estimated in the earlier stages until the collection of data reached over 62,000 words from interviews and feedback.Regardless of the reliability and validity of the tools and assuming that research methods have been used correctly for that process, this huge collection created the needs for an essential way to set boundaries for answering the research questions and analyze these qualitative data.At the time Padilla's 1 unfolding matrix was introduced, the challenges seemed to be resolved until mastering the process of self-studying and figured out how the unfolding matrix should be understood and applied to the current set of data. This technique was soon recognized to be good for qualitative acquisition and analyses (Padilla, 1994). However, the unfolding matrix is a technique for pre-data collection as described in Padilla's book chapter about it.The new application of the unfolding matrix in this article is especially viable because the research leading to this technique has large qualitative data sets which contain enough data to

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