Data Collected but Excluded in Qualitative Research in/on Informal Learning Environments (Poster 4)

• In Event: When Nothing Is Something: Null Results in Informal Learning Research

Abstract

Objectives & Perspectives: This poster aims to discuss how certain data would be selected to be analyzed in qualitative research studies in/ on informal learning environments. Qualitative research does not begin with very-specifically-determined inquiries (Glesne, 2016), so it often leads scholars to collect a huge amount of data. Especially with the development of technology, creative and diverse types of data have been increasingly used (e.g., Jung et al., 2020), which, in turn, makes their data set even more enormous. In a research study, however, it is impossible to show all data collected, and some kinds of “selection” process, such as strategic sampling, should be involved based on research questions. This poster will highlight the process of such selection in qualitative research and discuss data that can be interesting but has to be excluded throughout the process.

Methods: This poster will present several cases and themes found about qualitative data that were not included in analysis from several studies of the author. For this, the author takes the autoethnographic approach (Ellis et al., 2011) to reflect on the process of data selection and exclusion in their previous research projects.

Data Sources: This poster will revisit the authors’ previous projects on informal learning environments (e.g., science museum), through which they collected diverse types of qualitative data, such as video recordings, photos, interview transcripts, and field notes.
Results: In many of the author’s studies, strategic sampling was used to select data as they narrowed down their research questions and focuses. For example, in a study about family learning and interest at a science museum, as they decided to focus on each child’s interest and experience, many interesting episodes between multiple children were excluded. In this case, data that were not selected may be used for other studies with different research focuses; many qualitative researchers would agree that they had much data that were excluded so far but waiting to be analyzed in the “future”—although nobody knows when and how yet.

Also, the existence of conversation critically mattered to data exclusion because talks were usually the most common unit to be analyzed. It was hard to evidence the author’s arguments by analyzing only non-verbal interactions without verbal talk; interpreting just non-verbal elements were often challenged, “how did you know this gesture meant that?” Thus, some episodes where participants did not talk much were excluded even though they seemed to be interesting. Even though an interpretive approach is the core of qualitative research, the possibility of too many interpretations is often an obstacle. (The poster will share actual data, such as transcripts and screen shots, with audience.)

Significance: While null results are mainly discussed in quantitative research studies, highlighting the value of data that are not selected in qualitative studies is also meaningful. This poster will spark more in-depth conversations among qualitative researchers in/on informal settings about the data collection and analysis processes and how to re-think about data that are not included because of the sampling criteria but still can be meaningful.

Author

• Yong Ju Jung, University of Oklahoma