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Title: Connecting Dots: Coding Multiple Data Sources to Enhance Qualitative Analysis
This research paper elaborates on the process used by a team of researchers to create a codebook from interviews of Civil Engineers who included students, professors, and professionals, solving ill-structured problems. The participants solved two ill-structured problems while speaking aloud their thought process. In addition to recording the participant verbalization, the solution to their problems were also collected with the use of a smart pen. Creating a codebook from interviews is a key element of qualitative analysis forming the basis for coding. While individuals can create codebooks for analysis, a team-based approach is advantageous especially when dealing with large amounts of data. A team-based approach involves an iterative process of inter-rater reliability essential to the trustworthiness of the data obtained by coding. In addition to coding the transcripts as a team, which consisted of novice, intermediate, and experts in the engineering education field, the audio and written solution to the problems were also coded. The use of multiple data sources to obtain data, and not just the verbatim transcripts, is lesser studied in engineering education literature and provides opportunities for a more detailed qualitative analysis. Initial codes were created from existing literature, which were refined through an iterative process. This process consisted of coding data, team consensus on coded data, codebook refinement, and recoding data with the refined codes. Results show that coding verbatim transcripts might not provide an accurate representation of the problem-solving processes participants used to solve the ill-structured problem. Benefits, challenges and recommendations regarding the use of multiple sources to obtain data are discussed while considering the amount of time required to conduct such analysis.  more » « less
Award ID(s):
1712195
NSF-PAR ID:
10104585
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
ASEE Annual Conference proceedings
ISSN:
1524-4644
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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