Systematic qualitative data management (SQDM) during an interpretive action research

Abstract

This paper presents the systematic way of data management in an action research to explore the interplay of mathematical thinking processes and mathematical sense making experiences of first year engineering students. The transitional impact of future engineers from school mathematics to engineering mathematics is explored by collecting data through multiple techniques and methods. The interpretivist epistemology and constructivist theoretical perspective during this action research demanded a rigorous qualitative research process and extensive data collection using emergent methods and techniques. This paper would address the queries like what data to collect and manage and how to manage it during this research process. Data management became vital for securing and utilizing the data in a proper way throughout our research. Managing the data effectively also enabled us to risk free data, accuracy, verifiability, and improved productivity of the research. Properly managed data would easily be preserved and reanalyzed in future with new analysis techniques. During this research, the digital and nondigital data, documentation and meta-data were also collected. We used multiple softwares e.g. Microsoft Excel, Word and NVivo10 to manage the data. Documentation helped us to be precise and holistic to further utilize the data for interpretive analysis.