Establishing Trustworthiness Through Algorithmic Approaches to Qualitative Research

ABSTRACT

Establishing trustworthiness is a fundamental component of qualitative research. In the following paper, we document how combining natural language processing (NLP), with human analysis by researchers, can help analysts develop insights from qualitative data and establish trustworthiness for the analysis process. We document the affordances of such an approach to strengthen three specific aspects of trustworthiness in qualitative research credibility, dependability, and confirmability. We illustrate this workflow and shed light on its implications for trustworthiness from our own, recent research study of educators’ experiences with the 2020 COVID-19 pandemic;a context that compelled our research team to analyze our data efficiently to best aid the community, but also establish rigor and trustworthiness of our process. © 2021, Springer Nature Switzerland AG.