Combining Algorithmic Approaches and Human Insights to Establish Trustworthiness in Qualitative Research

• In Event: Working With Context, Collaboration, Challenge, Connections, and Combination in Mixed Methods

Abstract

Establishing trustworthiness is a fundamental step towards establishing rigor in qualitative research. In this paper, we examine the feasibility of combining algorithmic approaches with human analysis to develop insights from qualitative data and establish trustworthiness. We provide illustrative workflows based on our ongoing analysis of recent interviews with educators about their experiences in the COVID-19 pandemic—a situation that demanded time-sensitive insights to support the community, as well as rigor in research analyses. In our process of generating insights from algorithmic approaches and human interpretation of a qualitative data corpus, we outline some steps to establish three specific aspects of trustworthiness: credibility, dependability, and confirmability.

Authors

• Ha Nguyen, University of California - Irvine

• June Ahn, University of California, Irvine

• Ashlee B. Belgrave, University of California - Irvine

• Jiwon Lee, University of California - Irvine

• Lora Cawelti, University of California - Irvine

• Ha Eun Kim, University of California - Irvine

• Yenda Prado, University of California - Irvine

• Rossella Santagata, University of California - Irvine

• Adriana Villavicencio, University of California - Irvine