WIP: An Exploratory Sequential Mixed Methods Study on the Influence of Data Proficiency on Engineering Identity

This work-in-progress research article presents the latest findings from the survey development phase in a mixed methods study (Qual→ Quant). The study builds upon a previous qualitative investigation into the impact of data proficiency on the engineering identity of 52 undergraduate students across various engineering disciplines. The significance of this study lies in the recognition that data proficiency is a critical skill in modern engineering practice. While substantial research exists on developing engineering skills and competencies, limited attention has been paid to how proficiency with data influences the formation and development of an engineer's identity. The research questions include: How does data proficiency influence the development of engineering identity components-interest, competence, and recognition-among undergraduate engineering students across different disciplines and academic levels? The ongoing quantitative phase aims to reinforce and expand upon these qualitative insights. This phase will involve a larger sample of engineering students from different disciplines and year levels (freshmen, sophomores, juniors, and seniors). Data will be collected using survey instruments designed to assess data proficiency through the How People Learn (HPL) framework and measure engineering identity using the survey instrument developed by Godwin (2018). The quantitative study will (1) validate the themes that emerged from the previous qualitative study as well as confirm whether the insights gathered from a smaller, in-depth qualitative sample hold true across a larger population and (2) provide a more comprehensive understanding of how data proficiency influences the key components of engineering identity across a broader spectrum of students. The findings of this research will be of significant benefit to both researchers and instructors by shedding light on the role of data proficiency in shaping engineering identity. This will inform future engineering curricula with a more holistic approach to developing engineering skills and identities in a data-driven world.