Data Industry Competency for Post High School African American Males
There has been a great deal of news, discussion, and outcry regarding the lack of diversity in science, technology, engineering, and math (STEM) related fields, be it industry or academia. On many comparative lists regarding STEM students and workers, African American males are an unacceptably low percentage of the population. The problem is quite complex, and the reasons are numerous, including historic and present-day inequities, systemic social-political harms, higher education access and affordability, and difficulties obtaining acceptable levels of proficiency based on industry standards. Research shows supplying students with the resources, the state-of-the-art tools and innovations required to succeed help to stimulate engagement and improves outcomes. As our society becomes critically dependent on data, in all its many forms, the need for professionals in the field of data science and analytics is growing exponentially. Addressing the related educational and employment disparities in underrepresented populations should be a societal imperative, if for no other reason but to stave off enlarging the under-educated and under-employed populations. Increasing the understanding of how important it is to have unique, diverse, and inclusive data-driven decision making will benefits the whole of society. With Phenomenological Variant of Ecological Systems Theory (PVEST) as its grounding theoretical framework, this study takes a phenomenological research approach, utilizing the semi-structured interview method for data collection. Twenty-one participants from distinct industries including public, private, and non-profit, and who held rank positions within their companies were interviewed. Participants also aligned with the data analytics field as understood from the literature review. Participation was completely voluntary. Participants were not compensated in any way for their time. Utilizing both an inductive and deductive analytical approach, recorded and transcribed interviews were reduced into qualitative codes directly linked to the research objective. In turn, the qualitative codes merged and developed into categories and from those categories thematic structures emerged that served to illuminate the phenomenon and inform the findings. Findings show that a data analytics curriculum can provide an opportunity for not only post high school African American males, but interested parties from any number of groups, to participate in a real-world, problem-based data analytics project that will lead to a solid career in industry or in academics. Findings also show that the high level of ambiguity regarding data science versus data analytics curriculum, requisite skillsets, tools, and employment tasks requires much more attention in order to develop effective, successful training programs.
African American Males, Competency, Data Analytics, Data Science, Education
Networked Digital Library of Theses and Dissertations