CCE Theses and Dissertations

Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

College of Computing and Engineering

Advisor

Martha M. Snyder

Committee Member

Steven R. Terrell

Committee Member

Ling Wang

Abstract

Prior to the global COVID-19 pandemic, this study aimed to explore how exposure to information systems (IS) project management impacts perceptions of computing careers among high school female participants. Given the demand for computing professionals continues to grow, enrollment in some computing disciplines across institutions of higher education have experienced declining enrollments. Studies have shown that one of the reasons high school students do not enroll in computing disciplines is because they perceive computing as difficult, boring, and irrelevant.

As a computing discipline, information systems is focused on developing professionals who are able to integrate technologies into systems that run our organizations and societies. In addition to system integration, IS organizational alignment and project management are important skills for IS professionals. Information systems project management focuses on competencies, processes, tools, and techniques that can be used to manage computing projects. Project managers who work on IS projects integrate the project management lifecycle with the systems development lifecycle to create project objectives that include software, hardware, and telecommunications components. Therefore, to achieve successful outcomes, IS project managers must work effectively with a variety of professionals in other computing disciplines such as software engineering, computer science, information technology, and cybersecurity.

To address the research goal, a series of IS project management workshops were developed and partially implemented with a group of ten high school females. These workshops were designed to develop project management competencies, meet computing professionals, and create authentic project deliverables. The plan was to apply qualitative research methods such as collection and analysis of workshop artifacts, interviews, and the researcher’s reflexive journal, to determine how this experience impacted participants’ awareness and interest in computing careers.

The emergence of the COVID-19 global pandemic, however, had irrevocable effects on this study. With the closure of schools across the nation, the original study abruptly ended after two of six workshops were conducted. As a result, a new study was designed. The new study aimed to understand the lived experiences of teachers and the readiness and sustainability concerns they had after being abruptly transitioned from an in-person teaching environment to a fully online teaching environment. A questionnaire comprised of ten open-ended question was presented to a group of fifteen STEM teachers of the same school where the original workshops took place. Thirteen completed questionnaires were returned; data were then analyzed using a three-pronged approach: descriptive analysis, machine learning-based psycholinguistics analysis, and qualitative content analysis.

The descriptive analysis revealed verbosity among every participant and for every question. The machine learning-based psycholinguistics analysis produced rich psycholinguistic tone scores across seven dimensions: Analytical, Anger, Confident, Fear, Joy, Sadness, and Tentative. The qualitative content analysis reduced data from thirteen participants across ten questions to 11 primary codes, 26 secondary codes, and four thematic constructs: student needs, teacher needs, the role of school officials, and parent needs.

The study has practical implications for school officials, parents, students, and policy makers–specifically related to the technological impact of an unforeseen and widespread disruption of the education system.

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