Date
1-16-2025
Department
School of Education
Degree
Doctor of Philosophy in Education (PhD)
Chair
Richard A. Bragg
Keywords
AI, digital literacy, digital intelligence, education data literacy, artificial intelligence
Disciplines
Education
Recommended Citation
Harrell, Morgan V., "Data Literacy in the Age of Artificial Intelligence: A Hermeneutic Phenomenological Study" (2025). Doctoral Dissertations and Projects. 6433.
https://digitalcommons.liberty.edu/doctoral/6433
Abstract
The purpose of this hermeneutical phenomenological study is to explore the essential data and digital literacies for instructors in community colleges, trade schools, and vocational training programs located in the South to work with artificial intelligence (AI) effectively. The theory guiding this study is based on Max van Manen's framework on lived experiences and Paul Ricoeur's narrative theory, which is designed to enhance understanding of the perception and implementation of these literacies within an AI-augmented educational domain. As society's reliance on data continues to grow, it becomes essential to equip all citizens with the skills required for data literacy (Wolff et al., 2016). The central research question is: How do instructors perceive the role of digital literacy in preparing students for an AI-driven society? Employing a qualitative methodology, the researcher conducted in-depth interviews with 11 individual participants and eight participants in a focus group. A document analysis of the participants' responses provided a comprehensive view of the educational practices supporting digital and data literacy development. Through interviews and focus groups with instructors, the findings highlight a shift in digital literacy that encompasses technical proficiency, critical thinking, and ethical discernment. Participants expressed concerns about AI's potential to introduce and perpetuate biases in decision-making processes, especially in high-stakes fields such as finance, real estate, and education, where algorithmic outcomes can impact equity and opportunity. The findings show the importance of human oversight and suggest that AI should augment rather than replace human judgment, advocating for adaptive learning approaches that personalize education without sacrificing ethical integrity.
