Date of Award


Degree Type

Open Access Dissertation

Degree Name

Education, PhD


School of Educational Studies

Dissertation or Thesis Committee Member

Gwen Garrison

Dissertation or Thesis Committee Member

Emilie Reagan

Dissertation or Thesis Committee Member

Frances Marie Gipson

Terms of Use & License Information

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Rights Information

© 2024 Kyle Perez Robinson


administrator recommendations, artificial intelligence, ecological systems model, teacher attrition, teacher retention, teacher shortage

Subject Categories

Education | Educational Administration and Supervision | Educational Leadership


The COVID-19 pandemic was an unprecedented event in modern educational history that resulted in a dramatic upheaval of the traditional school system. The shift from brick-and-mortar to virtual instruction resulted in profound anxiety and demand (Kush et al., 2021). As the quarantine ended, the return to the physical classroom brought with it new, unanticipated stressors such as COVID-19 safety protocols, shifts in student behavior, and pronounced learning gaps from virtual instruction. Coupled with existing tensions, many educators who had previously identified as career teachers became “likely pandemic leavers” as they departed the profession (Steiner, 2021). While there is ample research on teacher attrition and retention, given the gravity of the global pandemic, it is critical to investigate the factors teachers consider when making the choice to leave or stay teaching in the wake of the COVID-19 pandemic. This qualitative research conducted and analyzed thirty semi-structured interviews with teachers who taught in Southern California during the 2021-2022 school year. This study explored the factors that influence retention or attrition and how teachers weighed these factors during the decision-making process to stay in or leave the teaching profession. Framed through the ecological systems model, “factors” are unpacked as the varying levels of systems that shape the teaching profession. Analysis revealed that school administration teams play a substantial role in teachers’ decision to leave, while individual values and relationships with students and colleagues were weighed heavily in the decision to stay. Additionally, this research considered how the implementation of artificial intelligence (AI) assisted qualitative coding in Atlas.ti, while inexact, can function as a supplementary tool to inform the creation and application of a researcher-generated coding scheme.