Date of Award

7-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mathematics and Systems Engineering

First Advisor

Joo Young Park

Second Advisor

Thomas Marcinkowski

Third Advisor

Xianqi Li

Fourth Advisor

John E. Deaton

Abstract

This study originally aimed to construct a theoretical model of cognitive maps reflecting astronauts’ pursuit of excellence, building HTH Model (Heavenly Hour, Terrain Triumph, Human Harmony). A second purpose emerged organically: developing a framework for ethical human-AI collaboration in qualitative-driven, computationally-enhanced, mixed-methods research, resulting in GOLDEN Framework (Ground, Operate, Lead, Deepen, Ethics, Nature). Integrating Interpretative Phenomenological Analysis with grounded theory, the researcher conducted nine semi-structured interviews with nine retired American astronauts and four of their partners to explore lifelong sensemaking narratives. GOLDEN Framework governed a six-stage protocol for ethical, reflexive human-AI collaboration spanning three AI tool types: AI CAQDAS, AI Chatbots, and AI Notebook, yielding 92 axial categories and 20 selective themes, from which three middle-range theories emerged, unified through ISEE across HTH Model’s chronosystem, ecosystem and identity system. Theoretically, HTH Model offers a cognitive-mapping architecture across these three interlocking systems, explaining how astronauts construct self-identity through pivotal moments and formative environments. Methodologically, the Prism Coding Principles and the I-AI Four-Pass Workflow were developed under the GOLDEN Framework’s ethical governance, aligned with AI4People principles. The Bicameral Theorizing Model formalizes the researcher’s dual theoretical contribution: Form, the structural and locational half, and Flow, the transformational and teleological half—both substantively theorized by the researcher, with AI-generated propositions serving as analytical catalysts that are ultimately synthesized and transcended. This dynamic, Human-AI Synergistic Integrity, reflects the emergent alignment between human ethical agency and AI operational capacity, rendering qualitative inquiry both computationally powerful and irreducibly human.

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