Pixelating Teacher Sentiments: Exploring Algorithmic Empathy via AI Photo Elicitation in Agricultural Education

Abstract

Pixelating Teacher Sentiments: Exploring Algorithmic Empathy via AI Photo Elicitation in Agricultural Education introduces a methodological tool for qualitative inquiry called Artificial Intelligence-Generative Emotional Elicitation and Experiential Mapping (AI-GEEEM). This proof of concept attempts to address the traditional research methods that often fail to capture the complex, pre-verbal emotional realities of teachers, a phenomenon. The AI-GEEEM method addresses this by leveraging generative AI to create a psychologically safe space for teachers to share their experiences. This approach is grounded in three established theoretical pillars to ensure rigor, ethical oversight, and psychological insight.