Pixelating Teacher Sentiments: Exploring Algorithmic Empathy via AI Photo Elicitation in Agricultural Education
Year: 2025
Type: article
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.
DOI: 10.35099/yddr-mp13
Authors: Clemons, Christopher, Haddad, Becky
Institutions: Auburn University, University of Nebraska–Lincoln
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7080426134
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