Modeling Teachers’ Emotion Regulation and Psychological Capital for Human-Centered Workplace Technology

Abstract

Designing adaptive, human-centered workplace technologies requires robust empirical baselines of end-user affective competencies. To bridge organizational psychology and systems engineering, this study models teachers’ emotion regulation, emotional labor, and positive psychological functioning as foundational user-state parameters for computer information systems and Emotion AI design. Employing a quantitative descriptive-correlational methodology, empirical data were gathered from 276 public central school teachers using standardized diagnostic instruments. The findings revealed that users exhibit high normative levels of cognitive reappraisal, deep acting, authentic emotional expression, and psychological capital, particularly resilience. Comparative inferential analyses demonstrated that these emotional parameters remain invariant across teaching experience brackets, proving that a unified, standardized emotion-supportive software framework can effectively serve an entire workforce without age-segregated customization. Significant gender differences, however, highlight the necessity for gender-inclusive algorithmic calibration. Furthermore, positive interrelationships among internal regulation, external emotional displays, and psychological capital confirm an interconnected behavioral dependency. These results provide information systems designers with vital empirical specifications, establishing that next-generation enterprise software must embed Positive Computing principles and adaptive user interfaces to actively scaffold employee well-being.