Generative Ai Ethics in School Leadership as a Determinant of Teachers’ Professional Identity in a Chinese Educational Institution

Resumen

There are several opportunities and difficult ethical issues associated with the quick adoption of generative artificial intelligence (GenAI) in higher education. While there are some studies that examine the connection between ethical leadership and teachers' professional identity (TPI), very few have examined this relationship. This quantitative comparative-correlational research in Guangdong University of Science and Technology, China, explores the relationship between TPI and Ethics in School Leadership (ESL) as related to GenAI. The sample consisted of 250 teachers who completed a questionnaire that measures 96 items across the six TPI dimensions (e.g., self-concept and role perception, motivation and commitment, emotional and affective orientation, psychological resilience) and 10 GenAI ethics dimensions (e.g., policy and governance architecture, data governance, bias and fairness controls, continuous monitoring). The results indicated that the ethics of GenAI were assessed at a higher level than midway (overall M = 3.25/4), with participatory governance and continuous monitoring proving to be the most positively rated ethics. Furthermore, TPI was positively evaluated (M = 3.23/4), particularly with regards to affective and emotional orientation. ANOVAs showed that there were no significant differences in age or type of AI or academic rank. The psychological resilience scores were 3.35 for teachers with 1–5 years of experience and 3.13 for teachers with 16+ years of experience. But there was significant variation in psychological resilience across years of service (F = 3.521, p =.016). One of the most important results was total TPI being positively associated with GenAI ethics (r =.664, p <.001). Specifically, data governance correlated positively with emotional trust (r =.556), equity (r =.558) and policy clarity (r =.569) with commitment. The findings highlight the importance of an integrated theoretical approach that combines identity theory and deontological ethics, as ethical AI governance contributes to higher trust in the organisation, protects teachers' professional autonomy and sets clear expectations, which all support the empowerment of teachers' professional identities. Some practical tips include enhancing data and authoring requirements, providing targeted psychological assistance to senior teachers, keeping participatory governance procedures, and conducting AI ethics training for discipline-specific teachers.