Closing the legitimacy gap in university analytics: Ethical leadership, trust, and data governance in Chinese higher education
TL;DR
An Ethical Analytics Leadership framework is proposed in which transparency, dialogue, capacity building, and ethical governance reinforce trustworthy analytics, and explains how leaders navigate tensions between accountability and autonomy in data-intensive, highly centralized systems.
Abstract
Universities rapidly scale learning and administrative analytics to support strategic and operational decisions, yet staff acceptance often lags when data use appears opaque, compliance-driven, or misaligned with academic values. Drawing on a sequential explanatory mixed-methods study of 238 academic and administrative leaders in four comprehensive Chinese universities, with follow-up interviews sampled across high, medium, and low levels of trust, literacy, and governance, we find that leadership transparency and dialogue predict institutional trust in analytics, while perceived staff trust remains more limited and constrained by concerns about surveillance, fairness, and participation, with middle leaders improvising data literacy support and ethical safeguards in context. The article proposes an Ethical Analytics Leadership framework in which transparency, dialogue, capacity building, and ethical governance reinforce trustworthy analytics, and explains how leaders navigate tensions between accountability and autonomy in data-intensive, highly centralized systems.