Abstract:

The rapid rise of agentic Artificial Intelligence (AI)—systems capable of autonomous, goal-oriented behavior—presents profound challenges to higher education governance. While AI offers new efficiencies in advising and administration, it simultaneously risks eroding academic autonomy and ethical accountability. This paper introduces the Human-Oriented Teaching (HOT) framework, designed to safeguard the human dimension of teaching and decision-making by ensuring that AI tools serve as extensions of, rather than replacements for, human agency.

The study aims to develop a measurable and ethically grounded model of “Dynamic Product and Process Regulation’ that aligns technological innovation with human-centered governance. It advances a theoretical and empirical approach for integrating AI responsibly into higher education systems, grounded in the principles of social justice, transparency, and public interest. HOT is operationalized as a Higher-Order Construct (HOC), composed of Lower-Order Constructs (LOCs) including AI usability, personalization, and educator empathy. Recent empirical research involving 1,200 university students demonstrates that AI-driven academic advising systems significantly enhance student satisfaction, academic confidence, and the alignment of academic choices with long-term career pathways. The HOT framework integrates the principles of social justice, cultural values, transparency, and public interest into a measurable and ethically grounded governance model called ‘Dynamic Product and Process Regulation (D.2P.R) in higher education. This model introduces two key mechanisms:
1. Regulation by product – embedding transparency, fairness, and human oversight directly into AI content production mechanism.
2. Regulation by process – establishing auditable decision logs for all autonomous actions to preserve accountability and human discretion into process mechanism.

Finally, the HOT model transforms philosophical concerns about AI ethics into a verifiable research and governance strategy. By prioritizing human agency, contextual judgment, ethical design and public interest, it provides higher education institutions with a replicable approach for balancing innovation, trust, and academic integrity in the age of agentic AI.

Keywords:

Agentic Artificial Intelligence; Higher Education; Human-Oriented Teaching; Ethical Governance; Public interest; Dynamic Product and Process Regulation; Student Satisfaction; Educational Innovation.