Feasibility Analysis and Path Exploration of AI Intelligent Agents Intervening in University Teaching: A Case Study of the "College Students' Career Planning and Employment Guidance"

Abstract

In the context of the rapid development of artificial intelligence technology, AI agents are gradually penetrating into the teaching scenarios of higher education, promoting a profound transformation of teaching models. This paper takes the "College Students' Career Planning and Employment Guidance" course as the research object, based on the theories of educational informatization and intelligent teaching, systematically analyzes the practical feasibility of AI agents' involvement in university teaching, and explores the implementation paths from three dimensions: teaching objectives, teaching processes, and teaching evaluations. The research findings show that AI agents have significant advantages in personalized learning support, optimization of teaching resources allocation, and intelligent teaching evaluation, but still face challenges in data ethics, transformation of teacher roles, and technological dependence. This paper proposes a three-dimensional implementation path of "target reconfiguration - process integration - evaluation optimization", providing theoretical references and practical basis for the reform of university course teaching.