With the rapid development of Artificial Intelligence Generated Content (AIGC) technology

the education sector is undergoing a profound transformation from digitalization to intelligence. Leveraging its powerful content generation capabilities

AIGC offers unprecedented opportunities for the personalized customization

dynamic updating

and multi-modal presentation of teaching resources. However

current applications of AIGC in educational scenarios still face severe challenges

including insufficient accuracy of generated content

prominent ethical risks

a lack of teacher competence in human-machine collaboration

and lagging evaluation systems. This paper aims to systematically review the status quo of AIGC-assisted teaching resource generation and deeply analyze core issues regarding technical reliability

educational adaptability

and ethical safety. On this basis

it proposes countermeasures such as constructing a "human-machine collaborative" generation paradigm

establishing a multi-level content audit mechanism

reshaping the teacher digital literacy system

and perfecting intelligent resource evaluation standards. Research indicates that through the dual drive of technological optimization and institutional innovation

the quality and applicability of AIGC-generated resources can be effectively improved

promoting supply-side reform in educational resources and ultimately achieving an organic unity of scaled education and personalized cultivation.