Research on the Innovation of Blended Course Construction Models Based on AIGC

Abstract

Generative artificial intelligence is changing the form of teaching materials, and the old model of blended learning courses can no longer meet the new demand for pre-set modules, linear interaction and fixed assessments. The purpose of the three new ideas in this paper is to put forward new ideas for the model of blended courses with AIGC, build a three-level system for identifying problems in traditional architecture, redefine course elements, design a three-tier structure for human-machine collaboration, develop a dynamic construction method for knowledge units based on multimodal semantics, apply adaptive path orchestration with real-time feedback and generative models, promote a change in assessment from measuring outcomes to observing processes by collecting all kinds of data and AIGC, and establish streaming analysis and double-loop closed-loop adjustment methods. The above offer the theoretical and technical basis for the adaptive construction of blended courses.