From Design to Replication: A Zero-Code AIGC Workflow for Blended Teaching Reform in the Marketing Channels Course

Abstract

This paper reports the design and preliminary implementation of a blended teaching model for Marketing Channels, a core compulsory course of the Marketing major, in which AI-generated content (AIGC) tools and curriculum-based ideological and political education (CIPE) are integrated. The traditional classroom of the course suffers from lecture-dominated delivery, delayed feedback, static cases, label-style value inculcation, and a closed-book final examination. We restructure each session into a four-phase cycle: AI-generated contextual introduction, project-based task solving, ideological micro-debate, and AI instant feedback. A zero-code “light AI application” workflow built on a structured prompt library allows non-technical teachers to generate localized cases, dynamic data tables, and micro-videos on demand. A “channel justice” thematic thread runs through knowledge points such as channel functions, channel conflict, and online channels. The closed-book examination is replaced by a process-oriented system that combines AI instant feedback, peer review, teacher value comments, and an AI-assisted channel diagnosis report. This paper focuses on the design side of the reform: how a college-level teaching reform project turns an AI-empowerment scheme into an operable workflow, a process-oriented assessment system, and a replication plan for related courses. For non-technical teachers, this workflow gives a practical, low-cost way to use generative artificial intelligence without sacrificing the teacher's role in value guidance.