A Study on the Enhancement of Philosophical Literacy Driven by Generative AI: Taking the Cultivation of Dialectical Thinking in Marxist Philosophy Courses as a Starting Point

Abstract

In university classrooms, the Marxist Philosophy course bears the responsibility of cultivating students' philosophical literacy and dialectical thinking, but it also faces practical difficulties such as abstract concepts, disconnect from case studies, and insufficient student participation. The rapidly developing generative artificial intelligence (AI) of recent years has brought new tools to the classroom, but it also carries the risk of using only answers and no longer thinking. This paper takes the collaborative practice of generative AI-dialectical thinking as its main thread, and, guided by Marxist dialectics, proposes a three-loop advancement model of contradiction-connection-development, combining it with the Prompt-Reasoning-Critique-Refine (PRCR) cycle to construct a closed-loop teaching system that runs through pre-class, in-class, and post-class activities. From the perspectives of theoretical foundation, instructional design, process mechanisms, and quality assurance, the paper systematically discusses how generative AI, while adhering to Marxist positions, viewpoints, and methods, can serve as a scaffolding rather than a substitute for students to conduct contradiction analysis, connect history and reality, and engage in critical reflection. It also provides directly usable prompt templates and rubric examples. Research shows that as long as there are clear teaching objectives, appropriate process design, and necessary normative constraints, generative AI will not only not weaken students' thinking ability, but will also help promote the growth of their dialectical thinking and the overall improvement of their philosophical literacy.