Confucius’ “Teaching in Accordance with Students’ Aptitude” Realized Through AI: A Case of Philosophical Academic Writing Course Reform
DOI:
https://doi.org/10.66581/m9260b32Keywords:
individualized instruction, generative AI, philosophy writing, higher education, stealth assessmentAbstract
Large philosophy classes make it difficult to realize Confucius’ ideal of teaching in accordance with students’ aptitude. Conventional assessments poorly capture growth in higher-order writing skills. This article reports a 16-week reform of an undergraduate philosophical academic writing course that integrated an AI “learning companion,” structured “arguing-with-AI” activities, and peer-supported clinical tutoring. Drawing on work in intelligent tutoring, stealth assessment, and emerging research on generative AI in philosophy teaching, we designed an 8-week conceptual module plus an 8-week clinic-style supervision module. Using a quasi-experimental historical cohort design (N = 79), we compared rubric-based writing scores, process data from AI interaction logs, and student self-reports across cohorts. The AI-supported design was associated with greater increases in argumentative coherence, evidence use, and originality in this sample than a traditional design, and it expanded individualized feedback coverage. We discuss how generative AI can extend—but not replace—instructors’ capacity to enact individualized instruction at scale in a philosophy context, and outline implications for AI governance and academic integrity.
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Ethics Approval
This study involved human participants (undergraduate students). All procedures were reviewed and approved by the Ethics Committee of the School of Philosophy, Guizhou University. Participation in research components (surveys, interviews, and use of de-identified course data for analysis) was voluntary. Students provided written informed consent, were informed that non-participation would not affect their course grades, and could withdraw at any time without penalty. All data were anonymized prior to analysis.
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