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Academic Stewardship through AI-Enabled Learning Governance: Ethical Systems for Inclusive Learner Support in Higher Education

Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Artificial intelligence is increasingly embedded in higher education through learning analytics, automated feedback, generative AI tools, academic advising, early-alert systems, and student-support chatbots. In Chinese higher education, these developments create opportunities for scalable learner support but also raise ethical concerns related to privacy, bias, transparency, accountability, learner agency, and inclusion. This study develops and examines an ethical academic stewardship framework for AI-enabled learning governance in Chinese higher education. Using a sequential explanatory mixed-methods design, survey data were collected from 628 respondents across six stakeholder groups in selected higher education institutions in Sichuan Province, followed by semi-structured interviews. Results showed high expectations for human oversight (M = 4.18, SD = 0.62), learner agency (M = 4.11, SD = 0.65), inclusive support (M = 4.09, SD = 0.66), and privacy protection (M = 4.06, SD = 0.68), while transparency perception (M = 3.21, SD = 0.76) and governance readiness (M = 3.37, SD = 0.74) were comparatively lower. Regression analysis explained 58% of the variance in governance readiness, with institutional policy clarity (β = .29), transparency (β = .24), human oversight (β = .18), and inclusive support (β = .16) emerging as key predictors. Qualitative findings further emphasized visible data rules, human review, bias control, accessibility, and appeal mechanisms. The study contributes a practical framework connecting institutional responsibility, data stewardship, algorithmic accountability, human-centered intervention, and inclusive learner outcomes.
DOI: 10.21203/rs.3.rs-9759894/v1
Language: English
Open Access status: green
OpenAlex ID: W7161970825
Cites: 36
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Related to: 10