Five Guiding Principles for Navigating Artificial Intelligence in Students as Partners Practice to Preserve Pedagogical Trust

Synthesis: Matthews (2025), in an editorial for the International Journal for Students as Partners, argues that Trust is fundamental to pedagogical relationships and therefore to students-as-partners practice in the age of AI. She warns that AI advances have amplified deficit views of students as cheaters or victims, a framing that risks fracturing learner–teacher relationships — especially when 83% of students in a large multi-institutional study (8,000+ respondents) reported using AI. Against the rise of "AI shame" and surveillance, she advocates pedagogical trust — a confident, reciprocal learning relationship open to uncertainty and co-navigated through dialogic decision-making and shared sense-making. To guide practice, she offers five principles for navigating GenAI together with students: (1) cultivate open and curious conversations; (2) acknowledge the emotional and vulnerable lived experiences of AI use; (3) make the role of AI visible and negotiable in learning activities; (4) create consistent opportunities for shared learning and reflection; and (5) ground ethical norms in shared values and a collective moral compass. Each principle pairs with questions for educators and students to explore together, positioning partnership as a counter to AI shame and surveillance.

Pedagogical Trust in the Age of AI

Trust has always underpinned pedagogical relationships, enabling or limiting the possibilities for partnership, participation, and learning. Matthews draws on the conception of trust as "a confident relationship with the unknown" (Botsman, 2017) to argue that higher education now confronts the deep unknown of Generative AI. In response, she advocates pedagogical trust — a confident, reciprocal learning relationship between students and teachers that is open to uncertainty and co-navigated through dialogic decision-making. This framing casts learning as a fundamentally social, relational process of meaning-making, growth, and connection, echoing arguments that AI advances should reaffirm — rather than displace — the centrality of human relationships in Higher Ed.

Students-as-partners practice emerged precisely as a challenge to the entrenched assumption that students cannot be trusted to collaborate alongside staff in shaping teaching, learning, and assessment (Cook-Sather et al., 2021). Matthews warns that advances in AI have amplified deficit views of students as either cheaters or victims of inadequate education, threatening to fracture learner–teacher relationships and limit collective capacity to respond to AI. The worry is amplified by a large multi-institutional study in which 83% of over 8,000 students reported using AI (Chung et al., 2025), and by evidence that roughly half used AI for Feedback even while recognising it may be less reliable than human teacher feedback (Henderson et al., 2025).

Partnership as Counter to AI Shame and Surveillance

Matthews observes a worrying trend, exemplified at her own university, of "AI shame" shutting down conversations about AI use — many people feel afraid to admit they use AI or to discuss its environmental and social harms, fearing judgment or trouble. When conversations close off, the trust sustaining learning partnerships risks being fractured. She positions student–staff partnership as the counter-narrative: an open, non-judgmental invitation that honours the relational foundations of education. Emerging partnership-based practices include students and staff co-creating how-to guides on AI (University of Sydney), co-designing an AI policy in first-year writing courses (Georgetown University), and co-creating and co-reflecting on AI in assessment within medical programs (University College London). These collaborative explorations foster — instead of fracture — pedagogical relationships through shared sense-making.

Matthews draws on Bearman and Ajjawi's (2023) metaphor of "black box pedagogy," framing AI relationally as more than a mere tool, with meaning arising through the interactions of people and what they produce with AI. This relational view requires preparing students to learn amid uncertainty in an AI-mediated world, demanding heightened ethical and critical attention. Student–staff partnership is especially well-suited to supporting navigation of such complexity and uncertainty, keeping the relational core of Higher Ed intact even as knowledge itself is enacted as dynamic, provisional, and co-constructed.

Five Guiding Principles for Navigating AI Together

Matthews expands on her earlier five propositions for genuine partnership practice (Matthews, 2017) to offer five principles that honour and imbue pedagogical trust:

1. Cultivate open and curious conversations together. Trust flourishes in spaces honouring curiosity and vulnerability, where AI is treated not as a problem to be solved but a mystery to explore collectively — rooted in care, deep listening, and the willingness to sit with uncertainty.
2. Acknowledge and work with the emotional and vulnerable lived experiences of AI use. AI awakens a spectrum of feelings — hope, fear, frustration, wonder — felt by students and educators alike; recognising this shared vulnerability is an act of care that invites empathy and makes it safe to seek support.
3. Make the role of AI visible and negotiable in learning activities. Transparency is more than disclosure; it is a collective act of witnessing and negotiating the shifting boundaries of Agency, authorship, and Creativity, making the invisible visible and inviting ongoing dialogue about AI's place in co-created learning.
4. Create consistent opportunities for shared learning and reflection on AI. Learning with AI is a journey, not a moment; partnership commits to sustained, collective spaces where students and educators reflect, question, and imagine anew — including ensuring those whose knowledge has traditionally been devalued are included.
5. Ground ethical norms in shared values and a collective moral compass. Ethics is not a checklist but a living commitment to justice, care, and respect that emerges from shared values, demanding ongoing reflection, humility, and a fierce commitment to equity and inclusion.

Each principle is accompanied by questions for students and educators to explore together, translating partnership into a living practice rooted in care, vulnerability, and communal wisdom. Together they refuse easy answers, offering instead a pathway where pedagogical trust is nurtured through relationship, dialogue, and shared commitment.

Implications for AI in Education

The editorial's central implication is that responses to AI in education should be trust-centred rather than surveillance-driven. Deficit framings of students as cheaters or victims undermine the relational foundations of learning; partnership — grounded in respect, reciprocity, and shared responsibility — offers a more productive path. For instructors, the five principles provide a practical, dialogic framework for navigating AI use openly with students, developing AI Literacy through co-inquiry rather than policing. For institutions, Matthews' call to model reciprocal, respectful, equitable relationships speaks to the wider responsibility of Higher Ed to sustain public trust at a political moment when it is increasingly fragile. The editorial also issues a research invitation: more critical discussion, reflection, and theorisation are needed on AI's role in pedagogical partnerships.

Connected Concepts

• Pedagogical Partnerships
• Trust
• Generative AI
• AI Literacy
• Agency
• Ethics
• Teacher Role
• Higher Ed
• Pedagogy
• Student Engagement
• AI Use Disclosure

Connected Articles

• Guided Inquiry GenAI Course Policy 2026 — A Guided Inquiry Approach to Students Co-Designing Generative AI Course Policies
• Williams Ingle Assessment Co Creation AI 2025 — Assessment Design Through Co-Creation in the Age of AI
• Chang Co Designing AI Youth Relational Privacy 2025 — Co-Designing AI with Youth
• Chang Should I Tell My Teacher AI Disclosure 2026 — "Should I Tell My Teacher?" Student AI Disclosure Practices
• Chang GenAI Peer Feedback Collaborative Argumentation 2026 — GenAI in Peer Feedback and Collaborative Argumentation

Citation

Matthews, K. E. (2025). Five guiding principles for navigating artificial intelligence in students as partners practice to preserve pedagogical trust. International Journal for Students as Partners, 9(2), 1–8.