PhD Candidate · Sydney, Australia
Researcher in Generative AI, Academic Integrity and Human–AI Education
My work examines how generative AI changes knowledge, assessment, authorship, academic integrity and human agency in education — and how universities can respond with policy that is clear, fair and workable.
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Research themes & methods
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Research projects
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Case studies analysed
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Writing samples
Live tool
A live web tool that coaches students through structured thinking on an assignment — planning, questioning and evaluating their own reasoning — instead of generating answers for them.
What I work on
How AI systems reshape learning, teaching, assessment and the meaning of knowing.
Authorship, disclosure and fair decision-making when AI is part of student work.
Systematic comparison of institutional AI governance and its real-world consistency.
Human-led AI workflows where accountability, verification and ethics stay with people.
Systematic reviews, thematic analysis, discourse analysis and document analysis.
Guides, policy briefs, SOPs and documentation that make complex rules usable.
Doctoral project
“The Role of Generative AI and Agency in the Epistemological Foundations of Contemporary Pedagogy”
My doctoral research asks how epistemic agency — a learner's capacity to form, justify and take responsibility for knowledge — is preserved, redistributed or eroded when cognitive work is shared with AI systems, and what that means for assessment, integrity and AI governance in higher education.
About the doctoral project →Portfolio
A systematic comparison of how Australian universities regulate student use of generative AI in assessment, coded against a structured analytic framework.
Document analysis · Qualitative coding · Comparative policy analysis · Spreadsheet coding matrix
Last updated 28 July 2026
A consistency study applying the same fictional student AI-use cases to different university policies to test whether they produce the same decisions.
Vignette methodology · Policy analysis · Structured decision coding
Last updated 28 July 2026
A six-question framework that structures fair, consistent decisions about student generative-AI use in assessment.
Conceptual synthesis · Case testing · Policy analysis
Last updated 28 July 2026
In print
Poudyal, B. · 2026 · Information Age, ACS (op-ed), 12 May 2026
Argues that universities misrepresent what degrees certify in the age of generative AI — pretending students work independently while tacitly tolerating pervasive AI use — and calls for institutions to shift from certifying individual knowledge to evaluating how students collaborate with and manage AI tools.
Poudyal, B. · 2025 · Information Age (op-ed)
Who I am
I am a PhD candidate based in Sydney, Australia, researching generative AI, epistemic agency and education. My work sits at the intersection of philosophy of education, academic integrity and AI policy: I study how universities regulate student AI use, whether those rules produce fair and consistent decisions, and how assessment can preserve human agency when machines can produce credible academic work.
Alongside conceptual research, I build practical tools — decision frameworks, policy-analysis pipelines and professional guidance — that translate research into things institutions can use.
Keep exploring
Fictional student GenAI-use cases analysed with a structured decision framework.
Guides, policy briefs, SOPs and documentation samples.
Education, experience, skills and professional development.
Get in touch about research, collaboration or roles.