Educational AI Auditing
I test whether AI tutors distribute cognitive challenge, scaffolding, dialogue, and expectations differently across learners.
- Computational audits
- Pedagogical equity
- LLMs
Computational education policy scholar
From Digital Rights toPedagogical Opportunity
I study how AI distributes pedagogical opportunity and how public educational institutions can audit, govern, and redesign that distribution.
Ph.D. Researcher, Penn StateEnterprise GenAI Research Fellow, Chicago Public Schools
AI should expand human capability
without quietly ranking human potential.
2022Digital Rights
2024Learning
2025Opportunity
2026Audit & Governance
The question behind my work
Who receives what kind of teaching from AI, under what institutional conditions, and with what consequences?
AI is becoming more than a tool. It is becoming an allocator of explanation, challenge, patience, attention, and trust. My research makes those allocations visible and helps public institutions remain accountable for them.
Research program
Auditing the systems that teach
I connect computational evidence, human learning, and institutional governance to protect every learner’s opportunity for intellectual growth.
Human–AI Learning
I study how AI changes learning, verification, intellectual agency, and the opportunity to become an independent thinker.
- Learning & transfer
- Epistemic agency
- Doctoral formation
Policy & Public Governance
I examine how schools and public institutions can adopt, monitor, and redesign AI systems under conditions of uncertainty.
- District governance
- Policy implementation
- Public accountability
Current inquiries
Pedagogical Equity in the Age of AI Tutors
A computational audit of differential instructional responses across race-associated name signals, language profiles, and socioeconomic contexts in four large language models.
The Readiness Divide
A 39-system analysis of socioeconomic status, readiness for AI-supported learning, and creative thinking in PISA 2022.
From Access to Inclusive Use
A cross-national study of school disadvantage, teacher capacity, and AI-supported inclusion using TALIS 2024.
My intellectual journey
One question, coming into focus
My path did not begin with AI auditing. It began with a concern about digital power and moved steadily closer to the places where technology shapes human possibility.
- 2022
Digital Rights
Privacy, free speech, content moderation, and the constitutional boundaries of platform power.
- 2023
Algorithmic Governance
Data governance, human rights, discrimination, market power, and the arrival of generative AI.
- 2024
Learning
Critical-thinking pedagogy, culturally responsive curriculum, and institutional readiness for AI.
- 2025
Opportunity
Comparative evidence on scientific literacy, ICT, schools, and the unequal conversion of resources into learning.
- 2026
Audit & Governance
AI-mediated teaching, scholarly identity, district governance, and the measurement of pedagogical disparity.
Selected publications
Ideas, evidence, and evolution
From production to verification: Generative AI, doctoral formation, and the leadership of digital education
Frontiers in Education
From integrity to identity: Course-level generative AI governance and scholarly subject formation in graduate education
Frontiers in Education
Analyzing Scientific Literacy in Asia’s Top Five PISA 2022 Performers Using Hierarchical Linear Modeling and Bourdieu’s Theory of Practice
Asia-Pacific Science Education
ICT and Its Impact on the Scientific Literacy of Secondary School Students: A Comparative Study Between Singapore and the USA in PISA 2022
Science Journal of Education
Critical Thinking Pedagogics Design in an Era of ChatGPT and Other AI Tools—Shifting From Teaching “What” to Teaching “Why” and “How”
Journal of Education and Development
Data governance and human rights: An algorithm discrimination literature review and bibliometric analysis
Journal of Humanities, Arts and Social Science
Public impact
Research inside the institutions making decisions now
At Chicago Public Schools, I connect scholarly inquiry with the practical work of governing generative AI in a large, diverse public system. My role is not only to describe uncertainty, but to help institutions learn from it.
This district-engaged research translates stakeholder evidence into governance recommendations, implementation priorities, and structures for organizational learning.
600+survey responses
25+executive interviews
18role-specific focus groups
1shared public mission
About Evelyn
Researcher · Policy thinker · Public partner
I study technological change by moving between systems, institutions, and human experience.
I am a doctoral researcher in Education Policy and Leadership at Penn State, with training in Comparative and International Education and Social Data Analytics. I earned my M.P.P. from UC Berkeley, where public policy and data science shaped how I first approached questions of algorithmic power.
My work is grounded in a simple commitment: every learner possesses epistemic dignity—the right to be treated as capable of reasoning, questioning, and intellectual growth. I want AI to enlarge those possibilities, not quietly narrow them.
Contact
Let’s continue the conversation.
I welcome conversations about educational AI auditing, human–AI learning, public-sector governance, and research collaboration.
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