What I study

Participation research asks whether families are present, heard, and satisfied. It rarely asks what becomes of what they contribute. I study that second question. In special education, families bring knowledge about their children into the meetings where their child's Individualized Education Program (IEP) is written — knowledge that no assessment captures — and the record that comes out often shows no trace of it. My work measures where that knowledge is lost, why, and what it means to build systems — human and computational — that stop losing it.

Across 136 IEPs analyzed with three large language models as independent coders, exclusionary language outnumbers collaborative language 14 to 1. Seventy-seven percent of documents are written at a fourteenth-grade reading level for families expected to read and sign them. The gap is four times wider for Black students.

I am a PhD candidate in Education at UC Davis, in the Learning & Mind Sciences emphasis with a designated emphasis in Computational Social Science. That pairing is the method: questions about how people learn and participate in formal educational settings, answered with large language models as independent coders, tested for inter-rater reliability, and validated by the families the documents describe. The human stays in the loop by design, and the people the system is about are the ones checking it.

Knowledge Entry and the Family Mattering Framework

Knowledge Entry names the stage between a family's participation and the institutional record, where what a family knows either enters the document with standing or does not. It distinguishes four outcomes — expressed, entered, given standing, acted on — and treats the gap between them as measurable rather than assumed.

Naming a gap is not enough. A concept nobody can measure changes nothing, so the question that followed Knowledge Entry was the one I ask as a technologist: how do we operationalize it? The Family Mattering Framework is the answer.

The framework applies Knowledge Entry to institutional texts, beginning with the IEP: a legally binding document, averaging around 40 pages of assessments and educational planning, that governs a student's services. It codes how such a record treats family knowledge on a manual-anchored 1–4 scale, with multiple large language models as independent raters and every rating validated against caregiver responses to the same passages. Applied to 36 IEPs and 115 caregivers in a study of what readability measures miss. Coding manual and technical reports at expertiep.com/research.

Publications and presentations

Peer-reviewed

Lindstrom, L. E., Ganguly, R., & Banks, A. R. (2026). Narratives of success: High-achieving women with disabilities navigating higher education in Australia. Higher Education Research & Development, 45(1), 173–187.

Banks, A., Yonehiro, J., Placido, D., & Munakata, Y. (2021). Scaffolding development: A meta-analysis of the role of parents in shaping children's executive function development. UCLA National Ronald E. McNair Journal.

Manuscripts

Banks, A. (in preparation). Knowledge Entry: Measuring family mattering in institutional documentation. Target: Teachers College Record.

Banks, A. (in preparation). Beyond readability: Linguistic access, documentary standing, and recognition in Individualized Education Programs. Target: Exceptional Children.

Lindstrom, L. E., Kahn, L., Ganguly, R., & Banks, A. (in preparation). "We are forged differently": Perspectives of disabled undergraduate students.

Book

Banks, A. (2019). Better Than a Diagnosis: A Single Parent's Guide to Autism. Happie Life.

Technical reports and research artifacts

Banks, A. (2026). Designing for trust before disclosure: Family-centered AI in special education (Expert IEP Technical Report No. 1). Expert IEP Research. [link]

Banks, A. (2026). Family Mattering Framework coding manuals: Linguistic Inaccessibility, Agency Marginalization, and Temporal-Experiential Disconnect. [link]

Banks, A. (2025). Family privacy promise: Data governance commitments for family-facing educational AI. Expert IEP.

Selected conference papers and invited talks

AERA Annual Meeting (2026). Paper session chair and presenter. "Unforgetting the Families Who Built Special Education: Computational Analysis of IEP Language and Family Voice."

NABSE 53rd Annual International Conference (2025). "From Paperwork to Partnership: How School Leaders Are Using AI to Fix IEP Frustration and Family Mistrust."

ASU+GSV Summit (2025). Panel and podcast, "Families as Force Multipliers."

Harvard Graduate School of Education (2025). Case study on Expert IEP as an educational technology innovation.

United Nations (2024). Public engagement speaker, "Equitable Deployment of Artificial Intelligence."

White House, Office of the First Lady (2024). Invited presentation on highly mobile students with IEPs.

AERA Annual Meeting (2024). "Enhancing IEPs through AI."

Pacific Rim International Conference on Disability and Diversity (2024). "Harnessing AI/ML for Personalized IEPs in Special Education."

Full CV