Research, built into working tools.

What EduWork.AI is.

EduWork.AI is a small business that turns research methods into tools people can actually use. It is a growing set of AI applications for education and workforce research, evaluation, and technical assistance, from predicting where needs are greatest to helping partners read the evidence for themselves.

Every tool here is a working demonstration, open to try, with no login. We build these tools for our own research and evaluation work, and we partner with agencies, labs, and other organizations that want to use them.

The team.

EduWork.AI is more than one person. Dr. Michelle Yin leads a small, multidisciplinary team that brings together the skills a good tool needs.

• Economists for research design, causal methods, and reading policy data.
• Data scientists for modeling, machine learning, and data pipelines.
• Psychologists and learning scientists for measurement, assessment, and how people learn.
• Software engineers for building and running the tools in production.

We work as a small-business partner on research, evaluation, and technical-assistance projects. If you are putting together a proposal or a contract and want this kind of capacity on the team, get in touch.

What you can do here.

• Predict district needs. Rank where to target applied research and technical assistance, with the drivers and matched strategies explained.
• Browse a modern resource center. Searchable, filterable evidence resources by topic, type, and evidence tier.
• Learn education statistics. Short interactive lessons on effect sizes, confidence intervals, RCT versus quasi-experimental design, and ESSA evidence tiers.
• Ask the evidence. Get a grounded, cited answer from a vetted library, with an honest "not enough evidence" when that is the truth.
• Accelerate research. Turn a set of studies into a structured evidence table and a plain-language brief.
• Scan regional needs and automate reporting. Rank problems of practice from a region's own documents, and assemble monthly progress reports from a project log.
• Check AI-score stability. See how AI scores of the same work diverge across models, and report a bounded, human-calibrated estimate.

Grounded in research.

EduWork.AI tools are informed by Dr. Yin's ongoing research on education, workforce, disability, and the measurement of AI. The research program is carried out through the RISEI Lab. For the full portfolio of journal papers, working papers, and briefs, visit the lab.

A sister platform.

ReachABLE is a companion platform we built for people with disabilities and their families, helping them understand ABLE accounts, protect benefits, and build financial independence. Same work of turning research into usable tools, for a different audience.

Visit joinreachable.com →

Contact.