Tina Austin helps educators and institutions move beyond tool adoption—to design for human reasoning, discernment, and agency in an AI-mediated world.
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Institutions, media, and global education communities
The premise
“When AI can produce the answer,
learning lives in the reasoning.”
Generative AI has made finished work an unreliable proxy for learning. Tina’s work asks a more useful question: how do we make thinking visible, traceable, and worth doing?
Her answer is UnBlooms™—a recursive, problem-centered approach to learning design that develops judgment before, during, and after AI use.
UnBlooms™
A framework for thinking with AI
Bloom’s Taxonomy is often treated as a climb toward a finished product. But learning is rarely linear—and AI can now shortcut the visible output at every level.
UnBlooms begins with a meaningful problem, then cycles through inquiry, making, critique, reflection, and revision. The goal is not to avoid AI. It is to know when to use it, when to challenge it, and when to think without it.
Explore the open frameworkSelected research & writing
Tina’s work connects learning science, assessment design, AI literacy, and institutional change—moving evidence into practice.
Peer-reviewed paper · 2026
Introduces the UnBlooms™ Metacognitive Awareness Scale and Discernment Rate—measures designed to distinguish polished output from durable learning in AI-mediated environments.
Read the paperConference paper · LAK ’26
A within-subjects study of the UnBlooms Framework, presented at the Learning Analytics for Human-Centered Generative AI-Enhanced Smart Learning Environments workshop.
Explore the researchOpen framework · 2025
A problem-centered framework for learning design in the AI era: recursive rather than hierarchical, with reasoning made visible before, during, and after AI use.
View on ZenodoBook · 2025
A practical guide to designing, teaching, and assessing human reasoning when AI can generate the finished product—built for educators who need methods, not slogans.
Find the bookFrom framework to fieldwork
Tina works with universities, nonprofits, policy groups, and philanthropic organizations on responsible AI adoption—connecting governance, faculty development, assessment, and culture.
Higher Education Summit · Invited faculty speaker
IASEAI ’26 · AI Safety Literacy Framework
AIEOU · Research collaboration
AI & Workforce Board · Policy advising
Innovative Educator Expert · 2025–26
Faculty development · 1,800+ educators
Teaching with AI across disciplinesOpenAI Higher Education Summit · 2025
About Tina
Tina Austin is a globally recognized researcher, educator, author, and advisor working at the intersection of AI, learning, and institutional change.
A former biomedical researcher and longtime university lecturer, she has taught at UCLA, USC, CSU, and Caltech. She brings the skepticism of a scientist and the empathy of an educator to a question that matters everywhere: how do we gain the benefits of AI without giving away human judgment?
Selected appearances & work
Highlights carried forward from the original TinaAustin.com portfolio. Select any image to visit its original story.
Advising · Workshops · Keynotes
Bring Tina in to help your institution connect AI strategy to the people, learning, and values it is meant to serve.
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