ASPIRE

Adaptive Scaffolding for Personalized Instruction and Responsive Education

Our Mission

ASPIRE is a research initiative at the Halıcıoğlu Data Science Institute (HDSI) at UC San Diego dedicated to transforming college mathematics education through intelligent, adaptive learning systems.

We integrate generative AI with rich models of student knowledge and learning behavior to deliver personalized scaffolding that meets each learner where they are—helping students with widely varied mathematical backgrounds progress efficiently through prerequisite coursework and into credit-bearing mathematics.

Our interdisciplinary team spans data science, cognitive science, education studies, and computer science, collaborating closely with community college and university partners to ensure our tools are equitable, effective, and deployable at scale.

ASPIRE
Adaptive
Scaffolding for
Personalized
Instruction and
Responsive
Education

How We Approach the Problem

ASPIRE combines insights from AI, cognitive science, and educational research to build adaptive mathematics learning experiences.

Generative AI & Student Modeling

We use large language models directed by expert math knowledge graphs to understand exactly where each student is in their conceptual development and deliver targeted, just-in-time support.

Personalized Scaffolding

Drawing on principles from cognitive science and educational psychology, our scaffolding adapts in real time—providing hints, worked examples, and feedback calibrated to each learner's current understanding of the mathematics.

Equity & Access

We design with diverse learners in mind, partnering with community colleges and universities to close equity gaps in mathematics readiness for underrepresented student populations.

Continuous Improvement

Our platform collects rich learning analytics to feed back into both AI model refinement and evidence-based pedagogical design, creating a virtuous cycle of improvement.

Why Adaptive Mathematics Education Matters

Extreme Variation in Preparation

Students arriving in college mathematics courses bring vastly different levels of prerequisite knowledge. One-size-fits-all instruction cannot efficiently close those gaps—leaving many students stuck before they begin.

Transfer Pathway Gaps

Community college students face steep barriers when trying to satisfy math prerequisites for transfer. ASPIRE works directly with SDCCD and UC partners to smooth those pathways and reduce attrition.

Instructor Scalability

Faculty cannot provide individualized feedback to every student in large prerequisite courses. Our AI-powered tools amplify instructor impact without replacing the human relationship at the heart of education.