Our research explores how learning happens—across people, systems, and intelligent tools.

Experimental AI & STEM Research

Undisciplined develops experimental AI and STEM research projects that explore alternative models for teaching, learning, and interaction. This work examines how emerging technologies can support curriculum design grounded in learning science, cultural knowledge systems, and real-world practice—prioritizing meaning, context, and pedagogy over optimization alone.

  • This research explores how AI systems can support STEM and STEAM learning by engaging local knowledge systems, embodied practices, and cultural frameworks alongside formal scientific concepts. Areas of focus include mathematics, computation, environmental science, material science, and pattern-based reasoning as they appear in practices such as weaving, agriculture, design, medicine, and symbolic systems.

  • The project works with schools and community partners to document how STEM concepts are taught, practiced, and understood in specific contexts. Data may include classroom activities, curriculum materials, local problem-solving approaches, and community-informed explanations of scientific or mathematical ideas.

    All participation is consent-based, context-aware, and designed to avoid extractive data practices. Knowledge contributions are treated as intellectual assets, with attention to attribution, stewardship, and long-term use.

  • We collaborate with schools, educators, and community learning spaces interested in shaping future STEM curriculum tools. Pilot partnerships may involve classroom trials, co-designed learning activities, or documentation of local STEM practices.

    These collaborations help inform how experimental AI curriculum systems are designed, evaluated, and governed—while providing partners early access to research insights and future licensing pathways.

Partner on AI Reaserch

The Learning Lab: Curriculum Research

The Learning Lab serves as an ongoing research initiative exploring early childhood learning through play, material exploration, and systems thinking. Insights from this work inform curriculum design, learning environments, and future educational tools.

  • The Learning Lab studies how young children learn through play, movement, material exploration, and pattern recognition. We focus on how children engage with systems—such as cause and effect, rhythm, structure, and repetition—across physical, social, and sensory environments. This research informs early childhood curriculum design and the development of learning environments that support curiosity, agency, and understanding.

  • All research connected to the Learning Lab is designed with care for children, families, and educators. Participation is voluntary and transparent. Data collection focuses on observation of learning processes rather than individual assessment, and no personally identifiable information is used without explicit consent. Our goal is to understand learning patterns—not to evaluate or rank children.

  • Insights from the Learning Lab are used to improve curriculum design, learning environments, and future educational tools. Findings may inform publications, partnerships, or program development, always in ways that respect participant privacy and shared ownership of knowledge. Research outcomes are intended to support better learning experiences, not extract value from participants.

Partner on Learning Lab

Polyrhythms for Wellness

Exploring rhythm as a learning and regulation system. Polyrhythms for Wellness is a research initiative examining how layered rhythmic structures influence attention, emotional regulation, and cognitive engagement. The study explores rhythm as a structured system—bridging music, neuroscience, learning science, and cultural knowledge—to better understand how sound environments shape human experience. Insights from this research inform the development of experimental AI-driven sound systems used to study rhythm-based regulation over time.

  • Polyrhythms for Wellness studies how layered rhythmic patterns influence attention, emotional regulation, and physiological timing. The research focuses on entrainment—how the body and brain synchronize with rhythmic input—and explores rhythm as a structured, repeatable system rather than background sound. The goal is to better understand how rhythm can support focus, regulation, and wellbeing. These findings support the design of experimental AI systems that model rhythmic structure and response as part of ongoing study.

  • In this project, rhythm is treated as a measurable pattern. Rhythmic structures are documented through tempo, repetition, layering, and timing relationships. Participant interactions with rhythm are observed through changes in breathing, attention, and physiological rhythms. Data is used to identify patterns across sessions, not to evaluate individuals.

  • Polyrhythms for Wellness uses non-invasive, low-burden methods to observe rhythmic entrainment, such as guided listening sessions, breathing awareness, and optional physiological indicators when appropriate. Participation is voluntary and transparent, with a focus on comfort, agency, and respect. No diagnostic claims are made, and data is handled with care.

Ongoing research. Public materials forthcoming.