Explains the historical and intellectual gaps that Utorics addresses. Covers why traditional frameworks—psychology, HCI, behavioral economics, classical UX—fail to fully predict user behavior. Establishes the need for a scientific discipline that unifies interaction, cognition, and physics-inspired models.

Presents the foundational axioms of Utorics: users as energy-constrained agents, interactions as flows, friction as a measurable force, and interfaces as dynamic fields. Students develop a conceptual map of the core system that will guide the remainder of the course.

Provides a high-level overview of QFIT and how it integrates principles from quantum mechanics and fluid dynamics. Students learn why user behavior is modeled as probabilistic, why flows matter, and how cognitive “energy” and “viscosity” shape interaction outcomes.

Explores how human intent behaves like a probabilistic field, how micro-interactions create ripples in behavior, and why user decisions are not strictly deterministic. Introduces the idea of uncertainty, wave-like behavior, and state transitions in real-world interactions.

Students learn the three most important dynamic structures in Utorics: • Fields (forces acting on attention and intent) • Flows (the pathways through which users move) • Friction (points where energy is lost) Practical examples help connect the concepts to observable interface behavior.

Introduces entropy as the measure of disorder in a system and applies it to digital interactions. Students learn that interfaces either increase entropy (creating confusion) or reduce it (increasing clarity). Covers cognitive depletion, decision fatigue, and the role of “negentropic” design.

Models intent as a probability distribution that shifts in response to cues, context, clarity, and cognitive load. Students learn to interpret interactions not as linear but as evolving probability states, which can be influenced through design choices.

Shows how Utorics enables prediction of user behavior in structured, scientific ways. Introduces students to measurable variables, testable hypotheses, and the ability to forecast friction, drop-offs, and behavioral shifts with greater precision than traditional methods.

Provides a conceptual introduction to the Flow Equation—the core mathematical model of QFIT. Students learn what each term represents (flow velocity, cognitive viscosity, external forces, gradients) and how the equation can diagnose or correct interaction problems.

Teaches students how to observe, identify, and interpret user-flow anomalies in real products using Utoric principles. Includes examples like turbulence, local minima, backflow loops, and high-friction zones. Students learn to translate these patterns into actionable improvements.

Introduces visual tools such as flow maps, field gradients, energy landscapes, and friction-heat diagrams. Students learn how to convert abstract concepts into diagnostic visuals that support analysis, storytelling, and decision-making.

Covers principles and patterns for reducing friction and guiding users toward optimal flow. Students learn how to engineer clarity, reduce entropy, and create stable, high-probability pathways. Includes a library of Utoric anti-patterns and their corrections.

Presents diverse examples of interfaces, products, and environments analyzed through a Utoric lens. Students learn how theoretical concepts translate into real decisions and measurable improvements. This lesson bridges theory with practice.

Introduces empirical testing methods grounded in Utorics—how to measure friction, entropy, probability shifts, cognitive costs, and flow velocity. Students learn step-by-step methods to design experiments, gather data, and model outcomes.

Provides an honest assessment of Utorics’ current boundaries and open questions. Students learn where the models apply well, where they struggle, and how the discipline continues evolving. Emphasizes scientific humility and methodological rigor.

This lesson helps students understand Utorics not only as a theoretical discipline but also as a developing professional field. It covers: • Professional practice: How practitioners can apply Utoric principles in everyday work, from diagnosing broken flows to modeling probabilistic user behavior. Students examine how Utorics complements existing roles in research, design, analysis, decision science, and product strategy. • Foundational skills and competencies: What a practitioner should know—energy modeling, entropy analysis, flow visualization, hypothesis design, system thinking, and experimental rigor. • Emerging research directions: Current open questions in Utorics and QFIT, such as: • Modeling cognitive viscosity under different emotional states • Predictive models for multi-agent interaction systems • Entropic signatures of user uncertainty • Field-based interaction mapping in AR, VR, and embodied environments • Early attempts to formalize “interaction constants” across domains • Interdisciplinary collaborations: How Utorics intersects with cognitive science, behavioral physics, computational modeling, and decision theory. Students see how new contributions shape the scientific foundation of the field. • Future of the discipline: What professional trajectories may emerge as Utorics develops—academic pathways, certification programs, research labs, professional standards, and communities of practice. This lesson positions students within a growing field and invites them to see themselves as contributors to a new scientific body of knowledge.

Explores ethical questions raised by predictive modeling of user behavior. Topics include: • Influence vs. manipulation • Respect for autonomy and informed agency • Transparency in probabilistic interaction systems • Responsible use of behavioral prediction • Equity, bias, and accessibility in probabilistic models Students learn how to apply Utorics in ways that elevate user well-being, maintain dignity, and preserve agency.

Students receive instructions for a capstone assignment applying Utoric principles to a real digital or physical environment. They will diagnose flows, map fields, identify friction, propose improvements, and present a scientifically grounded analysis with visuals and evidence.