Grade 9 · Integrated Human Systems Science
The Keystone Year. Learners reason abstractly, coordinate multiple representations, and work with formal variables. This year marks the transition from systems literacy to systems competence, where students learn explicitly how different disciplines—biology, engineering, data science—view the same problems.
Analytical Commitments
Formerly "Anchor Ideas," these are now treated as formal rules of analysis. Students must explicitly name and apply these commitments to show competence.
Complex systems require multiple disciplinary lenses.
No single tool explains the whole; students must layer biological, physical, and social perspectives.
Matter, energy, information, and risk move through systems.
Students trace these four fundamental flows to diagnose system health.
Models simplify reality and must be tested, limited, and revised.
Students formally critique the limitations of their own models.
Decisions are constrained by evidence, ethics, and uncertainty.
Students make choices within defined constraints, acknowledging what they do not know.
Technical tools increase power and responsibility.
Students recognize that advanced tools (AI, bio-engineering, automation) require advanced ethical frameworks.
Grade 9 exists to answer one question: What tools do different disciplines use to understand and improve the same human systems? Students leave Grade 9 not as specialists, but as informed choosers of specialization.
What Grade 9 adds to the system: Competence. Students learn the actual tools of the trades (equations, diagrams, code, design briefs) rather than just the concepts.
Standards by Disciplinary Lens
Each lens is applied to the same SDG systems (Water, Energy, etc.), teaching students how different experts view the same problem.
9-HS1
System Modeling and Representation
All SDGs
Abstraction
Validation
- 9-HS1.1 Students construct conceptual, mathematical, and computational models of human systems.
- 9-HS1.2 Students translate systems between representations, diagrams, equations, and simulations.
- 9-HS1.3 Students analyze model assumptions and limitations.
- 9-HS1.4 Students revise models based on evidence and failure.
Hands-on STEM expectation
System diagramming, equation-based modeling, simulation tools, model debugging.
9-HS2
Energy, Matter, and Conservation
Water · Energy · Production
Laws
Limits
- 9-HS2.1 Students apply conservation principles to track matter and energy through systems.
- 9-HS2.2 Students analyze efficiency, loss, and transformation quantitatively.
- 9-HS2.3 Students evaluate system performance using energy and material balances.
- 9-HS2.4 Students design improvements grounded in conservation constraints.
Hands-on STEM expectation
Quantitative flow analysis, efficiency calculations, constrained redesign challenges.
9-HS3
Data, Variability, and Uncertainty
All SDGs
Variability
Confidence
- 9-HS3.1 Students collect, visualize, and analyze multivariable data.
- 9-HS3.2 Students distinguish signal from noise and identify sources of uncertainty.
- 9-HS3.3 Students evaluate reliability and bias in data sources.
- 9-HS3.4 Students use data to support or refute system claims.
Hands-on STEM expectation
Data sets, error analysis, visualization tools, uncertainty discussions.
9-HS4
Human Health and Biological Systems
Health & Well-Being
Scale
Interaction
- 9-HS4.1 Students model biological systems at cellular, organismal, and population scales.
- 9-HS4.2 Students analyze interactions between environment and biological function.
- 9-HS4.3 Students evaluate health interventions using biological evidence.
- 9-HS4.4 Students compare biological and technological solutions to health problems.
Hands-on STEM expectation
Physiological modeling, exposure analysis, intervention comparison.
9-HS5
Engineered Systems and Design Logic
Infra · Cities · Production
Optimization
Robustness
- 9-HS5.1 Students apply formal design processes to system problems.
- 9-HS5.2 Students analyze constraints, criteria, and failure modes.
- 9-HS5.3 Students evaluate tradeoffs in engineered solutions.
- 9-HS5.4 Students iterate designs using performance data.
Hands-on STEM expectation
Design briefs, prototype testing, failure analysis, redesign cycles.
9-HS6
Computation, Control, and Information Flow
All SDGs
Algorithms
Control
- 9-HS6.1 Students model systems using algorithms and logical rules.
- 9-HS6.2 Students analyze feedback and control mechanisms.
- 9-HS6.3 Students evaluate automation and decision-support systems.
- 9-HS6.4 Students design simple computational models to improve system performance.
Hands-on STEM expectation
Flowcharts, rule-based simulations, basic control modeling.
9-HS7
Ethics, Policy, and System Decisions
All SDGs
Policy
Responsibility
- 9-HS7.1 Students identify ethical dimensions of system decisions.
- 9-HS7.2 Students evaluate policy options using scientific evidence.
- 9-HS7.3 Students analyze impacts across populations and time.
- 9-HS7.4 Students defend decisions using evidence and ethical reasoning.
Hands-on STEM expectation
Case analysis, structured debates, policy simulation.
Grade 9 throughline: Disciplinary lenses. Students integrate the specific tools of science, engineering, and computation to analyze complex systems, preparing them to choose a path of specialization in later years.
Design and Practice Standards
Required across the year, these standards ensure students treat their models as testable, revisable tools rather than static facts.
- 9-DSP1 Students integrate disciplinary tools to analyze complex systems.
- 9-DSP2 Students critique and revise models using evidence.
- 9-DSP3 Students justify decisions using data, models, and ethical reasoning.
- 9-DSP4 Students reflect on limitations and uncertainty in solutions.
What Grade 9 accomplishes
Students master the shared toolset of science, engineering, and computation. Disciplinary differences become visible and meaningful, and branching into specialization becomes a matter of informed emphasis.