Preparing for the Next Generation Science Standards - Developing and Using Models

Main ideas / lessons

• Purpose of NGSS & models-focused practice

  • The webinar explains how Scientific and Engineering practices (from NGSS / Framework for K–12 Science Education) include the practice of developing and using models.
  • It emphasizes that models are central to how students learn science: not just recalling information, but reasoning with models to make sense of phenomena.

• How NGSS was developed (high-level structure)

  • The standards are the work of four organizations:
    • National Academy of Sciences
    • National Science Teachers Association (NSTA)
    • American Association for the Advancement of Science (AAAS)
    • Achieve
  • The development involved multiple phases:
    • Framework for K–12 science education (released July 2011), including:
      • Science & engineering practices
      • Crosscutting concepts
      • Core ideas by discipline
    • A later standards/implementation effort by Achieve and participating states, intended to support:
      • Assessments
      • Curricula
      • Teacher professional development

• What “models” mean in science education

  • A science model is described as an abstract simplified representation of systems.
  • Models make features and connections explicit/visible.
  • Models are used for forecasting and explanation, not merely illustration.
  • The webinar contrasts:
    • Internal/mental models (in students’ minds)
    • Conceptual/external models (charts, diagrams, tables, etc.)

• Modeling as a practice (a process)

  • Modeling is not a static product; it is an active cycle involving:
    • Developing/building a model that embodies ideas and/or evidence
    • Testing/evaluating the model with empirical evidence or theory
    • Using models for illustration and explanation/forecasting
    • Revising the model based on what evidence shows
  • Classroom modeling typically includes:
    • Model use (very common)
    • Model construction (also common)
    • Model assessment/evaluation (considered critical but less common)

• Why modeling matters for students and teachers

  • Modeling helps students:
    • Connect theories to data
    • Build coherent understanding
    • Improve scientific reasoning and understanding of how science works
    • Develop skills for communication, argumentation, and consensus building
  • Modeling helps teachers:
    • Teach science in ways aligned with NGSS practices (sense-making rather than only transmission of facts)

• Models are dynamic and socially negotiated

  • Students work with models in a social/community setting:
    • Disagreement is expected.
    • Students use evidence and mechanisms as criteria.
    • The class develops or refines consensus models.
  • Evaluation criteria emphasize usefulness/fertility (not “one correct model”):
    • Models are judged by how well they align with evidence and explain mechanisms
    • Multiple models can compete or complement each other depending on the question/context

• A key distinction: reasoning tools vs “art projects”

  • The webinar distinguishes:
    • Good scientific models used for explanation/forecasting/mechanistic understanding
    • vs. models as aesthetic replicas/copied diagrams that may lack mechanistic/cause-and-effect reasoning
  • Teachers are urged to assess the ideas/relationships a model represents, not just drawing quality.

• Classroom instructional structure: “idealized sequences”

  • The webinar describes a modeling-centered instructional sequence:
    1. Start with a central phenomenon / guiding question
    2. Elicit initial student models
    3. Conduct empirical investigation (collect evidence)
    4. Introduce supporting theoretical ideas to interpret evidence
    5. Students revise models (often with peer discussion)
    6. Build consensus models (class or small group)
    7. Apply the revised consensus models to:
       • The original phenomenon, and/or
       • New but related phenomena
  • This is presented as a unifying thread that supports coherence across a unit.

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Methodology / instruction-style content (detailed bullet list)

A. What to do in a modeling-centered lesson/unit (process steps)

1. Choose a central phenomenon

   • Use a real-world/sense-making question that students cannot answer using only prior knowledge.

2. Elicit initial models

   • Have students draw/construct an initial model representing their current thinking.
   • Treat initial models as ideas to be tested and revised, not final answers.

3. Plan and run empirical investigations

   • Collect evidence relevant to model components and mechanisms.
   • Use tools/experiments that help students observe/measure aspects of the phenomenon (e.g., humidity sensors, probes, simple observation tools).

4. Have students evaluate and revise models

   • Students compare model predictions/claims to evidence.
   • They remove/add model features based on what evidence supports.

5. Provide theoretical support at the right moments

   • Introduce concepts that help students explain how/why (mechanisms), not just what is happening.
   • Use models (often including simulations) to visualize invisible mechanisms.

6. Create structured peer discussion

   • Students share models, compare differences, and argue using evidence.

7. Build consensus models

   • In small groups or whole-class:
     • Decide what the most important/useful parts of the model are
     • Establish shared norms for evaluation (e.g., consistency with evidence, mechanisms, explanatory power)

8. Revisit the original phenomenon and extend to new contexts

   • Use consensus models to explain outcomes of the original system.
   • Apply models to new—but related—phenomena to test transfer and generalization.

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B. How to evaluate student “models” (classroom guidance)

• Evaluate based on:
  • Consistency with evidence
  • Whether the model supports explanation and/or forecasting
  • Presence of mechanisms/cause-effect relationships
  • Ability to be used for further inquiry and understanding
• Avoid over-focusing on:
  • Artistic quality or diagram neatness
  • Whether arrows/visuals look correct aesthetically when underlying reasoning is missing

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C. How teachers should handle student “errors” during modeling

• Don’t correct instantly every moment; that can reduce curiosity and student agency.
• Instead:
  • Ask strategic questions to help students notice mismatches between model claims and evidence
  • Guide students to self-correct by revisiting evidence and evaluation criteria
  • Use comparison/contrast prompts among student models so misconceptions surface through discussion
• Intended classroom culture:
  • Safe for ideas
  • Focused on sense-making and evidence-based revision

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Examples presented (what they illustrate)

1. Elementary school example: Evaporation and condensation (solar distillation)

• Central phenomenon/question

  • Students consider whether they could drink liquid from a lid of a solar distillation apparatus containing dirty water.

• Student initial models

  • Often include evaporation and heat, but may lack mechanistic explanations.

• Empirical evidence gathering

  • Students test ideas by measuring changes (e.g., humidity/water vapor increases around warmer water; comparisons between warm/cold).
  • They may use sensors/probes and/or simpler observation methods.

• Model revision and added theory

  • Students incorporate particle ideas:
    • Water consists of particles that move; transitions explain how water vapor forms and then condenses.

• Peer evaluation and consensus building

  • Students compare and build consensus evaporation/condensation models.

• Application

  • Students use models to explain how the device produces clean water.

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2. High school example: Genetics modeling with pedigree data (Mendelian and extensions)

• Central phenomenon/question

  • From family history/pedigrees, determine how traits/conditions are transmitted (e.g., recessive/dominant patterns).

• Initial models

  • Students begin with a model grounded in Mendel’s ideas and align it to understanding of meiosis (information from mother and father).

• Empirical or simulation data

  • Students use crossbreeding/simulation contexts to infer dominance/recessiveness from outcomes.

• Model refinement

  • When outcomes don’t fit the simplest model (e.g., additional traits/sex-linked patterns), students revise to incorporate additional genetics concepts:
    • dominant/recessive
    • codominance
    • multiple alleles
    • sex-linkage / attachment patterns (as described)

• Consensus and application

  • Students argue about which model best fits which pedigree and then apply refined models to new cases.

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Resources / support mentioned

• NSTA Education resources portal and training center
• NGSS-related information site(s) referenced:
  • nsta.org/ngss
• Additional mention:
  • A resource website by Mark Windschitl (tools/videos for secondary)
  • NSF-sponsored materials (e.g., “Ivy Quest” for middle school)
  • Professional forums/discussion spaces for continuing NGSS dialogue

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Speakers / sources featured (all identified)

Speakers (people)

• Bryn Slate (moderator)
• Ted Willard
• Christina Schwartz
• Cindy Passmore

Referenced institutions / sources

• National Academy of Sciences (NAS)
• National Science Teachers Association (NSTA)
• American Association for the Advancement of Science (AAAS)
• Achieve
• Framework for K–12 Science Education (National Academy Press / committee including scientists and teachers)
• Andy Anderson and colleagues (credited for the “pyramid/triangle” framing of observations → patterns → models and iteration)
• Concord Consortium (used for simulations referenced in the example)
• Nobel Prize laureates (not named individually; referenced as part of committee/scientists involved in the framework)
• Sue Johnson (credited as an early innovator related to genetics modeling sequences)