Teaching Lesson 1

The most important thinking skills to promote in this unit are the comparison and contrast between the real and virtual world, and the development of a critical eye towards models and modeling.   How can you as a teacher get your students to be reflective and critical thinkers about models?  How can you nurture students' ability to ask questions of models, and invoke students' natural curiosity?

Assignment:
Review the activities from Lesson 1 as well as the material below. Reflect on how you would teach this in your class. Post your reflection to your portfolio in "Pedagogy->Module 1" under the heading Lesson 1.


Lesson Objectives

The student will:

Experience being part of a complex adaptive system (LO1)

Compare and contrast a computer simulation vs. a real-world phenomenon (LO2)

See a demo of using a computer model to run experiments (LO3)

Investigate the parts of a computer model (LO4)

Speculate as to why computer models can be valuable scientific tools (LO5)

Learn characteristics of complex Adaptive Systems (LO6)


Teaching Summary

Getting started – 10 minutes

1.     Pre-test / Assessment (short survey to assess existing knowledge)

             Activity 1: Walk & Turn- 25 minutes  (New Learning)

2.     Participatory Simulation

3.     Computer Model, Teacher-led demo

4.     Correspondence between real-world and virtual world?

5.     Under the hood: Parts of a StarLogo Nova computer model

             Activity 2: Complex Adaptive Systems - 10 minutes (New Learning)

6.     Video “Introduction to Complex Systems”

7.     Characteristics of Complex Adaptive systems

             Wrap-up – 5 minutes (Reflection)

8.     What are computer models good for?

9.     Review of new terms used.


Assessment questions (suggested):
  • How can computer models be used to learn about the real world?
  • What kinds of things would you rather model on a computer than in real life?
  • What are some key differences between a model and the real world?
  • We've heard about three characteristics of complex adaptive systems (many interacting agents or parts, simple rules, and emergent patterns).  Given those characteristics, is a clock a complex adaptive system?  Why or why not?

NGSS Scientific and Engineering Practice Standards

Practice 1: Asking questions and defining problems

1A: Ask questions that arise from careful observation of phenomena, models, or unexpected results.

1F: Ask questions that can be investigated within the scope of the classroom, outdoor environment, and based on observations and scientific principles.

Practice 2: Developing and using models

2A: Evaluate limitations of a model of a system (not for a proposed object or tool.)

2C: Use a model of simple systems with uncertain and less predictable factors.

2E: Use a model to predict and/or describe phenomena.

2G: Use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.

Practice 3: Planning and carrying out investigations

3D: Produce data to serve as the basis for evidence to answer scientific questions or test design solutions under a range of conditions.

3E: Collect data about the performance of a proposed system under a range of conditions.

Practice 4: Analyzing and interpreting data

4B: Use graphical displays to identify temporal and spatial relationships.

4D: Analyze and interpret data to provide evidence for phenomena.

Practice 5: Using mathematics and computational thinking

5A: Use digital tools (e.g., computers) to analyze data sets for patterns and trends.

5B: Use mathematical representations to describe and/or support scientific conclusions and design solutions.

Practice 6: Constructing explanations and designing solutions

6B: Construct an explanation using models or representations.

Practice 7: Engaging in argument from evidence

7C: Construct and present an oral argument to support or refute a model for a phenomenon.

NRC Crosscutting Concepts

1. Patterns:

1D: Graphs, charts, and images can be used to identify patterns in data.

3. Scale, Proportion, and Quantity

3A: Time, space, and energy phenomena can be observed at various scales using models to study systems that are too large or too small.

3E: Phenomena that can be observed at one scale may not be observable at another scale.

4. Systems and Systems models

4B: Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.

4C: Models are limited in that they only represent certain aspects of the system under study.

7. Stability and Change:

7A: Explanations of stability and change in natural or designed systems can be constructed by examining the changes over time and forces at different scales, including the atomic scale.

CSTA K-12 Computer Science Standards

CT

Modeling & simulation

2-11

Analyze the degree to which a computer model accurately represents the real world.

CT

Modeling & simulation

2-9

Interact with content-specific models and simulations to support learning and research.

CT

Modeling & simulation

3A-8

Use modeling and simulation to represent and understand phenomena.

CT

Modeling & simulation

3B-8

Use models and simulation to help formulate, refine, and test scientific hypotheses.

CT

Modeling & simulation

3B-9

Analyze data and identify patterns through modeling and simulation.

 

Responsiveness to various student needs

In Project GUTS, we integrate teaching strategies found to be effective with learners with various backgrounds and characteristics such as economically disadvantaged students (EDS), students from underrepresented groups in STEM (URG) , students with disabilities (DIS), English Language learners (ELL), girls and young women (FEM), students in alternative education (ALT), and gifted and talented students (GAT).  In each lesson we describe the accommodations and differentiation strategies that are integrated in the activities to support a wide range of learners.

 Module 1 Lesson 1 Activity #1: Walk and Turn Participatory Simulation & Model

(EDS) We validate the use of place [by situating the experiment within the school setting] to keep the students engaged and make a connection of science and school/neighborhood.

(URG)  We use technology to present information in multiple modes of representations.  We choose a modeling and simulation activity that involves student movement, a strategy that uses a multi-modal experience to increase student engagement.

(DIS) We use technology to present information in multiple modes of representations.  We provide multiple means of action, expression, representation and engagement.  These are all principles of Universal Design for Learning.

Module 1 Lesson 1 Activity #2: Introduction to Complex Adaptive Systems

(EDS) We validate the sense of place [by describing neighborhood phenomena such as traffic patterns and ecosystems as complex adaptive systems] to keep the students engaged and make a connection of science and neighborhood.

(ELL) We recommend using a word wall with words with photos or to represent concepts as a language support strategy for English language learners.

(FEM) (URG) We choose a curriculum topic, Complex Adaptive Systems, that has relevancy and real-world application, to interest and engage the girls and students from underrepresented groups in STEM in the class