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DECODE NYC Virtual Lesson Plan - MODIFYING A MODEL: OMNIVOROUS FOXES

Posted January 27, 2021 by wellina

This remote lesson serves as an opportunity for students to modify the code of an agent-based model to reflect the complexity of real-world food webs. Students will evaluate theeffectiveness of the modifications based on their understanding of population dynamics.

Alternative Intro to StarLogo Nova - Modeling Change Lesson 1

Posted July 3, 2017 by sgibbs

The first part of the Modeling Change Unit can be used as a fun stand-alone programming activity for students unfamiliar with StarLogo Nova. It guides students to build a model that use keyboard controls to change the two-dimensional location of agents (in section 1a) and change other traits including the third dimension (z), shape, color, and heading (in section 1b).

Crash Course on Design Thinking

Posted April 3, 2017 by turtle

A 90-minute "virtual crash course" on Design Thinking, by Stanford University. A resource for teachers. "Using the video, handouts, and facilitation tips below, we will take you step by step through the process of hosting or participating in a 90 minute design challenge. Through this experience we hope you will take away some of the basic principles of Design Thinking and start to adapt them into your personal and professional routines"

Rubric ideas for assessing computer models

Posted April 5, 2017 by turtle

In December 2015, Code.org teachers were asked for their ideas on 4 important criteria to include in any rubric used to assess computer models. Here are their ideas, in a forum discussion.

Guía de observación de un modelo basado en agentes

Posted May 16, 2017 by Rizzi

Se trata de una guía para poder observar un modelo basado en agentes y reconocer sus diferentes partes, como por ejemplo las abstracciones (quiénes son los agentes, cuál es el entorno, cuáles son las interacciones); la automatización; los supuestos y el análisis.

Ficha de diseño de un modelo

Posted May 16, 2017 by Rizzi

Es una guía con preguntas que deben contestarse cuando se diseña un modelo de simulación basado en agentes.

Papeles en el viento ("Papercatchers")

Posted May 17, 2017 by Rizzi

"Papeles en el viento" (Papercatchers) es una simulación participativa en la que los estudiantes aprenden sobre el crecimiento de la población y los límites al crecimiento. Los estudiantes desempeñan el papel de miembros de una población creciente, siguen reglas sencillas que rigen la supervivencia y la reproducción, y recopilan y grafican datos.

Modeling Change

Posted July 3, 2017 by sgibbs

This contributed curriculum physics unit introduces and builds models to explore concepts of independent and dependent change, constant and variable x and y change, gravity, and projectile motion. Each lesson contains detailed instructions on how to build each model, and links to base models and completed projects. Modeling Change Lesson 1 is also uploaded as an independent resource (since it can serve as an alternative introduction to StarLogo Nova).

Interview with Hal Scheintaub

Posted August 2, 2017 by ilee

Teachers with GUTS interviewed Hal Scheintaub and demo of StarLogo Nova models created by his students on August 2, 2017.

What's Represented?

Posted June 12, 2019 by ilee

These exercises ask the learner to identify abstractions in the computer model as compared to a diagram or image of a natural phenomenon.

Skill Building Deck

Posted June 12, 2019 by ilee

A slide deck of exercises to build CS and decoding skills

NGSS Standards

Posted October 14, 2019 by ilee

Document highlighting the conceptual shifts in the Next Generation Science Standards

Prisoner's Dilemma (Tit for Tat)

Posted March 30, 2017 by turtle

A participatory simulation where partners examine strategies of cooperation versus individual gain. Based on the game theory activity of Prisoner's Dilemma, this activity introduces students to the contrast between theories of "Tragedy of the Commons" (individuals maximizing their own gain will result in collapse of the resources) and classic economic theory (maximum individual gain will lead to greatest efficiency).

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