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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.

Neural Network Game

Posted December 10, 2019 by ilee

This is a presentation / activity presented at AAAI/AI4k12 2019 on teaching about neural networks through a participatory simulation.

Skill Building Deck

Posted June 12, 2019 by ilee

A slide deck of exercises to build CS and decoding skills

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.

Debugging Guide

Posted May 26, 2018 by sgibbs

A short guide for identifying and fixing common bugs in StarLogo Nova 2.0.

The Giraffe and the Platypus

Posted June 12, 2017 by sgibbs

This is an activity that allows teachers in a workshop to experience and explore the equity issue involved in differences in background knowledge of students.

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.

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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