Farsi / Persian
NetLogo Models Library:
This model recreates a rollypolly experiment with two chambers in conditions decided by the user. The two possible conditions are moist or dry. Users can also set which condition rollypollies prefer. The rollypollies start in the middle and move towards their preferred chambers when the experiment starts.
The user selects conditions for each of the chambers using the two choosers and the preferred conditions for the rollypollies. The rollypollies will move around randomly each second (which maps to one tick in NetLogo). The only exception to this is when rollypollies are in their preferred environment. When this happens they will only move randomly half the time.
NUMBER-OF-ROLLYPOLLIES is a slider that ranges from 0-50. It controls the number of rollypollies in the model.
CONDITION-IN-CHAMBER1 and CONDITION-IN-CHAMBER2 are choosers that control the condition of the chambers. The two options are dry or moist.
PREFERRED-CONDITIONS is an input box that sets the preferred condition. The user must type in
moist for it to be effective.
Does changing the number of rollypollies in the chambers affect anything?
Is there a difference between the rollypollies preferring dry conditions or moist conditions?
Try changing the preferred condition in the middle of the experiment. What happens as a result of this? Hint: Use the plots to help you.
Try changing the chamber conditions in the middle of the experiment. What happens as a result of this?
This model was incorporated into an Animal Behavior Experimental Lab which was designed for high school Advanced Placement (AP) Biology students. Within the lab, these students simulated agent-level interactions to model their prior hands-on lab experiments.
The associated unit contains several iterations of this rollypolly model:
The basic model Students use the model to make observations and conduct experiments regarding habitat preference behavior of rollypollies.
An introductory model with suggested time intervals Students are asked to record data after different time intervals and across different numbers of rollypollies. They are expected to learn about the nuances of experimental design (large sample size, multiple trials, etc.).
The model extended with CODAP, a data science tool Students use a computationally enhanced data collection method to record and analyze data using CODAP, a computational tool for data visualization and analysis.
A NetTango version that allows students to code with programming blocks Students use a block-based coding environment, NetTango, to code habitat preference behavior.
This is a very simple model that is easy to extend. Here are some ideas on things to implement in the model:
This model uses the INPUT widget of NetLogo to allow user set the PREFERRED-CONDITION by rollypollies, in effect, allowing the user to edit the code of the model without having to search through the CODE tab.
Checkout the Bug Hunt Speeds in the Models Library.
If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.
For the model itself:
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This model was developed as part of the CT-STEM Project at Northwestern University and was made possible through generous support from the National Science Foundation (grants CNS-1138461, CNS-1441041, DRL-1020101, DRL-1640201 and DRL-1842374) and the Spencer Foundation (Award #201600069). Any opinions, findings, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding organizations. For more information visit https://ct-stem.northwestern.edu/.
Special thanks to the CT-STEM models team for preparing these models for inclusion in the Models Library including: Kelvin Lao, Jamie Lee, Sugat Dabholkar, Sally Wu, and Connor Bain.
Copyright 2020 Uri Wilensky.
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