AcaWiki - User contributions [en]

AcaWiki:SOPA-RWA

2012-02-21T08:40:03Z

Dcoetzee: /* Time to take down banner? */

A bunch of sites are doing some form of blackout or soft blackout (interstitial) on Wednesday (Jan 18) against SOPA. See mockups for English Wikipedia at https://en.wikipedia.org/wiki/Wikipedia:SOPA_initiative/Blackout_screen_designs

It'd be nice if AcaWiki could join in, and even nicer if it also promoted opposition to [https://en.wikipedia.org/wiki/Research_Works_Act Research Works Act] which would make it for people not at rich universities to access primary research in order to summarize.

I don't know that anyone has done a slick contact-all-relevant page for RWA -- http://www.taxpayeraccess.org/action/action_access/12-0106.shtml may be closest, good to link to if there isn't anything better.

==Status==
* http://lists.ibiblio.org/pipermail/acawiki-general/2012-January/thread.html#298
* Implemented site notice variation below. Text, links, presentation could all surely be improved.

==Presentation options==

* Interstitial: would require javascript, adding ref to javascript in <head>, presumably in a MediaWiki theme
* Site notice: fat banner using https://www.mediawiki.org/wiki/Manual:Interface/Sitenotice '''(done)''' and nice to add https://www.mediawiki.org/wiki/Extension:DismissableSiteNotice
* Blackout: "redirect" entire site to static page. Would require rewrite rule and static html somewhere, or replace index.php

==Proposed message==

Two bills are making their way through the U.S. Congress that would have highly negative consequences for AcaWiki and the public good. Please take action against both.

Many large sites are blacking out January 18 to spur action against '''SOPA'''. Visit '''[http://americancensorship.org americancensorship.org]''' to take action against this bill, which is a censorship and security risk for the entire internet. Wikimedia's General Counsel explains [https://blog.wikimedia.org/2011/12/13/how-sopa-will-hurt-the-free-web-and-wikipedia/ how SOPA would hurt wikis].

'''RWA''' would prohibit federal agencies from conditioning their grants to require that articles reporting on publicly funded research be made accessible to the public online. This is [https://www.nytimes.com/2012/01/11/opinion/research-bought-then-paid-for.html unjust], and would specifically harm AcaWiki, greatly reducing the number of people with access to important literature -- access is required to summarize. Please tell '''[http://www.taxpayeraccess.org/action/action_access/12-0106.shtml congresspeople to oppose RWA]'''.

==Time to take down banner?==
While I admire AcaWiki protesting against legislation that impacts it, leaving it up for weeks at a time on a site with very little traffic is not going to make a big impact and deter the site from growing so that it ''can'' have bigger impact and fulfill its original mission. I think it's about time to take down the banner. [[User:Dcoetzee|Dcoetzee]] 09:40, 21 February 2012 (CET)

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T16:56:10Z

Dcoetzee:

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using MIT's StarLogo system, graphical educational software for simulating an emergent system. An ''emergent system'' is a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the educational benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of the experimenter moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering temperature and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T16:55:32Z

Dcoetzee:

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using a prototype of MIT's StarLogo system, graphical educational software for simulating an emergent system. An ''emergent system'' is a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the educational benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of the experimenter moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering temperature and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T16:54:45Z

Dcoetzee:

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using a prototype of MIT's StarLogo system, educational software for simulating an ''emergent system'', a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the educational benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of the experimenter moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering temperature and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T16:53:50Z

Dcoetzee:

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using a prototype of MIT's StarLogo system, educational software for simulating an ''emergent system'', a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the educational benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of the experimenter moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering heat and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T16:52:43Z

Dcoetzee:

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using a prototype of MIT's StarLogo system, educational software for simulating an ''emergent system'', a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the educational benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering heat and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

2012-02-20T13:38:22Z

Dcoetzee: Create

{{Summary
|title=Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World
|authors=Uri Wilensky, Mitchel Resnick
|url=http://ccl.northwestern.edu/papers/levels/levels.html
|tags=emergent,emergence,education,science education,levels,dynamic systems,abstraction,educational technology
|summary=This work presents three case studies using a prototype of MIT's StarLogo system, educational software for simulating an ''emergent system'', a system where complex large-scale behavior emerges from the interaction of simple, localized behavior of many agents, such as a traffic jam arising from interactions of individual vehicles. The goal is to demonstrate the benefits of approaching scientific problems as emergent systems, while also highlighting conceptual errors due to confusion between the large-scale and small-scale behavior in these systems.

The first model simulates a simple abstraction of a slime mold, designed to encourage homogeneous agents to aggregate into large clusters. SLIME highlights several counterintuitive concepts that students struggled with:

* The idea that a cluster can be viewed both as a singular entity with large-scale behavior and as a collection of agents with small-scale behavior;
* The idea that random behavior of agents is essential (rather than disruptive) to the development of large clusters;
* The idea that giving agents more information may in fact lead to smaller clusters, contradicting the intuition that they are "trying" to form large clusters.

Scientists once believed that aggregation of slime mold was organized by a differentiated leader cell rather than an emergent outcome, which the authors call the "centralized mindset": "When people see patterns in the world, they tend to assume centralized control, even if it doesn't exist."

The second case study focuses on GasLab, a simulation of an ideal gas in a box created by a teacher. The simulation reproduced and offered insight into the Maxwell-Boltzman distribution of particle speeds, and highlighted the importance of moving continually between the large-scale and small-scale "levels," explaining one using the other. Students refined GasLab by altering heat and volume, and developing a way to measure the resulting pressure.

The third case study involved a predatory-prey system. Whereas such systems normally require differential equations to analyze, students using these systems replicated the oscillatory populations of predators and prey over time with only simple computational rules for agents defining when birth and death occur. This also creates a more personal experience for students, who can imagine themselves in the place of individual agents.
|relevance=The authors' main argument, that emergent systems should be taught in school to engender a more personal and accurate exploration of scientific phenomena, remains untested at a larger scale, and has not been explored in an experimental setting. In 2005, Chi found that misconceptions of emergent systems, such as those mentioned in this work, are more robust than those in direct systems ("[[Commonsense Conceptions of Emergent Processes: Why Some Misconceptions Are Robust]]").

As of 2012, [http://education.mit.edu/starlogo/ MIT's StarLogo] is still available and contributing to innumerable new publications in diverse areas, and the three models studied in this work are still available ("[http://education.mit.edu/starlogo/samples/slime.htm Slime]", "[http://ccl.northwestern.edu/netlogo/models/GasLabGasinaBox Gas Lab Gas in a Box]", and "[http://education.mit.edu/starlogo/models/library/EcosystemPredatorPreyGrass Ecosystem - Predator, Prey, and Grass]").
|journal=Journal of Science Education and Technology
|pub_date=1999
|doi=10.1023/A:1009421303064
|subject=Education
}}

User:Dcoetzee

2012-01-28T03:19:15Z

Dcoetzee:

{{User
|name=Derrick Coetzee
|photo=Derrick Coetzee in hat and necklace.jpg
|location=University of California, Berkeley, Berkeley, CA, United States
}}
Hi all, I'm Derrick Coetzee, as of 2012 a graduate student at University of California, Berkeley researching software engineering and a long-time administrator at the English Wikipedia and Wikimedia Commons projects. I have written a number of paper summaries in the past on my blog [http://papersincomputerscience.org Papers in Computer Science], and find this project exciting. See [http://moonflare.com Moonflare.com] for links to my various sites.

User:Dcoetzee

2012-01-28T00:19:15Z

Dcoetzee:

{{User
|name=Derrick Coetzee
|photo=Derrick Coetzee in hat and necklace.jpg
|location=University of California, Berkeley, Berkeley, CA, United States
}}
Hi all, I'm Derrick Coetzee, as of 2012 a graduate student at University of California, Berkeley researching software engineering and a long-time administrator at the English Wikipedia and Wikimedia Commons projects. See [http://moonflare.com Moonflare.com] for links to my various sites.

User:Dcoetzee

2012-01-28T00:18:54Z

Dcoetzee: Created page with "{{User |name=Derrick Coetzee |photo=File:Derrick Coetzee in hat and necklace.jpg |location=University of California, Berkeley, Berkeley, CA, United States }} Hi all, I'm Derrick ..."

{{User
|name=Derrick Coetzee
|photo=File:Derrick Coetzee in hat and necklace.jpg
|location=University of California, Berkeley, Berkeley, CA, United States
}}
Hi all, I'm Derrick Coetzee, as of 2012 a graduate student at University of California, Berkeley researching software engineering and a long-time administrator at the English Wikipedia and Wikimedia Commons projects. See [http://moonflare.com Moonflare.com] for links to my various sites.

File:Derrick Coetzee in hat and necklace.jpg

2012-01-28T00:16:07Z

Dcoetzee: User photo for User:Dcoetzee. Taken by User:Dcoetzee using remote shutter. Licensed under Creative Commons Zero Waiver.

User photo for [[User:Dcoetzee]]. Taken by User:Dcoetzee using remote shutter. Licensed under Creative Commons Zero Waiver.

File:DSC 1982.cropped.jpg

2012-01-28T00:15:23Z

Dcoetzee:

'''(Uploaded this file under wrong name, please delete)'''

File:DSC 1982.cropped.jpg

2012-01-28T00:14:38Z

Dcoetzee: User photo for User:Dcoetzee. Taken by User:Dcoetzee using remote shutter. Licensed under Creative Commons Zero Waiver.

User photo for [[User:Dcoetzee]]. Taken by User:Dcoetzee using remote shutter. Licensed under Creative Commons Zero Waiver.