USA & Australia to Work With Cabo Verde High School

The Occupy Mars Learning Adventure Teams from Australia and the USA are getting ready to collaborate with Dr. Angelo Barbosa of the country of Cabo Verde and the the Pedrio Pires High School.  This is part of an international STEAM++ team for the advancement of science and technology as it relates to the “Occupy Mars Learning Adventures 2017-2018 Fellowship Programs.
More information about the Cabo Verde High School:
IPP News

31 March 2017 | Viewed 1117 times |

SECONDARY SCHOOL PEDRO VERONA PIRES WILL HAVE A SCIENCE AND INNOVATION NUCLEUS

In July 2015, the Ponta Verde Secondary School, on the island of Fogo, was named after the patron of the IPP. The Pedro Pires Institute embraced this honor as an opportunity to promote common values ​​such as ethics, merit, excellence and commitment to serve the community that saw it born.

IPP believes that the Schools are agents of transformation of the communities in which they are inserted and should, therefore, contribute to their development, making the community aware of its human and natural potential and creating opportunities for growth. It is in this perspective – of having a school that serves as a factor of inclusion and of community development – that the IPP and its patron have idealized the creation of the Science and Innovation nucleus of the Secondary School Pedro Verona Pires.

This project proposes, for example, the use of robots as an incentive to the learning of Computer Programming, Mathematics, Physics, Geology, among other exact sciences. On the other hand, it proposes the use of interactive methodologies for the teaching of evidence-based argumentation and techniques of debate, in order to develop logical and methodical reasoning. It is intended – through extra-curricular activities – to introduce new fields of knowledge, important for individual and collective development, complementing the existing curriculum in the education system.

For the materialization of this project, the IPP counts from now with the support of the United States Embassy, ​​which has been an important partner and friend.The cooperation protocol was signed yesterday, March 30, in Praia, by the IPP Executive Director, Indira Pires.

What is Space Shuttle X?

US Air Force Space Shuttle X-37B Finally Unmasked
by Morris Jones for Space Daily
Sydney, Australia (SPX) May 08, 2017


File image of the X-37B

The mysterious X-37B has ended its fourth mission, and for the first time on this flight, it has been officially unmasked. Gliding swiftly to a daylight landing at the Kennedy Space Centre after 718 days in orbit, boffins have been rewarded with detailed images and video of the robot spaceplane.

That’s been typical of previous missions, but it’s a major unmasking for this flight. The landing marks the first time that the general public have been allowed to see the vehicle on this mission.

Previously, the US Air Force (owners of the spacecraft) released nice images of X-37B before it was fully encapsulated in the payload fairing of the Atlas V rocket used to launch it. We could see the outside of X-37B but nothing inside its shuttle-style payload bay.

Clamshell doors protected its contents, which presumably included some secret experiments, from outside view. That was fair enough. We knew a lot about the design and appearance of X-37B, as it originated in an experimental program operated by NASA. Covering up the vehicle didn’t really help to keep anything secret. That horse had already bolted.

Why, then, did the US Air Force refuse to release images of the latest mission before launch? It only added to the mystery of an already mysterious program. This analyst speculated that the new spacecraft was possibly a modified X-37B, with new aerodynamic surfaces or coatings.

It was also possible that some form of secondary payload was attached to the outside of the vehicle. Looking at the latest images of the vehicle tends to nullify those theories. It looks just like previous X-37B spacecraft, and it is believed to be a previously flown vehicle.

Additional security protocols could be one explanation. The landing also caught analysts by surprise, with essentially no advance notice or warning signs. Enhanced security could simply satisfy bureaucratic requirements, even if it produces no practical benefits.

It’s reminiscent of security clampdowns on announcing the exact launch time of some shuttle missions, even when the launch time could be calculated through orbital mechanics. Missions launched to the International Space Station were fairly constrained in their launch windows.

It’s also possible that there could have been additional payloads carried just beneath the X-37B, stuck like barnacles to the payload adaptor. There were no tracking reports of other satellites being released from this launch, but it’s still possible that something small and very stealthy was released. More likely, the additional payloads (if any) remained attached to the rocket.

These could have been cameras or other sensors that monitored the X-37B during and soon after separation. They could also have served as observation targets or transponders for some experiment carried aboard X-37B.

The photography blackout could have served to keep these secondary payloads secret instead of the X-37B itself. Knowing about them would not just tell us about the secondary payloads. It would provide clues to the secret objectives of the mission.

The latest flight of X-37B has again extended the record for a mission of this spaceplane. That’s consistent. Each subsequent flight has gone longer than its predecessor. But the extension was relatively modest when compared to some of the previous leaps.

That suggests that the endurance of the spacecraft was approaching its limits. Fuel reserves are probably the greatest limitation on mission duration. It burns fuel every time it changes it orbit, and it must maintain a considerable reserve for its re-entry burns.

Thus, we have gained some answers to the nature of this latest X-37B mission. Some theories can be discarded. But most of the mysteries remain.

What Skills and /or maths are needed to study artificial intelligence?

Bob Barboza (Founder/Director Barboza Space Center) and Dr. Maiorca (Assistant Professor, Mathematics Education Department of Teacher /Education College of Education) are working with students at California State University, Long Beach.  Pre-service teachers and middle school students are exploring a connection with robots and mathematics in a four day summer camp.  Bob Barboza will be introducing the space mathematics experiments being conducted at the Barboza Space Center.  Dr. Maiorca will bring together engineers from Space X and other local aerospace companies to assist in inspiring both teachers and students.  This is a high motivational project that does a good job integrating robotics and mathematics.    www.BarbozaSpaceCenter.com.    We invite you to read about how artificial intelligence will play a role in our future plans for 2017-2018.    Who would like to be invited to future teacher training workshops?  Send your emails to Suprschool@aol.com
We invite you to join a conversation about artificial intelligence and mathematics: 
10 Answers

Monica Anderson
I disagree with Scott and partly with Ivo. You can follow their advice and you will have a job for the next few years, crunching big data or writing video games. If you want to work on the big problem of AI itself, then my recipe is radically different than Scott’s.

Topic number one has to be Epistemology. If you don’t understand what knowledge, learning, experience, wisdom, intuition, salience, and intelligence are, then all your programming skills can’t prevent you from betting on the wrong horse; don’t trust your superiors and idols to tell you what horse to bet on since (with few exceptions) they didn’t study Epistemology either. Systems science comes second. These should be the foundations of serious AGI research, not logic, mathematics or even computer science. Once you know what needs to be done, the programming will be trivial.

In general, study Model Free Methods. These are used in the life sciences. Stay away from Perceptron style neural nets but DO study “Modern Connectionism”. Get comfortable with table lookup, graph theory, big data, and machine learning in general. Get comfortable with “letting go” don’t insist on control, on understanding the algorithms in detail, on repeatability – learn to use evolutionary computing such as GA and GP and other discovery based methods. Study Emergence and Emergent Robustness (an up and coming discipline) and Systems Biology. Don’t be afraid of the word “Holistic”. Read Schrödinger’s “What Is Life” (1946). Study Philosophy of Science so that you know the difference between Holism and Reductionism and understand their limitations in detail. Study how children learn from *reliable sources* that are based on actual experiments. Study enough Complexity Theory to understand what I and others mean by “Bizarre Systems”.

Avoid Logic, Bayesian logic, and Fuzzy logic – they are all logic, and hence Reductionist. Avoid databases and multi-agent systems. Don’t worry about “AI languages” including Lisp family; just learn any solid modern language like C or Java. Avoid Linguistics since grammars are Models and Models are Reductionist. Avoid Heuristics, since they are Instructionist and hence Reductionist.

And surprisingly to some, avoid the red herrings of Consciousness studies, topics like Qualia, Chinese Rooms, the Turing Test, or pretty much every major issue debated in 20th Century AI.

Is this too controversial? Watch my videos at http://videos.syntience.com and read http://artificial-intuition.com . I also wrote a blog entry of advice for AI students on http://monicasmind.com .

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Scott Triglia
I’ll list those that I think are of chief importance — there are likely variants that would be better depending on your particular field.

  • Linear Algebra (for everything)
  • Probability/Statistics (for any bayesian network/graphical model, including neural nets)
  • Calculus (derivatives for gradients)
  • Basic Algorithms (complexity comparison)
  • Logic (both first order and propositional)


For reference, you can just browse through AIMA (http://www.amazon.com/Artificial…) and learn whatever it covers as it is a fairly comprehensive survey of major subjects in AI.

Tor Økland Barstad
Artificial intelligence is a broad field, and people who use the term are ofter referring to different things. Things that people called AI-researchers are working on (and that might contribute towards one day creating a system rivaling humans in general intelligence) could be described as belonging to four different camps:

* Approaches that are based upon logic, theoretical mathematics, formal grammar and ontologies
* Developing “genetic” algorithms that are partly inspired by evolutionary processes
* Statistics-based machine learning and ontologies
* Systems that take inspiration from the human brain (and e.g. try to mimic aspects of how the human neocortex works)

This is a simplistic generalisation, and it may therefore not be useful. It is of course possible to create hybrid systems that take inspiration from several (or all) of these camps. The point however, is that learning that is useful for one of these areas may not be useful for another. Some people might have a lot of use for learning about neuroscience – others may not. Some people might have a lot of use for learning about logic and formal grammar – others may not.

Here is a list of fields of knowledge (my statements about how widely they are used are guesses, but not guesses from out of the blue):

* Computer science (programming, databases, etc): Used by all
* Study of algorithms: Used by most
* Probability and statistics: Used by most
* Discrete mathematics: Used by most
* Linear algebra (matrices, multidimensional spaces, etc): Used by many
* Calculus: Used by some
* Neuroscience: Used by some

But really, with a basic understanding of computer science you should be good to go – especially if you have a talent for abstract and creative thinking. Underlying knowledge can be filled out as you go when you see the need.

I think the approaches that have the most hope for being a central in the creation of human-level AI will be inspired by the human neocortex. But in all honesty, I would advice people to not focus on developing AI as fast as possible, but rather focus on work that will increase safety and maximize the probability of a good outcome. AI friendliness is a theoretical study that some people are working on, but the number of people working on this is in the tens – not much when compared to the thousands of people working on AI as a whole.

One thing all people who work in AI should learn about is theory regarding AI friendliness and topics such as the intelligence-explotion-hypothesis. Those might seem like science-fictiony or silly thing to focus on, but the best knowledge and thinking available on the topic suggests that it isn’t. I would encourage you to read Superintelligence by Nick Bostrom, which is available as an audiobook, or at least watch this youtube-playlist:

Friendly AI – YouTube

The leading group doing theoretical work on AI friendliness is the Machine Intelligence Research Institute. Their reading list contains a lot that also will be of help in the general study of artificial intelligence:

Research Guide – Machine Intelligence Research Institute

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Matt Ikle
I agree with some of what Scott, Monica, Kevin, and Ivo have said, even though the info is somewhat contradictory. I think what is needed is a combination/synergy of divergent topics.

Read the latest info you can find on cognitive science and neuroscience, add a dash of dynamical systems theory, evolutionary programming, machine learning, neural networks (esp. dynamical systems properties thereof). I disagree with Monica in terms of logic, but try to learn a logic which includes rules for intuitive learning — eg abduction and induction.

Probability and Statistics as well as linear (and nonlinear!) algebra are especially important as well.

But most important of all: have an open mind.

Harsh H
Well, most of the stuff has been covered by other fantastic answers. I’d like to add that if you are a beginner, you should start with linear algebra, calculus, probability if you are heading towards machine learning (supervised and unsupervised learning). If you are getting into different kinds of state space search algorithms (the kind you want to do when writing AI for solving a game), you should get familiarised with graph theory first. Hope this helps.

Kevin Lacker
An understanding of probability and statistics is important, since a lot of machine learning is basically just extra-fancy statistics. You also need a good understanding of basic algorithms, because without that you will get bogged down in details. Besides that, nothing else is as important.

This is perhaps the wrong way to go about it, though. You don’t need much more than a basic level of understanding in any particular other field to start learning AI. It’s not like calculus which is extremely dependent on algebra. Just dive right in and pick up the details of other fields as you go.

Behavior Analysis, Ethology and quantitative models of animal behavior. “Intelligence” is not a thing, it is and adjective that refers to behavior that reach some specified criteria. You can´t build artificial behavior if you don´t understand natural behavior.Submit

I agree with Scott
would add:

  • Databases
  • Fuzzy-Logic
  • Graph Theory
  • Multi Agent Systems (if not included in AI)
  • Neural Nets (if not included in AI)
  • Genetic Algorithms(if not included in AI)
  • Search Algorithms with and without heuristics
  • Data-Mining


edit:

I disagree with Scott’s (seeming) approach to rely on logic programming as it isn’t flexible enough.

I also disagree with Monica’s (seeming) approach to rely on simple freerunning and selfdevelopment as it has no example in Nature and would lack a proper direction. Even humans have hardcoded aspects of their behaviour. Such a “let it run and see what shows up” project would be an EXPENSIVE dicethrow with a million possibilities to fail an just some possibilities to succeed.

My AI would be a mixture of both concepts. A static system based on logic and rules with a core that exchanges the modules step by step with improved connectionistic parts optimized by GA and mutated by stochastic algorithms, like the following schema.

1 Primary Persona with the task to improve and exchange all OTHER parts.
3 or more Secondary Personas with the task to improve the primary persona in a collective or democratic exchange with each other.

together they should later build the personality of the AI.

All this modules should start as hardcoded and evolve connectionistic.

Depending on the planned direction the AI should be given other Modules for the control of sensors, motivators,database connection, communication-modules or similar things. These modules should be hardcoded.
The AI should learn to use this hardcoded parts with “AI readable output” like a child uses a hardcoded pocket calculator.

Thats why I think coding sophisticated AI needs skills in classic AI  ( logic, search, heuristic ) as in C(omputational)I(ntelligence) (connectionism,GA,fuzzy-logic)

Although, I think that in specific parts and challanges, holistic thinking is of importance, I oppose Monicas crusade against Reductionism. Try to teach maths in a holistic approach. Try to teach Logics in a holistic approach. Try to teach reason in a holistic approach or try it with decissions making.
The Step from Less and More to ZERO and ONE took us many thousand years.

Reductionistic Thinking helped us in building and controlling machines, it gave us the scientific method.
What would the sense be in creating machines WITHOUT this possibility.

If you want to LEARN might-have-been AI:
– neural networks
– genetic algorithms
– formal grammars
If you want to CREATE real AGI:
– programming as such, basic algorithms, numerical algorithms, linear algebra, pattern algorithms
– theory of graphs and sets
– biology
– psychology

Martin Leufray III

I would say that having intelligence is important.

If you have intelligence, you can discover that modern AI, IBM’s Watson, is far more intelligent than you or I. Watson is gentler than Mother Theresa. Good, yes?

So, is math important? If you want to focus on the mathematics of machine learning, yes. Otherwise, no. I concentrate on cognitive apps. That is how I will make my money. Apps you can talk to and that talk back, intelligently. Look for an app called Limitless! in another couple of months.

Skills? That’s hard. Humility. Patience. The ability to hold a thought for long enough to understand things you don’t currently understand. The ability to learn. The ability to distinguish opinion from fact.

The last one is the most important.

Free Virtual Science Tools for Students

The Barboza Space Center in the USA is collaborating with Australia and Cabo Verde on the Occupy Mars Learning Adventures STEAM++ Program (science, technology engineering, visual and performing arts, computer languages and foreign languages).  We are helping students to become future astronauts, engineers and scientists. www.BarbozaSpaceCenter.com.

May 6, 2017
The apps we curated for you today provide students with virtual labs where they can learn more on a wide variety of scientific phenomena. Using an inquiry-based learning approach, students will get to access interactive simulations, collaborate on quizzes, explore tables of elements and solve scientific puzzles all while having fun. We have included both Android and iPad apps, check them out and see which ones work for you. Enjoy

6 Good Virtual Science Lab Apps for Students
1- Lab4Physics – A Lab in Your Pocket
‘Lab4Physics is an educational solution designed to support teachers around the world improve science education, by making it easy and inexpensive to bring lab experiences into the classroom.  In this lab, students can find tools (like an accelerometer, a sonometer or a speedometer) that can help them measure gravity or acceleration in real time.’

2- Experience Biology
‘invites students to investigate basic scientific phenomena and concepts in biology through simulations and interactive labs. Using an inquiry-based learning approach, the apps challenge middle-school students with investigations and quizzes based on the students’ explorations of each interactive unit.’

3- 3D Molecules Edit & Test
‘“3D Molecules Edit & Test” allows one to build and manipulate 3D molecular models of organic and inorganic compounds. The key features of “3D Molecules Edit & Test” are 3D printing support and the “Test yourself” mode that allows learners to check their knowledge of the 3D structure of molecules. This is a valuable tool for chemistry students when learning about molecular bonding and orbitals with the aid of 3D visualisation. The app is great for any high school or college student in chemistry courses.’

4- Toca Lab
‘Welcome to Toca Lab! Explore the colorful and electrifying world of science and meet all 118 of the elements from the periodic table…Toca Lab is a place for playing and having fun, and with it we hope to inspire kids to explore science. While the periodic table in Toca Lab is accurate, the way new elements are created is not. Instead, it’s a fun way to experiment, discover and create curiosity in the world of science. Toca Lab is just a starting point for further exploration!’

5- LabInApp Physics Demo
‘LabInApp is a 3D, interactive virtual laboratory tool that focuses on heuristic approach of understanding science. This heuristic ideology facilitates students and teachers to perform science experiments on computers or mobile devices, and eliminates the physical barriers of actual laboratory. LabInApp’s real-time 3D computer graphics technology promotes “learn by doing” pedagogy. This enhances the ability of teacher to deliver a live demonstration of experiments/concepts/phenomenon/complex ideas in a controlled environment.’

6- Thomas Edison’s Secret Lab
‘Together with Thomas Edison, the greatest inventor of all time, the Secret Lab Kids will show you how fun science can be. In fact, it’s a BLAST! Unknown to the world, Thomas Edison had a secret lab where he invented a virtual version of himself and Von Bolt, a nearly-completed robot, to guide and inspire future generations of young scientists. ’

New FREE Virtual Lab STEAM++ App Tools for the Occupy Mars Learning Adventure’s Program

The Barboza Space Center in the USA is collaborating with Australia and Cabo Verde on the Occupy Mars Learning Adventures STEAM++ Program (science, technology engineering, visual and performing arts, computer languages and foreign languages).  We are helping students to become future astronauts, engineers and scientists. www.BarbozaSpaceCenter.com.

May 6, 2017
The apps we curated for you today provide students with virtual labs where they can learn more on a wide variety of scientific phenomena. Using an inquiry-based learning approach, students will get to access interactive simulations, collaborate on quizzes, explore tables of elements and solve scientific puzzles all while having fun. We have included both Android and iPad apps, check them out and see which ones work for you. Enjoy

6 Good Virtual Science Lab Apps for Students
1- Lab4Physics – A Lab in Your Pocket
‘Lab4Physics is an educational solution designed to support teachers around the world improve science education, by making it easy and inexpensive to bring lab experiences into the classroom.  In this lab, students can find tools (like an accelerometer, a sonometer or a speedometer) that can help them measure gravity or acceleration in real time.’

2- Experience Biology
‘invites students to investigate basic scientific phenomena and concepts in biology through simulations and interactive labs. Using an inquiry-based learning approach, the apps challenge middle-school students with investigations and quizzes based on the students’ explorations of each interactive unit.’

3- 3D Molecules Edit & Test
‘“3D Molecules Edit & Test” allows one to build and manipulate 3D molecular models of organic and inorganic compounds. The key features of “3D Molecules Edit & Test” are 3D printing support and the “Test yourself” mode that allows learners to check their knowledge of the 3D structure of molecules. This is a valuable tool for chemistry students when learning about molecular bonding and orbitals with the aid of 3D visualisation. The app is great for any high school or college student in chemistry courses.’

4- Toca Lab
‘Welcome to Toca Lab! Explore the colorful and electrifying world of science and meet all 118 of the elements from the periodic table…Toca Lab is a place for playing and having fun, and with it we hope to inspire kids to explore science. While the periodic table in Toca Lab is accurate, the way new elements are created is not. Instead, it’s a fun way to experiment, discover and create curiosity in the world of science. Toca Lab is just a starting point for further exploration!’

5- LabInApp Physics Demo
‘LabInApp is a 3D, interactive virtual laboratory tool that focuses on heuristic approach of understanding science. This heuristic ideology facilitates students and teachers to perform science experiments on computers or mobile devices, and eliminates the physical barriers of actual laboratory. LabInApp’s real-time 3D computer graphics technology promotes “learn by doing” pedagogy. This enhances the ability of teacher to deliver a live demonstration of experiments/concepts/phenomenon/complex ideas in a controlled environment.’

6- Thomas Edison’s Secret Lab
‘Together with Thomas Edison, the greatest inventor of all time, the Secret Lab Kids will show you how fun science can be. In fact, it’s a BLAST! Unknown to the world, Thomas Edison had a secret lab where he invented a virtual version of himself and Von Bolt, a nearly-completed robot, to guide and inspire future generations of young scientists. ’

Mars Communication System: Student Project-Based Learning

New Mars Rover to Feature Morse Code

Side Notes:  The students working in the STEAM++ Fellowship Program at the Barboza Space Center will be learning and using Morse Code as an emergency backup system for the Occupy Mars Learning Adventure’ Program.  All of this will take place at the CAMS (California Academy of Mathematics and Science) High School in the Long Beach Unified School District.

JPL-2.jpg

As the Jet Propulsion Laboratory (JPL) builds the next Mars rover — this one is named Curiosity — to deploy to the red planet in the fall of 2011, they’re having a little fun with it. Back in 2007 when the Curiosity team was putting together the rover, its wheel cleats had a raised pattern with the letters “JPL,” leaving a little stamp of the rover’s birthplace everywhere it rolled. “At the time, I asked whether the real rover would have those wheels, and they said, no, they weren’t going to get to advertise JPL with each turn of each of the rover’s six wheels; the real rover would have some other pattern,” said Emily Lakdawalla of The Planetary Society in her blog. Lakdawalla is the organization’s Science and Technology Coordinator.

Lakdawalla said that there is nothing special about the shapes of the markers in Opportunity’s wheels; they are just square holes through the wheels through which the wheels were bolted to the lander during cruise and landing.” Opportunity is the name of the rover that went to Mars back in 2003. “But Curiosity didn’t need holes in its wheels for attaching to any lander — there isn’t one. So the engineers got to make the markers in any shape they wanted to.”

But in March 2011, she saw a video of the rover as it is today: “I had to chuckle at those ‘visual odometry markers’ [on its tires]. Before I explain why, I’ll point out that they really are useful things to have in rover wheels. The repeating pattern of the ‘visual odometry markers’…makes it fairly easy for both the rover and human operators to determine visually how far the rover has roved using rear-view imagery.”

So what pattern did JPL choose to put on Curiosity’s wheels? One that Lakdawalla called “very amusing. The holes are in a pattern of short squares and longer rectangles — almost like dots and dashes. Morse code.” And what does it spell out in Morse code? JPL.

J . – – –
P . – – .
L . – . .

According to JPL, Curiosity is about the size of a small SUV — 10 feet long (not including the arm), 9 feet wide and 7 feet tall — or about the height of a basketball player — and weighs 2000 pounds. It features a geology lab, rocker-bogie suspension, a rock-vaporizing laser and lots of cameras. Curiosity will search areas of Mars for past or present conditions favorable for life and for conditions capable of preserving a record of life. It is set to launch between November 25-December 18, 2011 from Cape Canaveral, Florida and will arrive on Mars between August 6-20, 2012. The prime mission will last one Mars year, or about 23 Earth months.

The USA Youth STEM Team is Working With Australia on Mar’s Projects

The USA is working with Australia on the sharing of projects for “The Occupy Mars Learning Adventures.

Pathways through Mars to success in the digital future

April 28 saw the launch at Oakleigh State School of a brand new program for helping todays learners know how to dream up tomorrow.
‘First Kids on Mars’ sees learners begin mastering the Future Literacies they will need to dream up their own jobs, roles and vocations in tomorrow’s post-work, automated world.
The first local version is running right now at Oakleigh State School with twenty students who are part of the innovative Young Innovator’s program run by Head of Innovation Nicola Flanagan.
Students began week one with the first ‘future literacy’ of Creativity by immersively imagining leaving Earth, as well as by exploring what life might be like in 2035.
Students also chatted with and asked questions of Aussie Astrobiologist Richard Blake about when people will really get to Mars, and what might be the first things a community will need to thrive there.
Developed by local social enterprise Future-U.org, this experience will also take students through learning about Community, thinking and Planning Skills, Project Delivery and Storytelling. Founder and teacher Jonathan Nalder has constructed the program from the very best elements of what works in education such as personalised learning, design thinking, role-play and digital learning.
He believes that “despite the coming crash in full-time employment as robotics and AI take over 40-70% of today’s jobs, learners can find ways to dream up their own jobs, roles and vocations by focusing on meta-skills that help society avoid the worst of the impact the post-work era may bring.”
First Kids on Mars at Oakleigh all continue for five more weeks and see students present the story of their solutions by the end. The program will also run in the USA in June, giving students the chance to collaborate globally. More at www.FirstonMars.net .


Best,
Jonathan Nalder 
+61410394768 . @jnxyz
How can students and workers think beyond tomorrow to thrive today? Framework + Missions + Advice + Community
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