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 Great American Eclipse!:
Labdisc Records Solar Eclipse at Multiple US Locations

Students from Fulton county Schools view the eclipse with ISO glasses next to their Labdisc experiment.

Last week, on Monday the 21st the United States experienced a solar eclipse, the first recorded in the country for almost 100 years. During this total solar eclipse, the moon’s diameter appeared larger than the sun’s, blocking all direct sunlight and transforming day into complete darkness.

The path of total eclipse touched 14 states, 16% of the area of the United States and a partial eclipse visible in all the other states. The event began on the Oregon coast as a partial eclipse at 9:06 a.m. (PDT) and ended later that day as a partial eclipse along the South Carolina coast at about 4:06 p.m. (EDT).

What better opportunity for budding young scientists to use the
Labdisc to record a real and live scientific event!

Together with science students, the Globisens team and their US partner Boxlight – recorded the eclipse in Georgia and New York, with Globisens CEO, Dov Bruker recording in Mexico.  Recording with the Labdisc in multiple locations of the eclipse allowed the young scientists to compare the eclipse duration and the lowest level of light as the eclipse traversed the continent.

In Johns Creek, Georgia a group of students from Fulton County Schools setup a Labdisc using the Labdisc plastic rod and a bucket of sand to stabilize it. They recorded the results over a 2-hour period. The eclipse started with a recorded 40,000 lux and decreased to only 256 lux and then increased back to around 35,000 lux when the eclipse concluded. The students also used a home-made box projector to view the shadow created by the eclipse.

As the sensor-triggered street lights turned on during the eclipse, our young students made several additional observations regarding the natural world around them. They noticed that the birds stopped chirping, and the cicada’s (large insect) and crickets started making noise, which they normally do only after sunset.

See more innovative experiment projects using the Labdisc from around the world


Analysing Data

Image result for big data
What has Big Data ever done for me?

The term Big Data is used quite frequently today and it seems that it is an important facet of our daily lives. Is it something that we should be worried about or should we be looking at what it is and work out how to incorporate it in our teaching?
What is Big Data?
Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. We produce 2.5 exabytes of data every day which is the equivalent of 90 years worth of High Definition Videos. The idea of Big Data is not just the amount but the variety of devices which are abe to store the or collect the Data. Being able to analyse data from a variety of sources and being able to draw conclusions from the data is really what the idea behind Big Data is all about. Big Data is information gathered from anywhere be it number of Tweets in a day to the indexing the DNA.

The ability of a computer to process the data varies and even when theImage result for big data analysis is carried out on a subset of the data the amount  of information can be colossal. So why should we consider including data analysis in our teaching plans? Firstly we need to have a skilled work force which can obtain information from data. Governments, schools and businesses make decisions based on the information which has been provided by data collection. If we do not teach our young people these skills then we will be unable to make sense of our world because we are unable to interpret the data being provided.
In my view we should be actively teaching data analysis or data handling. We need to make sure that our young people are able to understand the information they are given on a daily basis from a variety of sources. From the moment they wake up they are making sense of their world. The clock or the mobile tells them what time it is. The weather app provides information so that they can make decisions about what to wear. The television or a buzz feed app lets them know what is going on their world depending on what information their mobiles have about their likes and dislikes based on the information they share with the various apps that they interact with. Having the ability to understand and process this information is a key part of growing up in a digital world so why wouldn’t we teach how to collect and understand the data that is out there.We need to teach data handling so that we have a source of expertise for the future. The decision makers of tomorrow will be very much dependent on the data collected, especially in real time, which could effect the way they do their jobs. We need people who can analyse and report back.
The skills needed can be taught in a cross curricular fashion which takes account of Computing, Science, Mathematics, History and Geography. As an example we can gather data collected about earthquakes from the USGS or BGS. We can use this data to simulate an earthquake and allow the young people to make decisions based on the data that they have, this will involve Science, Technology, Engineering and Mathematics (STEM). Once the young people have made decisions based on their interrogation of the data they can put together a presentation for an assembly to the rest of the school. This would allow writing and presentation skills to be worked on and celebrated.Image result for data visualisation
The presentation could involve the use of data visualisations which allow information to be shared in an image format aiding understanding.
A person in a local authority responsible for highways needs to have information about weather conditions and traffic data both in real time and historically so that they can plan for adverse weather conditions. Having the ability to interrogate data in a variety of locations and bring it together for a particular purpose is a skill we need to ensure our young people acquire. Analysing Big Data has its own problems. The very fact that there is more data to analyse means that there will be a bigger error rate and it is really important that we have people who are able to decipher the information and record accurately what is happening.In our example regarding the local authority highways person if the data is analysed incorrectly it may result in too much salt being purchased or too many wagons being deployed on the roads when there is no real weather threat.It is worthwhile looking at the data provided by Traffic England as this site provides real time updates of traffic around the UK and is an excellent resource for interrogation.
As we are all governed by data collected by us or on our behalf. Recent revelations around data collection of personal data by social media companies has come as real surprise to many people and we should be teaching our young people about the way personal data is used and how we can protect them in a digital world. I think it is only right to make sure that our young people are able to make sense of the data around them and interrogate it confidently and make the correct value judgements.

Computer Science Education Week

Using the BuildIT Kit to make a lighthouse

The BuildIT Kit can be used for a lot of creative ideas. We began by thinking about the sea and this led to the idea of a Lighthouse. Here is what we used to create the lighthouse.


We connected the BuildIT Kit and then cut some wire to length so that the Crisp tin could stand up. We connected the wires and then put a hole in the bottom of the tin and threaded the LED and the wires through. We then cut a hole in the crisp tin  cap and placed the wash softener cap through it.




Once this was done we fixed the LED in place with sellotape.



We then placed a sheet of A4 paper around the tin and trimmed it to fit.








lighthouse2 Next we quickly drew on windows and a door. I am sure you can do a better job. Tip: mark where the windows and door will go then draw them on while the paper is flat then stick the paper around the tin.

We then programmed the computer to turn on the LED for 1 second and then turn off for 2 seconds.






Finally we took the image and placed it into a landscape picture.








This activity can be extended to cover many other subjects.


Writing about the life of a lighthouse keeper


Finding out the different heights ans circumferences of lighthouses.

Knowing the height work out how many stairs would get you to the top.

D&T :

Design and create your own lighthouse using spare components.


Write a program to make the light flash.


There is a book called the “Light keepers Lunch” which could be used as a starting point and there are many curriculum ideas to be found here

Share  your work with us as you make and program a lighthouse and show what you have written and found out.

This could be a project for the the Hour of Code and Computer Science week, enjoy.

Security Problems of an eleven year old

This video is a great example of what some of our young people are able to do and also able to analyse. Jake Seth Reiner seems at home presenting to an audience of computer programmers. His command of the complex vocabulary surrounding programming is evident.

Watch the video and be amazed at his computational thinking around the problems he has to solve.

International Journal Of Computer Science Education In Schools

The International Journal of Computer Science Education in Schools (IJCSES) is committed to increase the understanding of computer science education in schools by publishing theoretical manuscripts, empirical studies and literature reviews. The journal focuses on exploring computer science education in schools through pedagogical, cognitive and psychological perspectives.

Teachers and those working in education are able to publish and gain a wider audience for their own research.

For more information and to register please Click Here

Will automation destroy jobs?

Carl Benedikt Frey, co-director of the Oxford Martin Programme
on Technology and Employment, gives his expert view on the effects of automation on jobs – and the news isn’t all bad.

Carl Benedikt Frey of the Oxford Martin School at the University of Oxford has become (with colleague Michael Osborne) the leading authority on the automation of jobs. Their methodology focuses on how reliant tasks are on human aptitudes such as social perceptiveness, persuasion, originality and manual dexterity. We asked him about the impact automation will have in the future.


Adoption – the technology needed to automate 47% of jobs is already there. The pace of adoption depends on the relative cost of technology and labour. In China, for example, we’re seeing rising wages, which means the relative cost of technology is becoming cheaper – so the pace may become even faster.

Regulation is another determinant – no matter how good the Google Car is, unless insurance frameworks are adopted to allow for driverless cars, the pace of adoption will be slow.

I think it unlikely that robots will enter the domain of complex social interactions or jobs that require creativity or perception, and manipulation of irregular objects.


The UK has a strong base in financial services which are very automatable, so in terms of remaining competitive, the adoption of technology in UK financial services will be essential to driving productivity. However, some countries are being particularly pro-active. China’s new five-year plan explicitly embraces automation as a strategy for remaining competitive in manufacturing.


It seems from our research that digital companies such as Facebook and Google do not create as many jobs as the technology companies of the past – the GMs, Fords and Dells. But the fact that there are not as many people working directly in technology does not necessarily mean we will see a decline in the general number of jobs.

Our research suggests that once a technology job is created, it leads to the creation of five new jobs in the local economy. And in some new research that we hope to publish soon, we’ve seen that in developing economies, the multiplier effect from new technologies is even higher.


The Rise and Rise of the Robot

How the rise of the robots will affect your job

We’re heading for the fourth industrial revolution where more and more jobs will be automated – from care assistants to check-in staff. So how can we manage the march of the machines?

The residents of the Colony Club, an assisted-living home near Fort Lauderdale in Florida, are fond of Zora, the little redhead who helps them with their daily exercises, tells them a story or two, takes them on a walk, reads them the weather forecast and will even dance them the Macarena if they ask.

And she works for virtually nothing, after an initial payment of around £12,000. For Zora (pictured above) is a 57cm-high Belgian-made robot, one of 200 ‘Zoras’ now working either as care home assistants or hotel receptionists, worldwide from Florida to Perth in Australia.

Robots like Zora have already entered occupations, such as social care, nursing and medicine, that until recently were considered the preserve of humans. And they not only offer an insight into the next 50 years, as big data, technology and artificial intelligence fully converge on the workplace, but also pose questions about the jobs and tasks that will be left – or created – for us humans in the future.

A much-cited study, The Future Of Employment, by the University of Oxford’s Carl Benedikt Frey and Michael Osborne, is the basis for predictions that 35% of jobs in the UK and 47% in the US could be susceptible to computerisation or automation in the next two decades. And a study by the McKinsey Global Institute on disruptive technologies predicts that in the next 10 years, robots could jeopardise between 40 million and 75 million jobs worldwide.


To place that in some kind of context, analysts from Bank of America Merrill Lynch are calling it the fourth industrial revolution (after steam, mass production and electronics).

Science fiction? It’s happening already. We think nothing of paying for groceries at a scanner or doing our banking via an ATM. We’ve grown accustomed to the idea of smartphones that can talk to us, and of self-driving cars. In a recent Ovum survey of 4,500 people in 20 countries, almost half of people with smartwatches say they use them for work.

In 2004, MIT futurist Thomas Malone forecast in The Future of Work, the coming era of heightened and yet decentralised human collaboration. A dozen years on, we’ve become used to Wikipedia and Google Translate as examples of this technology-enabled collective intelligence.

Unmanned drones still need to be programmed by humans. Credit: Shutterstock

The rise of uncrewed vehicles and drones is creating a new workforce of pilots, drivers and ship captains who do their jobs not from the sky or sea, but from an office chair in a remote location.

But with a few exceptions (Wikipedia’s suggest bots, for instance), it has been the humans bringing most of the intelligence to this new relationship with machines.

Increasingly, however, we will see the machines playing more intelligent roles – with what Malone now calls ‘cyber-human intelligence’ – eating up the feast of data served to them by smart devices and other low-cost sensors in the ‘internet of things’. Artificial intelligence (AI) already facilitates the capture, structuring and analysis of big data in many areas, most prominently in stock trading, using textual analysis to predict the development of stocks.

AI analysis of stock trading is already at our fingertips. Credit: Shutterstock

But it is also moving into medical diagnosis, education, such as the one-to-one teaching of maths, and computer games – McDonald’s uses games to teach UK employees how to use its point-of-sale system. London law firm Berwin Leighton Paisner automates the analysis of Land Registry documents, rather than sweating interns and paralegals to do the tedious chore. Not even the fourth estate is safe from AI – Quill, developed by Chicago company Narrative Science, crunches data and generates reports in a journalistic style.

There can be little doubt that robots and chatbots – intelligent virtual assistants which can converse in complex and unstructured formats, then take action – will turn the customer service industry upside down, cutting the cost of managed services by 60% in the next two years, predicts tech research company Gartner. Unilever and BMW are using simple Q&A bots able to answer the most common customer questions. The Henn-na hotel in Nagasaki, Japan, which opened last summer, is fully staffed by robots – from check-in staff, to porters and the concierge.

Replicating the dexterity and flexibility of the human hand is one of the great challenges, but a robotic hand developed by London’s Shadow Robot Company is good enough to have been used as a chef in a prototype robotic kitchen.

Of course, the robots, intelligent machines and software platforms completing these tasks do not understand what it is that they are doing, but whether the machine can ‘think’ matters little to a manufacturer or service provider seeking ways to get a job done as well or better than a human.

The Shadow Dexterous Robot Hand can even hold a lightbulb. Credit: Richard Greenhill and Hugo Elias of the Shadow Robot Company

History indicates that in the long run, more jobs have been created by automation and technology than destroyed. There is no convincing argument against that happening again in this fourth industrial revolution – perhaps we just cannot yet imagine the new jobs that will be created.

But neither is there evidence yet that the introduction of these latest technologies is creating an equal number of well-paying jobs to compensate for those lost. Osborne and Frey’s Technology at Work shows that in 2010, only 0.5% of the US labour force was employed in industries that did not exist in 2000 – though they argue that the digital industries create wider economic benefits.

Many jobs will be stripped of routine, complex technical tasks, allowing for greater focus on interpersonal skills in occupations that were once largely technical. Daniel Susskind, economist and lecturer at Balliol College, Oxford, predicts that the organisations that will succeed in this AI-driven future will be those willing to change the nature of jobs as more areas became automated. They will focus their enterprises on the aptitudes that machines have yet to master: interpersonal communication, empathy and problem-solving.

The challenge for leaders? It won’t be predicting which jobs should be replaced by intelligent machines, but how best to harness the march of the robots, imagine the opportunities that they bring and make them work for, rather than against, the organisation’s oh-so-old-fashioned human resources.

Management Today