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During the last week of July Microsoft employees around the world participated in our //oneweek Hackathon, where teams create projects with technology to solve small and big problems. Some of the ideas are just fun things that go nowhere, and others end up being built into products that you then end up using. It’s volunteering at its best because people get to forget their day job for a week, and do something they are truly passionate about. And many of the teams go all out - working for weeks in advance of the Hackathon, and then virtually living with their Hackathon team for the week whilst they code, test, sleep and eat pizza. Some teams, like the OneNote for Learning team, actually got started weeks before the Hackathon, but worked in different countries. For the //OneWeek Hackathon, the OneNote for Learning team all then came together in Seattle.
From 3,300 projects, built by 13,000 hackers, one team gets crowned champions of Microsoft Hackathon 2015.
This year’s winners were a project team that created OneNote for Learning, an extension to OneNote to help students succeed in reading and writing, and to support every student, including those with learning disabilities like dyslexia, or language barriers. What they produced - with the help of coders, education researchers and designers - will very quickly be turned into a complete product and be rolled out to pilot schools this year.
You can read the story about OneNote for Learning here - and if you want to keep up to date with their progress, and how you can get your hands on it (or lobby to pilot it too!) then maybe connect with Mike Tholfsen on Twitter - he’s the guy in the purple OneNote t-shirt in the middle of the photo.
Read more about the Microsoft Hackathon winner - OneNote for Learning
We have just announced dates and venues for our 2015 Education Partner Summits in September, in Brisbane, Sydney, Melbourne, Adelaide and Perth. As usual, the invitations are open for Microsoft Education Authorised Resellers and our other partners who deal with education customers.
This year’s education ICT buying season is almost underway, and we have lots of new product and service announcements - including specific versions of Windows 10 and Office 365 for education - that are key for our partners and education customers. There are also significant changes in the market, including a shift to cloud services, Bring Your Own Device, a growing move away from institutional purchases towards students buying devices from retailers, and the devolution of the decision making process from central bodies to schools and individual teachers.
With traditional revenue streams being disrupted by these elements, we are running a national series of Education Partner Summits in September which are an opportunity to gain deep insights into the changing dynamics of the schools, TAFE and universities sectors from the Microsoft Education team. The agenda is specifically focused on meeting the needs of those who want to develop the most effective sales messages and strategies to win and grow in a transformed marketplace by providing practical sales resources. You will also leave the event with an understanding of how you can create new opportunities by leveraging this year’s launch of Windows 10 and getting the most out of Office 365 in Education and Azure cloud services. It will also be an opportunity to develop your relationship with our Education sales team.
The seminar will benefit sales and marketing personnel in Microsoft Authorised Education Resellers dealing with the education sector and provide valuable insight to product marketing and development teams who are looking to identify new profitable product and service opportunities within the sector.
The aim is to ensure that our partners can compete effectively, and tell a differentiated story that appeals across the different levels of decision makers within educational institutions.
We’ll be hosting the events in our offices in each of the key capital cities, and each briefing will be a full day from 8:45AM until 5PM
In addition to some of the national education team from Microsoft (George Stavrakakis, Joseph Alvarez, Jason Trump, Dan Bowen and me), you will also get the chance to meet with our local team in each state - helping you get a solid connection to the national and local team!
Make a date: Find out more, and register
I read in today’s Sydney Morning Herald the continuing story of universities in Australia fighting a constant battle with cheats in exams and assessments. Today’s story reveals that there’s not just a problem with plagiarism in essays, but also students paying impersonators to sit their exams for them:
University students are increasingly paying impersonators to sit their exams or smuggling in technology to help them cheat, while other students cannot be trusted to sit in sloping auditoriums because of their willingness to copy answers in multiple choice tests, a new report reveals.
The story focuses on one investigation report from an Australian university, but the problem is likely to be happening across a broad range of universities, in Australia and internationally.
And I realised that two weeks ago I wrote about a way to tackle this, in a way that’s cost effective, quick to implement and simple to do. The answer lives inside my story about “Making machine learning in education easier for every day users” - and something I’d been talking about with customers recently…
The simple summary of “Making machine learning in education easier for every day users” is that we’ve developed a series of recipes to help build intelligent services, called Project Oxford, and one of the recipes is to do face recognition - and you can quickly build it into your own app, website or software. The services take the complexity of machine learning tasks, hide all the detail, and let you just perform a simple task - in this case “Are these two pictures of the same person?”. And it is very simple for a developer to use it, because it’s based on our Microsoft Azure Machine Learning service.
Mat Velloso, one of our developers, built it into a website called TwinsOrNot.net, which lets anybody do the comparison by uploading two photos of your own, or finding two photos with Bing Image Search.
What is amazing is that Mat built this sitting in a hotel room in the Czech Republic, in one evening, thousands of miles from home, in just four hours. You can read his story of how he created twinsornot.net here, and how it went from a geeky evening-to-kill hotel-room project to a massive viral success (it went from zero users to 75,000 within 7 hours of being demonstrated at a local conference, and a million hits within days).
The user experience is really simple - you pick your two photographs, and it gives you a percentage probability that the two are the same person.
The image below is as close as I could get within our own local Education team - apparently there’s a 66% resemblance between Keith and Jason (which really isn’t that close).
So although it would probably take a human a bit longer to do the checking, the software can instantly tell us that we need to check out Jason if he turns up in the exam hall pretending to be Keith!
The system also makes allowance for every day differences - different lighting conditions, different styles of photo - even different facial hair. So the two photographs of me below were taken 2 years apart, one with full beard (yeah, I know, I never did that again!) and one without. And yet it knew that both photographs were of me.
Although TwinsOrNot.net was built as a fun website, exactly the same services could be used to build an app that runs on an exam moderator’s phone, or on a laptop at the entrance to the exam hall, that compares a student’s ID card photo to the person entering the exam, and in real time reports to the proctor whether they are the same person, or there needs to be more checking done.
If Matt could build this in an evening, then could the same be possible for a university? Well, they already have the components - almost all use the Microsoft Azure cloud services already; they’ve got laptops with webcams and they have got student ID photos. So all it needs is for a developer to spend a few hours building a prototype, and then they could try it in an exam hall by the end of the week. And, just as importantly, they could be ahead of the newspaper headlines within hours…
This isn't a perfect solution that could completely solve the problem, but (a) this could be done quickly at low cost and take a step forward against cheating and (b) doing it will improve the detection of cheating without adding a huge workload for staff. It’s not designed to give 100% assurance, but out of 100 students it would provide a way to highlight the 5 people that need a bit more checking by a moderator.
I think that the battle to combat exam cheats is similar to the battle against computer viruses - it’s a game of cat and mouse, and it’s a constant game of improvement iteration at high speed, and this suggestion is another step forward in the game…
1) Well, the website domain is available, because I only just thought of the name…
2) Listen to Matt Velloso on the MS Dev Show sharing his experiences
3) Read Mat’s blog, where shares the links he used for building TwinsOrNot.net
4) Mat's even shared his source code to get you started!
Once you’ve built a prototype, let me know how it goes!
Yesterday I wrote about the way to make Single Sign On easier for staff and students by using their Office 365 Education login on third-party websites. This week one of the most popular student learning websites in Australia (and elsewhere) has been added to the list, as your students and staff can now sign into Mathletics with their Office 365 Education identity.
Here’s the news straight from the Mathletics team:
Mathletics has evolved… to integrate with Office365! The multi award-winning e-learning platform now has integration with Office365 Active Directory, so you can sign into Mathletics using your Office365 account!
Mathletics is the world’s leading educational resource for mathematics, created by the team behind the World Education Games. Over 4 million students in schools across the world are a part of our global learning community.
You need never remember your password again…
Passwords are annoying, we get it. That’s why we are teaming up with some big names to ensure you have one less to remember. All students and teachers can now link their Mathletics and Office365 accounts to create a single point of access.
Linking a Mathletics account to an Office365 account is simple and takes just a few moments. Once linked, students and teachers can access Mathletics directly from their Office365 dashboard without needing to log in.
Once you’ve added it, users can seamlessly move between Office 365 and Mathletics, without having to login again (and the same applies to the other 70+ education services that have also enabled single sign on with Office 365)
Full details on how to set up Office 365 login for Mathletics are on the 3P Learning website here
Or, if you’re logged into Office 365 Education right now, you can hop straight over to the Office Store to add Mathletics into your Office 365 Education service.
Over the last year, we have been working with software and website developers to make it easier for students and staff to login to their services by allowing them to login with their Office 365 username. This means that students don’t need to remember yet another login identity and password, but simply use the username and password that you’ve already given them. And, in many cases, they are automatically logged in without having to re-enter their details. It also means that your users stay under your control - for example, if you suspend a user account, you’re also suspending it on all of the third-party websites too!
It’s the simplicity of Single Sign On, but without all of the previous hassle and custom technical work that both sides (developers and end user organisations) previously had when linking their systems together.
Apps and services like Teacher Dashboard, Literatu, nearpod, GeoGebra, LMS365, Brightspace, Moodle, RedCritter and ParentPaperwork give your users the option to sign in with their Office 365 identity when they go to login (this is the Sign in page for ParentPaperwork)
You can see a long list of some of the Office 365 education apps and services here.
And all of the services that connect to Office 365 can now be found in the Office Store’s Education category, and you can quickly add them into your Office 365 service.
What is great for users is that they can then see the apps that they are connected to, through their App portal (at https://portal.office.com/myapps), where they can see all of their Office 365 apps - the ones that we provide, like Word, PowerPoint, OneDrive and mail, as well as the third-party apps (as you can see below, I’ve got quite a few on my account ):
And anywhere the user is within Office 365, they can get to the apps really easily from the app launcher that sits at the top of their screen
This means that you’ve got a ready-made portal for users - they don’t need to bookmark all of these services on their different devices - they can just use the app launcher. And when they move between all of the different sites, they easily login with one click - they don’t have to keep signing in again and again each time they go to a different site.
And the IT team at school/university also get tons of useful data on who’s using what applications, how frequently etc, that is available through their Azure Active Directory service, which is linked to Office 365. They also have the ability to enable and disable apps, or even assign licences for specific apps to specific users or groups.
Find out more about developing Office 365/Azure Active Directory Single Sign On
Find out more about how IT can manage the Single Sign On services
Last year, I recorded an example of using the Power BI in education, and specifically the Q&A service, to turn data into information on Australian universities (you can see it here on YouTube). Recently, I’ve been creating an example with school data, to show another way of using Power BI in education. This latest example is a walk-through of the Q&A side of Power BI, which provides the ability for users to ask questions about data using a simple search box. The data that is used in this example is from the Queensland government's Open Data sites as well as the Australia Bureau of Statistics Census 2011 summaries, and they are linked together to allow you to ask questions in plain language. They were originally published in lots of different formats - spreadsheets, CSV files, zip files - so one of the jobs to do was to use the Power BI Desktop app to bring them together.
Watch the video for an introduction of what is possible
The reason for sharing this isn't to look at the data specifically, but to share with you how Q&A works for a typical user, and the kind of ways that you can ask questions and gain insight into your information. This example uses a wide set of data published in Queensland, but hopefully you will get an idea of the way that it could work with your own internal data. The video is 15 minutes long, so you’ll only get a brief insight into the kind of questions that could be asked about this data!
The Power BI team talk about a three step process for using data:
The video only shows the second step - how you can use Q&A to craft a data story - but in total all three stages took about 12 hours to build:
You can register for Power BI and download the apps, including the desktop app (to create data sets) and the Power BI app for Windows, iOS and Android - which allows your users to access your data when and where they want, on their own devices - directly from powerbi.microsoft.com.
For the majority of users, Power BI is a free service, and for power users who need Power BI Pro, there’s a 60-day trial available. My view is that a school might need one or two Pro users, and the majority of users will be able to use the free service. I used the free service to create the demo you’ve just seen! The Power BI pricing information here is full commercial pricing - you’ll need to talk to your usual Microsoft partner for education pricing.
My best recommendation for Power BI training is to use Jen Underwood’s site (http://www.jenunderwood.com/training/) which has tonnes of useful training in all aspects of Power BI.
Thursday’s competition for Windows 10 rock was won by Robert Matthews (@AskMrM on Twitter) from Wyong in New South Wales. So he’s now got a stack of sweets and a Targus laptop bag on the way:
What’s really interesting to me, is that The Wisdom of Crowds - which in simple terms says that if you ask a crowd to estimate a quantity, the group’s aggregated answer will often be as good, or better than, the answer given by any of the individuals within the group - applies here, even though there were less than a dozen answers.
Robert won, with the nearest guess of 420
The lowest guess was 175, and the highest guess was 1,010.
But the average of all the guesses was 439. The actual answer was 450. So although Robert was 7% out, the Crowd was only 2.5% out!
Which means that in reality, everyone’s a winner! (A line I’ve wanted to use for years…)
Yesterday our office celebrated the arrival of Windows 10 with jars of Windows 10 sugary confections. My colleagues here in Australia call it a lolly jar, and I’d call it seaside rock - it’s the kind of sweet that’s made with huge volumes of sugar, and then coloured and rolled, ending up with the words “I Windows 10” running through every sweet (and now you know ‘How to make Windows 10 rock’ )
In the past, when we’ve launched new products I’ve often tried to get my hands on early copies and given them away in silly competitions on my blog or Twitter. But this time almost everybody is going to get a free Windows 10 upgrade anyway, so instead I collected 10 jars of sweets, and threw in my brand new Targus Bex laptop sleeve, and so we can still have a silly competition!
I’ll give the prize for the closest guess for how many individual sweets there are in 10 jars of Windows 10 sweets by the 4PM Friday in Sydney.
To enter, just tweet me with your guess - I’m @rayfleming on Twitter
I’ll post them out to a winner in Australia first thing Monday (sorry folks, but I can’t post sweets abroad )
Having recently written two articles about the theory of applying Machine Learning in Education - “Two ways to use Azure Machine Learning in education” and “Making machine learning in education easier for every day users” - I think it’s time to dive into a specific example of machine learning in education where it is being used to support education outcomes in schools. The story comes from my colleagues on the Machine Learning blog.
The example is from Washington State, in the US, where Tacoma Public Schools has been using it as part of their ongoing initiative to prevent student dropout for school students. The district has delivered a dramatic turnaround - eight years ago five of the high schools were described as “dropout factories”, and five years ago just 55% of students graduated on time, compared to 81% nationally. But last year that had been boosted to 78%, ensuring that the district is recognised nationally for its educational achievements. The district is now developing the next level of data-driven improvement with the help of Machine Learning.
The long journey started several years ago when new leaders joined the school district’s board. The new leaders expressed a desire to be more transparent with data and to use the data to address any shortcomings. They resoundingly embraced the value of data-driven analytics for the benefit of the district and its students.
The board also asked themselves a radical question: What if they could process all their data to predict whether or not a student was likely to disengage and ultimately drop out? This was in the days before Machine Learning in education, and so the project team worked with Microsoft to create a data warehouse with student grades, attendance, health records and other data. And teachers and administrators were given access to data through their tools, like SharePoint and Excel. As the board President, Scott Heinz, described it:
It is only recently that the board have been able to apply Azure Machine Learning to predict future dropout risks - turning historical data into an engine for predicting future success. As Shaun Taylor, the district’s CIO said:
By using predictive analytics, we thought we would be able to intervene earlier and work closely with those at-risk students. Then we would be able to reach our ultimate goal: getting that graduation number close to 100 percent.
When we saw Azure Machine Learning, we started to see how it could be possible for us to realize our vision
The Microsoft team worked with the district to create a proof of concept, using Azure Machine Learning to create a model using five years of demographic, academic and student performance information to predict whether there was a risk of a student dropping out in the next semester. Using the Azure data services in the cloud, and going through a number of iterations of creating a predictive model (what’s key to this is understanding what factors might influence student dropout, and making that historical data available for the analysis) they were able to give a dashboard to board members to see the details of students at-risk of dropping out. Christopher Baidoo-Essien, at the school district summarised their journey:
As well as working on developing more real-time, or near-time, data sources for the analysis (using data that’s a month old risks missing key signals) and providing more regular analysis and reports, there is a focus on changing traditional, but incorrect, perceptions about the reasons for students’ struggles. As Christopher says:
There’s plenty of work still to be done, but the journey so far has proven that there is significant value in both the data dashboards, as well as the predictive analytics.
You can read the full case study on the Azure Machine Learning blog
We will soon start to see examples within Australia of using Azure Machine Learning in education, as similar work is starting here. One of the data science teams behind this work in the US is working with S1 Consulting in Australia to fine tune a model for student dropout from universities, using the Azure Machine Learning service, and there’s another team at Literatu working on predicting opportunities for support and intervention for high school students, based on their performance in school assessments, as well as external assessments, such as NAPLAN and PAT assessments.
Last week I wrote “Two ways to use Azure Machine Learning in education”, which started exploring the use of algorithms, alongside cloud-based machine learning in education to solve some of the key challenges facing education institutions. The problem is that it all sounds so very geeky. Hey, I just wrote “algorithms” and “machine learning” in the first sentence, which kind of proves the geekiness. Although this kind of technology is making huge differences to our online lives (like protecting us from spam email and giving us just the 3 out of 100 emails that aren't spam) it’s also something that has been the domain of technical wizards. To make a difference, machine learning in education has to be simpler.
But we’re moving into a world where we’re going to be able to use this technology to solve real-world problems that don’t involve huge numbers of data scientists, and where the real knowledge sits inside the heads of business users in our organisations. Not the IT department and the data analysts.
So how do we make it easier for every day users to be able to apply their expertise to analyse their own data?
Missed Part One: Building and sharing algorithms? Here it is.
Missed Part One: Building and sharing algorithms? Here it is.
If we’re recognising that there’s just a bit too much rocket surgery involved in today’s work with data, how do we make it easier to work with, for mere mortals like you and I? Well, there’s some smart teams working on that across Microsoft.
Patrice Simard, a Microsoft Distinguished Engineer, is leading a new machine teaching research project at Microsoft Research, which plans to focus on how to make the tools and UI possible for non-experts to create helpful and valuable machine learning capable systems - rather than just focusing on how to make machine learning algorithms more accurate - through a project call ‘machine teaching’. Before you react with shock, this isn’t about machines teaching, but about users teaching machines!
As Patrice says “No one has really built a machine learning tool for the layman” - and as more uses are found for machine learning, there’s a growing deficit between demand and the availability of data scientists with the right skills. There just aren’t enough people with machine learning expertise to do all the projects businesses and organizations want.
You can read more about this work on the next evolution of machine learning: Machine teaching here
But there are already some practical examples that you can look at to see what the future of Machine Learning could resemble for every day users, in Project Oxford, revealed earlier this year. Project Oxford allows developers to create smarter apps, which can do things like recognise faces and interpret natural language even if the app developers are not experts in those fields.
Project Oxford currently includes four main components:
If you have basic development skills, or you can team with somebody who has, then the Project Oxford website is the place to start.
So far, so good. But what about real uses of this technology? And what about the simplification angle?
A couple of months ago something called the #HowOldRobot went viral globally. It was the work of 3 Microsoft engineers who were applying machine learning systems to the challenge of working out how old somebody looks. And they made it very simple. You go to http://how-old.net and either upload your own photo, or find one on the internet, and it will estimate how old everybody in the photo looks.
Of course, it’s not 100% accurate, but it’s a powerful demonstration of simplifying the use of machine learning - for a start, it’s trying to guess how old you look, not how old you are!
Users are simply posing a problem, and letting the technology start solving it.
I found it disturbingly accurate. For example, a month before my 50th birthday, it tagged me as 50, and then got me as 48 for a photo taken when I was 48.
But, then again, when I tried it with a photograph of me in my 30’s, it completely messed up, and pronounced me as 15 years old (better than prematurely ageing me)
You can read a lot more about the #HowOldRobot, and the technology behind it, here, and there is also an excellent behind the scenes look at the viral growth of the #HowOldRobot here (imagine building something you thought would be used by 50 users, and getting 35,000+ people using it within three hours).
Inspired by this project, another Microsoft engineer Mat Velloso built a service in just a few hours to compare two photos of people and rate their similarity, with a ‘twin rating’. With TwinsOrNot.net, it’s the same simple user interface, and process of hiding the complexity of machine learning - with just a few hours coding. Again it uses the Project Oxford work.
You should try it for yourself, but here’s the result for the two most twin-like members of our Australian education team.
If we can use machine learning algorithms for (arguably) trivial things, and make it very simple to use, where can it be applied in education?
Carnegie Mellon University are already using it work out how to cut campus energy usage by 20%.
One of the examples that is easy to see (and currently very difficult to solve) is the problem of students dropping out of universities. In Australia, one in five students drops out of their course in the first year, with the majority dropping out of the university altogether. In some universities, this is as high as one in three students.
And yet, there is a strong bank of research from different universities which identifies the key factors that are associated with students dropping out (across six different studies, there are four factors which feature in the top five of over half the studies). Some projects have identified over 30 factors to monitor and analyse. It is the perfect scenario to use machine learning, because instead of spending a year or two analysing the factors, you can analyse the data every night for every student, and help identify the students at risk of dropping out. And plan your proactive intervention and support in response to what you can predict will happen, rather than reacting once you’ve discovered something has happened.
The beauty of using machine learning to do this is that the system can manage the model itself - it learns as it goes along, rather than you having to keep using an out-dated idea of what the causes of drop-out are. That’s just one of a few key reasons why you find telco’s using it to forecast customer churn, and online retailers using it to suggest additional products to buy.
If you’ve made it this far, hopefully you can see that there’s some value in keeping an eye on machine learning. So what can you do next? Here’s three resources and ideas for next steps: