AI Archives - Coorpacademy

Tell us what courses you play and we’ll tell you who you are

During the course of a day, our attention is constantly stimulated by various information. We only need to spend 30 minutes on our favourite social network, or turn on our television, to realise the constant hubbub around us. Paradoxically, we have also become more attentive to the type of information we are willing to receive. But the point is that this flood of information is one of the reasons why we want to create the most relevant content possible. But how can we deliver on this promise? We’ll explain it to you in a few lines, so you don’t lose your attention.

A finely tuned catalogue

If you have read our article on the recipe of the Coorpacademy catalogue courses, you will know that we take care of both the presentation and what is on the plate. To engage our learners and stimulate them during their learning, it is important to offer them premium content, designed by educational engineers or in co-publication with exclusive partners such as Forbes, IBM or Cegos. To build a relevant training catalogue adapted to each learner, it is crucial to offer tailor-made content, so that it fits them perfectly. Thus, our content catalogue includes courses concocted by us and also by the business experts of each organisation we work with, to promote the development of each individual’s skills.

Content tailored to the changing world

Learning means progressing, doing better, evolving. This implies not only change, but also temporality. We start from a point A, at a certain point in time, and end up at point B, in some time. Therefore, in a rapidly changing world, learning is essential. In preparing our courses, we think about the world of tomorrow, to better prepare you for it. Thus, the more than 1700 exclusive modules on soft skills that make up our training catalogue are designed to guide you through the 5 crucial transformations for the future of organisations. But fighting for tomorrow’s world means that it still exists. That’s why we offer Coorpecology, the first training platform dedicated to the ecological transition, and why we are proud to collaborate with the Collège des Directeurs du Développement Durable (C3D) to design courses that develop sustainable thinking.

Support that is as personal as your experience on our platforms

To get to know you, we have a major ally: data. If you’ve played the All About Data playlist, we’re not teaching you anything, data is essential to designing a learning experience that reflects you. Indeed, by playing courses on our platforms, we are able to refine what we offer. So, training is really just a click away. But if our courses adapt to our learners, our platform also adapts to the needs of our clients, integrating directly into their training ecosystem. When we say that we know you well, it’s also because our team of Customer Success Managers supports you in your training projects, to achieve your objectives and those of your learners. We offer you concrete actions to engage your community of learners over time and reach new heights!

At the EPFL Innovation Park, the interview of Jean-Marc Tassetto, co-founder of Coorpacademy

Discover the video interview of Jean-Marc Tassetto, co-founder of Coorpacademy, on the advantages of being an EdTech startup at the EPFL (Swiss Federal Institute of Technology) Innovation Park in Lausanne, Switzerland.

Jean-Marc Tassetto, co-founder of Coorpacademy : “Coorpacademy is what we call an EdTech start-up company, which brings together Education and Technology. We have a platform dedicated to Corporate Digital Learning. Coorpacademy’s Unique Selling Proposition is to deliver highly individualized learning experiences online. You and I being very different in the way we learn, we will be delivering through the same platform very specific content and instructional design pending to our upskilling and reskilling needs.

Being located at the EPFL Innovation Park, for us, really made a difference. First of all, we’ve created Coorpacademy on the campus and decided to do so because we are close and connected to two laboratories led by Professor Pierre Dillenbourg, working on Learning as a Science. All this is related to artificial intelligence applied to education, deep learning and machine learning applied to education. So, for us, it is a key differentiator when it comes to delivering top-notch solutions to large multinational companies like we are doing; it is really great to be backed up by top-notch scientists.”

We are proud at Coorpacademy to be part of such a thriving environment. Switzerland is a great place for innovation, and the Swiss Federal Institute of Technology is one of Switzerland’s most prestigious schools, at the forefront of learning sciences and innovation applied to learning processes. This was, from the day Coorpacademy was created in 2013, the best possible place for us to thrive.

In 2019, figures show that Switzerland is still topping most global rankings on innovation. According to the World Economic Forum, Switzerland is the 3rd most innovative country in the world, only after Singapore (1st) and Luxembourg (2nd).

The article states: “The Center for Global Innovation Studies at Toyo University recently published a Global Innovation Index, ranking the innovation performance of each country. The index was created by selecting and integrating a total of 58 indexes for comparison from five main fields: international cooperation, market trends, technological innovation, resourcefulness and relevant policies.”

Switzerland is also the 1st country of world when it comes to government funding for university research as share of GDP, with 0,76% of total GDP being allocated to university research. It is quite impressive for the 5th most competitive economy in the world!

Coorpacademy has its roots at the heart of innovation and research in learning sciences, and we are proud to make the most of this thriving environment to deliver top individualized learning experiences to our customers.

Let’s start using a whole new class of meaningful HR KPIs – Jean-Marc Tassetto in HRReview

This article has been originally published in HRReview. It has been written by Jean-Marc Tassetto, co-founder of Coorpacademy. To read it in its original form, it’s here.

There’s plainly a crisis in how HR and L&D is working with training data. For example, according to the 2019 run of its annual Digital Learning Realities Research, HR analysts Fosway reported that only 14 per cent of respondents in the UK HR community think they are effectively measuring the impact of learning, while 53 per cent admit they’re probably doing it ‘ineffectively’ and 33 per cent are not even trying.

Discover some extracts of the article:

“However, help may finally be at hand in the form of the Learning Experience Platform (LXP), originally defined by workplace learning expert Josh Bersin and recently formalised as a new market category by Gartner.”

[…]

“Why we need to move beyond the LMS

That’s because LXPs track any behaviour traces and use them to test what works and what doesn’t, based on a powerful new way of collecting such data, the ‘Experience API’ or xAPI standard. The Experience API is a technology designed to create a rich environment for online training and learning and is there to address the limitations found with the e-learning technologies currently used that are too focused on tracking the learner through a specific course, rather than through diverse learning experiences.

Why does this matter? Up until recently, elearning analytics only existed in a very limited form, as any learning data that was harvested was very partial. That was due to the fact that the technology L&D had to rely on for so long – the LMS, the Learning Management System – is primarily an admin and delivery system, designed for managing access to training and participation of learners.”

[…]

“The rise of new HR metrics

So how does this new API work? By working with activity streams. The best way to understand this is if you look at someone’s Facebook wall, what you are looking at is a series of activity stream statements, and the concept is gaining traction as a useful way to capture a person’s overall online activity, on social networks and in the enterprise. xAPIs capture learning experience data – and as we start to aggregate these streams across an enterprise, we can identify the training paths that lead to the most successful or problematic outcomes, and so what determines the effectiveness of the whole training programme. Doing that would in turn enable HR leadership to glean new insight not only on what a learner has successfully learnt, but how they gained this knowledge and which learning approach they chose to follow. This provides opportunities for strong diagnostic values and advance performance indicators, such as Curiosity, or Resilience, and other very promising new HR metrics.

For example, ‘Curiosity,’ is associated with advanced abilities including an aptitude for learning – and as Knowledge, in the Google age, is easily acquired, employees we know who have this capacity could be a real asset for the company.”

[…]

A deeper picture of workplace learning

By using these new behavioural indicators, data available for Human Resources and line of managers of the real capabilities of their teams becomes much richer and more complete. What’s more HR professionals can properly consider the full candidate potential of a person for a specific job not only in terms of their knowledge and skills, but also their character and behavioural qualities. Brands would have access to not only what a particular person has actually learned, but also how the learner landed there, what learning approach they have chosen, so we can come up with tailored recommendations that are close to their actual needs. Good news for the corporation and the benefit for the employee is to help her become the real owner of their employability. Finally, trainers and HR managers also benefit, because they can access all sorts of new types of insight – not only what someone successfully learnt, but also how the learner got there and which learning approach they chose.

So let’s seize the chance that the powerful combination of the LXP and the xAPI offers – and make workplace training and development the truly strategic business tool we all know it deserves to be.

You can read the article in its complete and original form here.

Discover other articles from Jean-Marc Tassetto, co-founder of Coorpacademy:

How to Stop Worrying About a Jobless Future? – Bdaily Business News

Let’s welcome a new dawn of behavioural learning analytics – TrainingZone

Why Training is an Under-Used Source of Employee Insight – Incentive & Motivation

How to Stop Worrying About a Jobless Future? An article from Jean-Marc Tassetto, co-founder of Coorpacademy

This article has been originally published in Bdaily Business News. It has been written by Jean-Marc Tassetto, co-founder of Coorpacademy. To read it in its original form, it’s here.

Digital business transformation and training expert Jean-Marc Tassetto, co-founder of Coorpacademy and former head of Google France, says new ways of helping employees to ’upskill’ are on their way.

Here are some extracts of the article:

“We all know that Artificial Intelligence and automation are coming at us at breakneck speed. So how will business cope? Will we all be unemployed soon?

According to The World Economic Forum, technologies like AI and Robotic Process Automation are indeed entering every profession, and at speed. But does that mean fewer jobs, as so many fear – or a completely new set of career opportunities?”

[…]

“That means we all need to change jobs and careers multiple times throughout our lives: an ability to adapt will be critical. Against this backdrop, the job of the responsible business owner is to create ways to help their employees access the kind of training that might help them adjust, as well as cope with any new advanced tech you introduce yourself.

This is being crystallised down as the need to create a ‘learning culture’ – encouraging workers to gain new skills that organisations require now or in the future and in attracting and retaining talent.

One problem: we’re not doing that yet. Training and HR teams are there to provide the resources, tools and time to support learning, scheduling the diaries and career plans of staff, booking the armies of trainers and projectors, and making hundreds of hours of relevant content available. But, traditional training culture seems to assume staff are passive objects that simply get shuffled in and out of all those training rooms!”

[…]

“To get workplace training back to where it should be, this needs to change. In particular, if we are serious about our commitment to re- and up-skill and prepare for that near future, we need a way to connect back with the employee and deliver what they want. We also need to rethink the way training has traditionally been delivered – and we have to ask ourselves if it is realistic to expect people who work remotely and anytime, to stop everything and sit in front of a trainer with a PPT and a laser pointer for eight solid hours.

What does that look like in practice? Actually, very similar to what you and I are already doing in our day-to-day lives, and especially the Millennials and digital natives on your team. We live on our phones and we all try and make dead time waiting for a train as useful as possible, looking for content. We refuse to be delayed by a knowledge gap, turning to the Internet to plug any lack of understanding – and we might play a mobile game for a minute or two during a lunch break.”

[…]

“The old method of scheduling fixed hours needs to be discarded in favour of a blended learner-chosen model, where classroom training could be supported by a virtual environment in which all lessons and material are digital and available, 24×7 and increasingly via mobile and in short bursts. In addition, incorporating gamification and collaboration features will increase staff engagement by activating the joy of competition, too.

Such learner-centric approaches really work – and can, our data shows, secure user engagement levels for digital training content of more than 80%.”

You can read the article in its complete and original form here!

Discover other articles from Jean-Marc Tassetto, co-founder of Coorpacademy:

Let’s welcome a new dawn of behavioural learning analytics – TrainingZone

Why Training is an Under-Used Source of Employee Insight – Incentive & Motivation

Jean-Marc Tassetto’s interview for French television (BFM Business).

Ever Heard of Machine Teaching?

This article is part of our new Learning research and innovation series, offered by Coorpacademy in association with the EPFL’s (Federal Institute of Technology of Lausanne, Switzerland) LEARN Center. The author is Prof. Pierre Dillenbourg, Professor at the EPFL, Head of the CHILI Lab (Computer-Human Interaction for Learning & Instruction) and Director of the Swiss EdTech Collider.

The terms Machine Learning, Deep Learning, and Artificial Intelligence are on everyone’s lips. But what if we extended this list to something we call ‘Machine Teaching’ – and then speculate on what it might mean for education?

Towards ‘Machine Teaching’

Let’s imagine an algorithm that needs to learn how to identify elephants in pictures. In supervised Machine Learning, it gets an example – e.g. picture-3465 – and a label, such as ‘elephant’ or ‘non-elephant’. Picture-3465 may just be the next in a set of thousands of labelled pictures. But if the 3,464 previous pictures were all of African elephants, the system would learn less from yet another African elephant picture, than if an Asian elephant picture was introduced for the first time.

Similarly, if all the previous pictures showed mostly mature elephants, it would be better for the algorithm’s training to select a younger one. Again, if most of them were side on pictures, a frontal view would improve the knowledge acquired by the algorithm.

In other words, if the examples were not fed to the learning algorithm randomly, but strategically selected, one could optimize the machine’s overall learning performance. In a classroom setting, selecting examples is the role of the teacher: she knows that if all examples of squares given to learners are in a horizontal position, learners will logically infer that a square with a 45 degree rotation is not a square.

Any algorithm that determines the optimal sequence of examples such that they are diverse and sufficiently dissimilar from what has been shown previously to a Machine Learning system can be called a Machine Teaching algorithm.

Why Should We Care about Machine Teaching?

If an algorithm receives random examples as inputs, with no strategic consideration of the type of example and what the algorithm will go on to learn from exposure to this example, then clearly problems will arise. First, we should not confuse the size of the sample data with its intrinsic usefulness: merely feeding big data to a Machine Learning algorithm is not enough to guarantee the AI has learnt well and will perform well in its tasks. Secondly, the algorithm could tend towards taking wrong or biased decisions. Let’s reuse the above example of the identification of elephants from pictures: if the only pictures labeled as “non-elephant” are pictures of white animals, the algorithm might infer that only white animals are to be categorised as non-elephants. Sounds silly, but this kind of biases creep in, and matter. Biased algorithms can reinforce gender stereotypes (as was the case in Google’s translation service), or might suggest wrong decisions about humans (as, for example, decision support systems for judges which over-estimated the probability of recidivism for African-American people).

How Does All This Apply to Education?

The impact of AI on education spreads over three layers: (1) Method: AI may enhance the effectiveness of learning technologies where it is expected to enable a fine adaptation of instruction to individual learner needs: over time, a system may learn which learning activity is optimal for a certain learner profile. (2) Content: AI is changing what students should learn or should not learn and is also accelerating the production of learning material, for instance generating questions from Wikipedia. (3) Management: AI and especially data sciences offer new ways to manage education systems (e.g. predicting students’ failure).

Machine Teaching turns out to be relevant in all of those applications. Personalised learning, based on recommender systems, can only be well adapted to the personal needs of a learner if the data set on which the recommendation is based on is large and equilibrated enough. That means we need non-random data selection in any machine learning, i.e. the algorithm needs to be fed with data on what is effective for all types of learners.

In terms of content, when learning about data science and machine learning, learners need to also learn how to design the optimal dataset that the algorithm will learn from. Engineers are becoming teachers of algorithms by default, because you cannot simply program a Machine Learning algorithm. We need to better facilitate the correct decision-making of the algorithm – the same way a good teacher helps her students to develop problem-solving and critical thinking skills.

Innovation in Learning Science and Educational Technologies are top of our agenda at Coorpacademy, as we see them as critical to our mission to continuously improve the learning experience on our platform, making it even more personalized, flexible and enjoyable for learners.

The author Pierre Dillenbourg

Skills development: it’s time to revamp learning culture

This piece by Jean-Marc Tassetto, co-founder of Coorpacademy and former Google France CEO, has been published in Personnel Today. If you want to read it in its original form, it’s here!

With PwC recently predicting that artificial intelligence will replace seven million jobs by 2037, employees need to learn new skills to reduce the risk of being displaced by new technology. But Jean-Marc Tassetto, co-founder of Coorpacademy and former Google France CEO, warns the UK’s current ways of developing employees’ skills are inadequate.

By now it should come as no surprise that employees in all sectors will soon need to work alongside technologies such as artificial intelligence, with many having to change jobs or reskill as technology develops.

But in order to equip employees with the skills needed to thrive, professionals in learning and development need to create a culture that delivers life-long learning at work. This is imperative for developing the skills organisations require now and in the future, and in attracting and retaining talent.

However, there is one problem – we’re not doing it.

Learning teams provide the resources, tools and time to support skills development – considering the career plans of staff, booking the armies of trainers and making hundreds of hours of relevant content available. But many are missing the needs of the recipient.

Traditional training culture seems to assume learners are passive objects that simply get shuffled in and out of training rooms. Yet for any training to succeed, it’s essential that employees buy into the concept and stop seeing training as something forced upon them.

Engagement is low

Corporate learning is currently in a state of crisis. According to research from Towards Maturity, 44% of L&D leaders report that staff are reluctant to engage with online learning. Engagement rates are perilously low – as little as 5-10% − and course completion rates can be as low as 2-3%, research by the University of Graz in Austria has found.

Translated into business reality, this means the small number of people who go on training courses or download company-mandated e-learning modules barely complete what HR and L&D teams think they do.

To stop corporate learning being a poor investment, this culture needs to change. In particular, if we are serious about our commitment to reskilling and upskilling workers to prepare them for the future, we need a way to connect with them as learners and find a better way to deliver what they want.

We also need to rethink the way content is delivered. We have to ask ourselves if it’s realistic to expect people to stop everything they’re doing and sit in front of a trainer with a PowerPoint presentation and a laser pointer for eight solid hours.

Plugging the gap between L&D and staff

But change is coming and a new generation of digital tools has emerged to plug the gap between L&D teams and the disengaged learner.

Global analyst Gartner found that “learning experience platforms”, which prioritise learners’ experiences and ease of use, will become invaluable as attitudes to learning change.

Training strategies should consider the reality of how people learn; content should always be available remotely – increasingly via mobile – and at the learner’s convenience in bite-sized chunks, making use of video, gamification and collaboration.

What does that look like in practice? Very much like what employees are already doing in their day-to-day lives. We live on our phones: making dead time waiting for a train or a phone call useful, turning to the internet to plug a lack of understanding, and playing a mobile game for a few minutes to let off a bit of steam.

“Training strategies should consider the reality of how people learn; content should always be available remotely”

Imagine if you delivered your training that way – mobile, always available, in short bursts, and, where appropriate, in a quiz format? Need to know about Blockchain? Employees could either be sent on a two-day residential course once a year, or offered a way to consume five to 10 minutes of useful, tailored content when they want or need it.

This is a new, powerful and flexible way for L&D teams to help learners to reach a certain level of knowledge day by day. These methods, alongside more traditional elements, can help develop a more user-centric learning culture.

Of course face-to-face training to hone certain practical skills is still part of that user-centric model. But a customised learning experience platform approach will mean employees are more likely to be thoroughly engaged in the training they need to keep pace with the changing world of work.

This piece by Jean-Marc Tassetto, co-founder of Coorpacademy and former Google France CEO, has been published in Personnel Today. If you want to read it in its original form, it’s here!

How Thinking Like A Computer Will Help Save Our Jobs

This piece has been written by Jean-Marc Tassetto, co-founder of Coorpacademy, and originally published on minutehack.com. To read it in its original form, it’s here!

Historically, IT training has focused on coding skills. Now we need to think more like machines as well.

According to Mary Meeker’s much anticipated, just published 2018 technology predictions, you can expect the pace of the disruption of technology on the way we work to just accelerate – not slow down.

But does that mean fewer jobs, as so many fear – or a completely new set of career opportunities?

The evidence of history points to the latter, as the famous Internet trend analyst herself says: ”New technologies have created and displaced jobs historically… Will technology impact jobs differently this time? Perhaps, but it would be inconsistent with history, as new jobs and services plus efficiencies, plus growth typically are created around new technologies.”

And it’s true technology is disrupting the job market. As the World Economic Forum’s 2016 Future of Jobs report and a recent OECD study also found AI (Artificial Intelligence) in particular looks set to take over more and more tasks.

Some authors claim that only as little as 35% of current skills will still be relevant in five years – others say less, and it’s white collar jobs facing automation upheaval this time round, not just blue.

Step forward Computational Thinking

It seems we are on the cusp of a new automation age for sure. And as the robots move into our workplaces, our job roles will adapt – and with it, the skill sets to remain relevant. Everybody will need to have abilities complementary with digital technology.

But not everybody will be in need of hard programming skills: the future will require more than just being to code in Python or deal with malware.

This could mean skills associated with the Cloud, analytics, mobility, security, IoT and blockchain certainly, but there is a growing consensus that, as a culture, we have to introduce a computational/programming-like approach into all of our approaches to work.

This is being formalised around the movement around Computational Thinking (CT), where the focus is not just on the machine but on the human, whose thinking and learning is enhanced by the machine as job roles involve more and more working with computers.

Computational Thinking is basically the approach we take when we consider how a computer can help us to solve complex problems – i.e. algorithms, the way a Machine Learning program can learn from the data it gets, the limits of computation and so on.

But it also shapes what the person involved in the business process does, like preparing a relevant data set for that task, dividing a problem in useful chunks resolvable for a computer, detecting configurations where automation and parallelisation can be introduced, designing digitally, and so on.

What does this look like in the real world? Say you’ve agreed to meet your friends somewhere you’ve never been before. You would probably plan your route before you step out of your house. You might consider the routes available and which route is ‘best’ – this might be the route that is the shortest, the quickest, or the one, which goes past your favourite shop on the way.

You’d then follow the step-by-step directions to get there. In this case, the planning part is like computational thinking, and following the directions is like programming.

With this definition, it’s immediately clear Computational Thinking is not just for computer scientists. Being able to think through a problem in a similar, logical manner and come up with a solution in the digital world is what matters, and what we may all need, and as our professional lives become increasingly automated, CT related skills will grow in importance.

Whether it’s computational contracts, education analytics, computational agriculture or marketing automation, success is going to rely on being able to work fluently with IT, but always to have your eyes on the bigger picture.

Some forward-thinking policymakers are beginning to try and put this digital extension to traditional education on the horizon.

The US, for instance, is among the early adopters of CT, with its National Research Council and US tech university Carnegie-Mellon has its Microsoft-sponsored Center for Computational Thinking that provides seminars, workshops, research activities on computational thinking in any domain of life.

Leading European Higher Education institutions are following suit, like the Federal Institute of Technology in Lausanne, Switzerland, which has been introducing dedicated CT lessons in all entry-level courses across all disciplines.

In the UK, the Open University is also running introductions to CT, while the National University of Singapore has made CT compulsory for higher education students, regardless of what course they are studying. Globally, Google is pushing hard for the democratisation of CT at early years to 12 education globally, providing a variety of teaching material to educators.

The call to action

But what should the world of business be doing about this huge momentous shift? How do firms incorporate CT approaches into their curricula to help their staff? What can we do to help employees successfully transition and acquire these new skills?

First, it’s absolutely key that you insist employees take time out for education and establish continuous learning programmes. To ensure success, you need to get away from the ‘top-down’ approach of old.

The old method of scheduling fixed hours for input needs to be discarded in favour of a learner-chosen model and a virtual learning environment in which all lessons and material are digital and available, 24×7 and increasingly via mobile and in short bursts.

In addition, incorporating gamification and collaboration features will increase employee engagement by activating the joy of competition and the desire for socialisation and exchange.

Employees are also time-poor and required to face rapid changes in their industries and jobs. What they learn must therefore meet their immediate needs and be adjustable to their level.

Asking them questions before any teaching takes place (the flipped pedagogy model) is a great way to pinpoint their level and means they’ll be offered the lessons they need. Finally, this is the foundation of a move towards adaptive learning, in which content and teaching frameworks are customised to the individual.

Such learner-centric approaches work, and can secure user engagement levels of more than 80%. One of our customers, Schneider Electric, places user centricity at the heart of its training efforts: “Individuals are able to self-pace their learning, and we are experimenting with mobile learning as the next frontier in this journey. Digital learning is now a way of life here.” None of this will succeed if employees don’t see the results for them.

According to a Gartner report published in May, “Place the learner’s experience and the solution’s usability at the top of the priority list for any new learning project.”

Training, be it CT-oriented or not, has to be about the learner experience, encouraging employees to develop all their skills to their full potential and to future-proof their careers – and employers need to offer skills like CT if they are to flourish, too.

Embracing a computational thinking mindset will prepare us to meet anything the digital world of the future can throw at us.

Jean-Marc Tassetto is the former CEO of Google France and co-founder of Coorpacademy, a growing force in the provision of user-centric corporate digital learning solutions.

To read this piece in its original form, it’s here!

Tag: AI