innovation Archives - Page 3 of 3

A new heart, infinite lives, to love learning a hundredfold!

This summer, our product team worked hard to give you two new features on the Coorpacademy platform. Here’s a short article to unveil them to you!

A new heart to love learning.

Cats have 7 (or 9), you had 3 to complete a course chapter on the Coorpacademy platform. Do you know what we are talking about? Lives, of course.

As a reminder, if you give a wrong answer, you lose a life. Once you’ve lost all 3 lives, you have 2 choices: you can watch the course video to win back one life, or you can start the chapter again. But that was before!

You have now 4 lives for each level, all the time, on Coorpacademy.

Why did we chose to do this?

We’ve observed that the success rate could increase by 50% on a course with one more life! Less stress, more time to focus on answering properly, on “Key Learning Factors” or on “Did you know?”. In the end, bigger chances to succeed in a course and bigger ones to love learning.

4 lives instead of 3 in order to improve, one more chance to answer rightly

Now that you love learning (even more that before), would you have 5 minutes?

5 minutes, it’s the time it takes to water your plants, to cook pasta or to take a shower. It’s now also the time you need to learn or to strengthen your knowledge on a topic. Because our agendas are fully booked, we’ve created 5′ Learning.

The way it works? It’s training, but in very short 5 minute sessions.

It allows you to learn always at the right time, before a meeting, when you really need to acquire some knowledge or – very simply – when you have a little time to satisfy your desire to learn.

Most importantly! There’s no life counting in 5′ Learning courses.

What does this mean?

You’ll never be stopped while doing a course, whatever the answers you give, right or wrong. You’ll then have time to focus on the correction of the questions you answered wrongly. Always keeping in mind that the goal is to revise, to learn and to memorize, at your pace.

Would you like a concrete example?

Franck is Digital Marketing Specialist in his company and he knows everything about digital campaigns. When he shows up at the office, he receives a meeting invitation from the SEO (Search Engine Optimization) Specialist, scheduled in 30 minutes, on the Google Ads “Quality Score” topic.

He freaks out a bit, because he doesn’t remember what it is and is afraid to ask someone. He takes his mobile phone, logs in into his company’s Coorpacademy Digital Learning Platform and selects the chapter “Quality Score: Your Adwords Campaign Currency” from the course “Search”.

4 questions, a 2 minute course video: in 5 minutes, Franck revised the key points of the Quality Score, without pressure because there’s no life tally, and is fully ready for his meeting.

Infinity of lives in 5′ Learning, zero pressure for a maximum of learning benefits.

The Principality of Monaco success digital learning story will be presented at Gartner ReimagineHR London 2019!

Reimagining the Future of Work.

At the Park Plaza London on September 18-19th, 500+ HR professionals will gather during this 2-day event around 7 tracks reimagining the future of HR and HR Executives from all across Europe will have the chance to attend 28 Gartner-led, insight-driven presentations.

Brian Kropp, GVP and Chief of HR Research Gartner, will do the opening keynote on “How HR Can Reimagine Work to Drive Performance.”

He says: “While important, things like artificial intelligence and automation are only part of the future of work story. Along with these conspicuous shifts comes a number of underlying trends — like rising transparency, or new work habits — with the potential to fundamentally change how work gets done.”

Brian will highlight the fundamental HR stakes facing the rise of AI and automation while focusing on the opportunities created by these shifts – opportunities most HR executives are usually unaware of.

During this event, Top HR trends and challenges will be explored in order to reimagine the future of work, through keynotes, one-to-one meetings and roundtables.

Digital business transformation, innovation, the rise of artificial intelligence… These issues are at organizations’ heart talent issues and companies will only succeed at addressing them if they have the right people with the right support.
We are in a period where we have unemployment rates for critical roles that are as low as 1% in some cases. For many roles, employers can’t find enough candidates.
Artificial intelligence, the gig worker, candidate and employee transparency, analytics carry a potential to fundamentally reshape the HR function.
There is more visibility than ever before – through channels like Glassdoor and Indeed, but also through internal communication tools – into things like compensation, manager quality, and what it’s like in general to work at an organization.
Talent management issues have hit the agenda of the C-Suite and the boardroom in ways they haven’t historically – through issues like workplace harassment and discrimination, and also through deeper attention from the investor community to the impact of talent management on business performance.

Having the right people with the right set of skills to thrive in this complex new environment.

Digital business transformation, AI or automation are creating opportunities. But organizations will manage to thrive in this future only if they have the right people with the right set of skills. Jean-Marc Tassetto, co-founder of Coorpacademy, was saying in his latest article, published in Finance Derivative: “As a result of the kind of seismic drivers of employment change taking place in all industries […], it is becoming more imperative that we all manage our long-term employability. Businesses, public institutions, large and small organizations – everyone’s at risk – that don’t equip their workforces with the tools to help will not be able to compete – shrinking, or even disappearing, as disruptive new players better prepared to help their teams develop the skills they need will take their place.”

A success Learning story.

The Monaco Digital Academy: a Learning Success Story

That is why the Government of the Principality of Monaco has confirmed Coorpacademy as its new digital training platform to underpin Monaco’s strategic transformation programme, Extended Monaco – a plan to digitise all of its public sector and economy.

In this context, the Principality’s government is launching a digital university, the Monaco Digital Academy, with a detailed training syllabus for its 3,600 public servants and agents in order to help them transition successfully to new way of working and processes.

Stéphan Bruno, Head of Human Resources for the Government of the Principality of Monaco, and Jean-Marc Tassetto, CEO of Coorpacademy, will present the project to the audience during a keynote on September 19th à 11:30, under the theme of Hyper-individualized Learning.

Stéphan Bruno explained the choice of Coorpacademy: “We wanted to create a training offer for our public service teams that is accessible, fun and diversified, and not limited to job skills. The user-centric learning experience offered by the Coorpacademy platform and the depth of its catalogue of courses elaborated with experts offered what we were looking for.”

“We are proud to have been selected as a core training supplier for this strategic digital plan that will impact all Monaco’s public policies,” adds Jean-Marc Tassetto, co-founder of Coorpacademy. “The importance of training in the strategy of the Principality’s government and leaders demonstrates the ambition of this plan and their global understanding of the issue of digital transformation.”

Discover insights about this training project.

If you’re in London on September 18-19th, comme meet the Coorpacademy Team!

“Hyper-individualized learning – How are the best companies and organisations in the world reskilling at scale their entire workforce for the jobs of tomorrow”, on Thursday 19th September at 11.30 – 12.00, Park Plaza London.

We’re looking forward to seeing you at this event!

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

When Struggle Helps You Learn: The Mechanisms Behind Productive Failure

Here is the first in our new series of articles focused on learning research and innovation, in association with the EPFL’s (Federal Institute of Technology of Lausanne, Switzerland) LEARN Center.

The author of this contribution is Dr Jessica Dehler Zufferey, Executive Director at the Center for Learning Sciences (LEARN) at the EPFL, and a former R&D director at Coorpacademy.

Innovation in Learning Science and Educational Technologies are at the 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.

Can the best learning only happen in a culture where errors are not just accepted but are seen as valuable occasions to improve skills?

When learning a new topic on the Coorpacademy platform, learners always have the choice to engage with questions first or to see the learning material first.

Intuitively one would expect that someone with high prior knowledge on the topic should start with questions, while someone with no or low prior knowledge should start with the instructional content before going on to answering questions. But is this actually true? Research on a method called ‘Productive Failure’ arrives at the opposite conclusion.

How does it work?

Initially developed in Singapore by Manu Kapur, now professor at ETH Zurich, and now established worldwide, Productive Failure emphasises the positive nature of the learner challenge. When learning new content, learners benefit from an initial phase of creative and conceptual brainstorming before turning towards the content, information, and explanation. If you want to learn something about data science, for example, you should first play with some data, invent some measures you could apply, and experiment with what you can come up with. The quality of the ideas you generate is not that important since even wrong ideas can create the productive failure effect. For Kapur, productive failure ‘is the preparation for learning’, not the learning per se.

What impact does it have?

Literature on the approach shows that not only will your conceptual understanding be better if you ‘fail first’, but your interest and motivation for the topic will be increased. A valuable side effect is also to train persistence. The number of ideas generated is also higher when failing first, so the method also stimulates creativity.

Why does it work?

The cognitive learning mechanisms behind the productive failure effect are actually quite well understood. First, any cognitive activation is beneficial for learning as it puts the brain in ‘active mode’. Second, all learning is situated and by developing their own ideas learners are creating the context in which to situate any upcoming learning. Third, by developing ideas before the instructional part, learners create a feeling for the types of problems that are similar so they are more likely to apply the to be learned content in future situations, and so improve performance as a result of learning.

What does it mean for you as a lifelong learner?

Whenever you start learning a new subject, do not go straight towards the instructional content in the belief that you need to begin by getting some basic understanding. Rather, profit from this initial ‘naïve’ phase and develop various ideas, right or wrong – and only then, once engaged, turn towards the content and enjoy learning.

Coorpacademy in the Top 5 hottest startups in Switzerland

Coorpacademy has been selected by The Next Web in the Top 5 hottest startups in Switzerland! TNW showcases the hottest young scale-ups in all European countries and Israel based on their performance, growth, and potential, which will all be represented at the TNW Conference in Amsterdam on May 9th 2019.

As Switzerland has been named the most innovative country in the world for eight years in a row by the Global Innovation Index, and ranked the second best startup ecosystem by the Global Entrepreneurship Index, Coorpacademy is proud to thrive in this startup heaven!

The Next Web describes Coorpacademy: “Coorpacademy is one of the fastest growing Edtech companies in Europe. The platform allows companies to train their employees through fun and interactive online courses on soft skills available off the shelf. The start-up is at the heart of research into new learning methods and is an expert in adapting its customers’ training content to new learning methodologies. Since its founding, they’ve raised €14 million, provided their services to over 150 enterprise clients and signed partnerships with more than 40 content partners. They are currently expanding internationally into the UK market and are growing their presence in France and Switzerland.”

Discover the full article on The Next Web website!

Learning Breakfast “Future of Learning”: an event co-organized with SAP SuccessFactors and with the participation of speachme

On April 12th, Coorpacademy welcomed in its Parisian headquarters, on 4 Boulevard Poissonnière, 40 Digital Learning Managers for a Learning Breakfast on the Future of Corporate Learning.

The event, co-organized with SAP SuccessFactors and with the participation of another Edtech start-up (speachme), allowed us to explore in 1 hour some of the latest trends in Digital Learning and in the future of corporate training.

The 3 speakers (Tolo Vinent, SAP SuccessFactors, Thibaut Chambon, speachme and Frédérick Bénichou, Coorpacademy) have shared their views on the Future of Learning: what’s at stake for Learning programs in a fast-changing world, the power of Peer Learning, how data can be used to improve the Learner’s experience.

Frédérick Bénichou, co-founder of Coorpacademy, unveiled our new Analytics Dashboard which integrates a dozen of behavioral indicators linked to the Learner’s experience, directly convertibles into concrete actions which allow Digital Learning Managers to better manage their online training programs.

The engagement, for example, even though it’s linked to performance, is not a indicator which can be reflected into concrete measures. We’ll present you a few of these (new) indicators in a next post!

Here are some pictures of the event:

Pictures of the Learning Breakfast

Tag: innovation