research Archives - Coorpacademy

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.

Aristotle said it and it is still true: there’s no real knowledge without ethics

This article is part of our Learning research and innovation series, offered by Coorpacademy in association with the EPFL’s (Federal Institute of Technology of Lausanne, Switzerland) LEARN Center. The authors are Jessica Dehler Zufferey, Executive Director of LEARN and Roland Tormey, Coordinator of EPFL Teaching Support Center.

When reflecting on your lifelong learning journey, you probably contemplate on which training you would like to take, what knowledge you might lack, and which of your learning habits are sub-optimal. In some moments, you might even find yourself thinking about what “knowledge” really is; is it being up-to-date with the latest flow of information? Is it having accumulated expertise in a specific domain through experiences? Is it our general level of education? Or could it be something else?

Three types of knowledge

In Ancient Greece at the dawn of scientific knowledge, Aristotle distinguished three types of knowledge. (1)

Epistème refers to the understanding of the world and the universally true reason of why something is. Today, we would talk about this as scientific and theoretical knowledge.
Technè applies and uses this scientific knowledge, most of the times in order to achieve something. While epistème allows to understand the world, technè is about acting on the world. (2)
Phronêsis, the third type, takes the reflection one step further. Not only is theory applied in action, but phronêsis adds the consideration of the ethical implications of the proposed action. Some have translated it as prudence, but not in the sense of hesitant application, but rather practical wisdom or sagacity and the capacity to distinguish good from bad action in day to day life. It seems easy to consider phronêsis as a necessary ingredient of knowledge, when we remind ourselves that not all application of scientific knowledge was and is ethically optimal.

These ancient concepts continue to bubble through in contemporary social and human sciences research too. Jonathan Haidt (3), a social psychologist at the University of Virginia, has explored the way in which our actions are often driven by emotions and instincts rather than by rationality. Much of our ethical behaviour is, he argues, driven by ‘moral emotions’ like compassion, gratitude, contempt and anger, rather than by ‘moral reasoning’ as it is traditionally conceptualized. For those who think of themselves as rational people, his research is eye-opening in the way it demonstrates the typical cognitive bias in ethical decisions: they are taken very quickly and driven by emotion, with our rational mind being used to justify the decision after the fact. Cultivating the aptitude to live ethically then requires more than developing our rational selves. Developing phronêsis – practical wisdom – will require emotional as well as intellectual work, it seems.

Are we there yet in our current education models?

Of the three types of knowledge identified by Aristotle, epistème, related to science & theoretical knowledge, is the most teachable. Universal laws can be explained and demonstrated to learners. In turn, technè builds on epistème. The identification of possibilities to apply that theoretical knowledge can be trained for example by experiential learning. Most of our learning, at school, at university, in apprenticeship and in corporate workplace learning is of the first or second type. Instructional designers often try to optimize the learning experience in order to facilitate the transfer from epistème to technè, i.e. the application of theoretical and conceptual knowledge.

However, phronêsis cannot be taught independently of the other two. It is considered to grow naturally with experience. However, the opposite might be happening. François Taddei reports in his recent book Apprendre au XXIe siècle (4) how the consideration of ethical implications can drop with growing levels of expertise and education. He refers to a 2011 study showing that the number of years of medical studies was negatively correlated with empathy (the dimension of ethical considerations addressed in this study). Similar results are reported for management students who seem to lose their collaborative attitude over the course of their studies. Our own studies with engineering students have found that their levels of moral reasoning may decline as they study. (5)

Many call for a more integrated view on education that integrates all three types of knowledge. For example, the French national engineering accreditation body CTI (Commission of Engineers Titles) included the capacity to identify ethical responsibilities as an essential criterion for any training of engineers. (6) (If at this point, you want to analyse the capacity of practical judgement in your organisation, you could apply the inventory on ethical climate for example).

A training program addressing all three types of knowledge

Research suggests that training of phronêsis should not be implemented as pure philosophical courses on ethical reasoning. Criteria for success are for instance cognitive engagement through complex dilemmas with diverse potential decisions, emotional relation with realistic rather than dramatic case studies, and integration in subject-matter courses.

Take computer science education as an example. In this field, there has long been a focus on teaching computer science (the epistème part of it) and/or ICT (Information and Communication Technology) usage (the technè part of it). Only recently, and probably due to the general awareness about the digital transformation of all aspects of life and society, the analysis of the impact of digital technology on the world was included as an essential ingredient. The German Society for computer science, for instance, has declared in 2016 that digital education needs to include three questions:

How does digital technology work?
How do I use it?
How does digital technology impact the world?

In order to educate on the third question in our current projects on, more generally, computational thinking education, we sought for inspiration from the latest thinking in a quite new domain called sociology of digital technology (the most recent and complete view was presented by Dominique Boullier). Different perspectives are used in order to analyse the impact of digital technology on many levels:

Cognitive science and psychology help to analyse the impact on ones behaviour and thinking as a user of digital technology;

Social psychology and sociology support the evaluation of impact on interpersonal relations, social groups and society;

Historical comparison allows us to identify the impact on any aspect of life such as work, mobility, communication, security, or health. It can even shed some light on the question of how digital technology might impact the future.

Why it matters

Today, we see that scientific knowledge and technological evolutions, especially in digital technologies, have an enormous impact on the world. There are few things we now do without digital help, whether it’s explicitly using digital tools, or it’s the algorithms working in the background sometimes without us being aware of them. Our communication patterns have changed dramatically. In parallel, algorithms inside social media platforms recommend us social interactions. Professionals from multiple domains have included digital practices into their working habits. Our consumption is turning more and more towards e-commerce. Our online behaviour is used to advertise products and services more successfully, and the internet of things will expand the data available to improve these recommendation systems further. We should get prepared for more transformations in the future.

At the same time, we are confronted with incredible challenges, ecological (global warming, access to drinking water, renewable energy, …) and societal (just think of public opinion and democracy in this time of ‘fake news’), that we need to tackle if we want our societies and species to survive.

As a result, it is time to learn to learn again – not only theoretical knowledge and how to use it, but how to make use of it for the betterment of ourselves, of our relations with others, of our society, and our world.

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.

Authors EPFL Jessica Dehler Zufferey and Roland Tormey

Sources

(1) Aristotle, Nicomachean Ethics, second edition, translated by Terence Irwin, Indianapolis: Hackett Publishing Co., 1999.

(2) Stanford Encyclopedia of Philosophy. Episteme and Techne. https://plato.stanford.edu/entries/episteme-techne/#3

(3) Haidt, J. (2013) The Righteous Mind: Why Good People are Divided by Politics and Religion. London: Penguin

(4) Taddei, F. (2018). Apprendre au XXIe siècle. Calmann-Lévy

(5) Tormey, R. LeDuc, I., Isaac, S. Hardebolle, C. and Vonechè Cardia, I. (2015) The Formal and Hidden Curricula of Ethics in Engineering Education https://www.sefi.be/wp-content/uploads/2017/09/56039-R.-TORMEY.pdf

(6) CTI https://www.cti-commission.fr/fonds-documentaire/document/25/chapitre/1217

(7) Cullen, J. B., Victor, B., & Bronson, J. W. (1993). The Ethical Climate Questionnaire: An Assessment of its Development and Validity. Psychological Reports, 73(2), 667–674. https://doi.org/10.2466/pr0.1993.73.2.667

(8) German Society for Computer Science, 2016, Dagstuhl-Erklärung.Bildung in der digitalen vernetzten Welt. https://gi.de/fileadmin/GI/Hauptseite/Themen/Dagstuhl-Erkla__rung_2016-03-23.pdf

(9) Dominique Boullier. 2019. Sociologie du numérique. Paris, Armand Colin.

Learners Vote Coorpacademy as Top Gartner FrontRunner® for Learning Management – Press Release

Corporate Digital Learning expert Coorpacademy is pleased to announce that it has been recognised as the leading ‘FrontRunner® for Learning Management’ by The Gartner Digital Markets Research Team.

Software users voted Coorpacademy top in the entire category, based on Usability and Customer Satisfaction, beating 22 other providers including Cornerstone LMS, OpenEdX and Lessonly.

Coorpacademy is a major force in the provision of user-centric corporate digital learning solutions. Coorpacademy makes in-work training always about the user, connecting back with the learner to find a better way to deliver what they want, as well as encouraging staff to develop their skills, especially ‘soft’ ones, to future-proof both their careers and the corporate knowledge base.

It is a leader in the next generation of Workplace Learning tools, the ‘Learning Experience Platform (LEP),’ which work by enhancing learner interaction and engagement as well as offering a wide range of training content. In Coorpacademy’s case, this translates into new digital functionalities, such as gamification and mobile learning, the latest teaching innovations including reverse pedagogy and 5-minute targeted ‘micro’ training modules, individualised learning paths and multiple forms of high value content via a catalogue of over 1,000 courses.

Commenting on the news, Jean-Marc Tassetto, co-founder of Coorpacademy, noted that, “We are extremely proud to be recognised by the learners themselves as a leader in Usability and Customer Satisfaction, as we are all about the user experience and the fact that users rate our platform so highly is testament to that. This reflects our determination to only ever offer training that suits the learner and which engages them enough to keep them coming back for more!”

About Coorpacademy

An Edtech startup and the European leader in Corporate Digital Learning, Coorpacademy is revolutionising online training with a Learning Experience Platform that integrates the latest innovations in instructional design, including gamification, microlearning and adaptive and social learning. Coorpacademy offers tailor-made content for its B2B customers and their 800,000 employees, but also a catalogue of over 1,000 courses produced with top industry experts like Forbes, IBM, IBM Think Academy, Wolters Kluwer and Video Arts.

Founded in 2013, the company is based at the EPFL (Swiss Federal Institute of Technology)’s Lausanne campus, and also has commercial offices in Paris and London.

About Gartner Frontrunner®

FrontRunner®’s Learning Management Quadrant tool is 100% data-driven and has been architected to help businesses easily identify top software products in a particular category, based on verified user reviews across three websites – Capterra, Software Advice and GetApp, which operate under the overall Gartner Digital Markets umbrella. The final rank is derived from user reviews to highlight users’ current most-favoured Learning Management software: products qualify as FrontRunners if they have received 20 unique user reviews in the last 24 month and earned the top scores for Usability and Customer Satisfaction, as well as offering the core learning management functionalities of course tracking and course management.

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

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.

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!

Swiss EdTech is on the rise!

This blog post condense news from several Swiss medias.

Swiss EdTech is on the rise! In the EPFL (Ecole Polytechnique Fédérale de Lausanne) offices, the Swiss EdTech Collider, an incubator specifically dedicated to EdTech (Education Technology) companies, celebrated its first anniversary. Dedicated to ambitious entrepreneurs who want to transform learning and education through technology, it’s already a complete success. “From 30 startups when we began, we’re now 70 in the Collider. We already organized around 70 delegation visits of potential partners,” says Pierre Dillenbourg, researcher at the foundation of MOOCs at the EPFL and Swiss EdTech Collider’s President, in an article published in l’Agefi, a Swiss economic newspaper.

At the beginning, this idea comes from the difficulty for some entrepreneurs, specialized in innovative education, to reach the right investors. “Investors knew well the FinTech, MedTech, SpaceTech, BioTech, CleanTech sectors… but globally, the whole amount of knowledge about EdTech was a bit low.” Other advantage for these startups: the arrival of Coorpacademy inside the EdTech Collider, a bigger company with a B2B business model. “It’s a company that reached a different scale: the direction team has a large business experience and the company already employs 56 people” comments Pierre Dillenbourg on the Coorpacademy’s arrival inside the Swiss EdTech Collider.

Several assets put Switzerland in a good position in the EdTech sector. In an article from Largeur.com, a newspaper based in Romandy, Pierre Dillenbourg speaks about the different assets Switzerland has to become a leading education hub. “Around the Leman Lake, you can find, in addition to the EPFL, the IMD, the Ecole hôtelière de Lausanne, two university hospitals, and famous laboratories. And that’s only around the Leman Lake! The excellence culture in training is unique in the area. And the ability to find fundings is far more superior than what you can find elsewhere in Europe.”

Initiatives in the EdTech sector are multiplying. On April 19th, on the EPFL campus, Le Temps and PME Magazine have co-organized the first edition of the Forward tradeshow, the Innovation Forum for SMEs. More than 900 people were there to meet the actors that make the Swiss innovation. Digitalization was on the spotlight, and Jean-Marc Tassetto, co-founder of Coorpacademy, intervened in a workshop on the digitalization of continuous training for employees.

Fundings must follow these initiatives for them not to become obsolete. For Pierre Vandergheynst, VP for Education at EPFL: “The institutions and public authorities engagement is not only a bet on future, but a prerequisite for the digital revolution not to be perceived as a constraint for our economies, but as a source of economic growth.” An advise shared by the UNESCO, which estimates that “each dollar spent on skills for young people can bring 15 times more of economic growth.”

Sources :

L’Agefi : La technologie bouscule les salles de classe

Largeur.com : Le futur de l’éducation s’écrit en numérique

Tag: research