Yes a learning engine: demo is ready, but #AI and #Learning challenges ahead #TBB2019 @InnoEnergyCE

If you have ideas on ensuring continuity in pedagogy when clustering courses (research), on certifying across corporate and university learning (blockchain/bit of trust certification), on opening up industry academies to decrease L&D costs (HR and L&D), ... please think along and respond to the challenges mentioned at the end.

People in high and common places seem to agree that the world is in transition, especially workplace learning, as innovations keep changing what is possible. As I am working on one such an innovation (the skill project of InnoEnergy), I am at the one hand very excited about the new opportunities it might open, yet at the same time concerned that the complexity is bigger than expected.

First: have a look at the demo screencast here. It shows the overall idea, and ... this might immediately give rise to questions.

Today the Business Booster event (TBB) is opened, and with it, the skill project demo is launched. The skillproject (we still need to get a brand name for it), is combining AI and learning for the sustainable energy sector. But in essence, once we get the sustainable energy sector mapped with this tool, others can follow. 

AI and learning? What does it do: the project identifies industry needs (AI-driven), pinpoints emerging skill gaps in the sustainable energy sector (AI-driven), analysis the existing workforce to know where urgent skills gaps are situated (AI-driven) and then refers employees to a personalized learning trajectory addressing their skills gap (part AI, part human support). The goal of this project is to ensure that employees of the sustainable energy sector stay futureproof in a quickly changing working environment. Let's be honest, it sounds cool, but ... the challenges are multiple. 

The emergence of a Learning Engine

The skillproject helps realize the emergence of a learning engine, an intelligent career-oriented engine which knows your own skills and which signposts you to where you want to go with your career by suggesting a personalized learning track.

In the Learning Engine you simply type in “goal: become Director of Innovation’s in offshore wind energy which courses?” and the engine immediately returns a tailored, personalized learning track consisting of a variety of certified, business training from both universities, corporate academies, open educational energy resources and coaching options to send you on your way. This will allow professional learning to surpass the limits of classical, university-based learning.

Challenges

In order to get our engine to come up with the best, most-tailored courses, we need access to industry academies, as well as university courses. 

Learning-to-Learn capacities. Once we signpost learners to a cluster of courses, they need to take them (the familiar 'take the horse to water' comes to mind). But even if the learners are taking the courses, 

Granularity for course clustering: clustering courses to keep on top of your field of expertise is one thing, but then what is the granularity of those courses? Micro-learning is an option, and modular learning will become a clear necessity, as all learners have different existing knowledge, which means they all need different parts in order to upskill what they already know. 

Ensuring pedagogical continuity, even OU finds that a challenge. Great, so let's cluster modules. But then, how can we link these modules together, Do we believe in the non-pedagogical support (e.g. hole in the wall from Sugata Mitra already dates back 10 years), or do we need to find a solution to provide pedagogical continuity that fits with this new assembly of short modules, and courses coming from different sources (both university and industry)?

Certification across the learning ecologies: to blockchain or not to blockchain. Once we start learning across institutes, we need to keep track of that what we learn, by keeping tabs on the actual learning: corporate academy learning, university modules, hands-on training, workplace learning... one solution is to embed blockchain in education to keep track of all learning. But this is easier said than done, and open standards and trust might be an issue to consider (bit of trust initiative offers good reading). 

Feel free to send questions, comments, share your own projects... let's get together.

Redirect FB algorithms now and 4 lessons from #CambridgeAnalytica #digitalcitizens

Anyone interested in data and ethics has been reading a gazillion of articles the last week. So, time to recap the big results coming out of the Cambridge Analytica files: correlations have their scientific merits (argh!), humans can be profiled in just 12 likes (honestly, this is how diverse we all are?!), anything measured can be used against us (a Cobra), and teachers around the globe seem more ethical than scientists (my partner says it’s true, I say it isn’t). Well... manipulation is part of history, I guess... but still!

First of all, a nice MIT research project on “How to manipulate Facebook andTwitter instead of letting them manipulate you’ (yes, it is a timely title 😊 ) mentioned in MIT’s Technology Review. The project let’s you – the user – manipulate algorithms emphorced on you by Twitter and Facebook (I like it, activism from within the system). This initiative is called GOBO (if you want to jump right in, you can login for this project here) and it is a prject from researchers at the MIT Media Lab’s Center for CivicMedia. It has an interesting parallel referring to Cambridge Analytica approach, BUT in this case it is truly scientific, and they ensure deleting ANY and EVERY data collected once they have results on how you would like to see algorithms adjusted. So take back the algorithms of Twitter and Facebook with GOBO.

I am just resurfacing after the Cambridge Analytica fraud (I call it fraud as they have been anything but ethical in their so called scientific data gathering: no informed consent, data gathered and not anonymised before using it for 3 parties, data not deleted after a project was finished….).

Correlations are used successfully? Argh!! For years, many educationalists and researchers emphasize that correlation is no replacement for causality. Causality is the basis of all strong research. It is clear that education and correlation aren’t a love story. We- as educators and researchers - know and understand the importance of context, of language use, of how personal each of our learning journeys takes form. In a sense, we should know better then to construct a test that puts everyone in the same batch, and then believe in it to state those things that we think sound nice (however tempting that type of action is... I mean, saves time on reflecting, nuancing, evaluating... and all these time-staking stuff) … but Cambridge Analytica got away with it. PISA was/is another such example. It even manages to enter the OECD report (https://www.oecd.org/education/) as core element of proof leading to rigorous outcomes. PISA test is an in correlation resulting test. A nice list of educationalists that argued against using PISA here. With the Cambridge Analytica files, the correlation monster pops up once again … AND it is now used ‘successfully’ to blind-side people and to get them to doubt their political choices just enough to swing their vote. So, correlations can be used quite viciously for some of the time.  

Forget complex human traits: humans can be profiled in just 12 likes! And all of this comes from research (great paper on how it was set up here, Schwartz , Eichstaedt, Kern, Durzynski, Ramones, Agrawal, Shah, Kosinski,Stillwell, Seligman and Ungar (2013) . Well… how difficult is becomes to state (and belief) that humanity is truly diverse! Admittedly, the Big Five Traits also distil human diversity into just 5 personality traits, but still… being profiled on 12 likes… How individual are we, if that is all it takes to cast each one of us in a box that subsequently can be manipulated from that moment onward? It becomes quite difficult to see humans as complex beings when I take that into account… but we are social, at least that is now proven once again.

Anything measured can be used against us. One of the most interesting blogposts I have read, is an older one from MikeTaylor, stating that as soon as you try to measure how well people are doing, they will switch to optimising for whatever you’re measuring, rather than putting their best efforts into actually doing good work, and this optimising is always at risk of being distorted, even corrupted (Mike refers to Goodhart’s law, Campbell’s law and the Cobra effect – great read).

And teachers around the world have more ethical sense than scientists that do not teach… well it is a discussion, my partner says that fact is well known, I say scientists who do not teach can be ethical as well…. Those darn Cambridge Analytical (and derivates) people! (good example of this is Autumm Caines , she wrote on Platform literacy refering to her encounter with Cambridge Analytica to get all her data from them all the way back in February 2017 (which was a hastle!). Yes, she got active one year before this whole event blew up into an international scandal. Autumm keeps ethics high!   

Open Textbooks through REBUS community #opened

Great open textbook opportunity! Ever contemplated writing and sharing an open textbook? This might be the moment/community you were waiting for. The Rebus community offers an organized (actively learning) option to create, review, add, to open textbook initiatives… and - in the end - get them published. So open access, open writing, open collaboration … all the way and with an international perspective as well, in addition to being open minded about using multiple languages. 
 

Driven by a huge goal: “building a universal library of free Open Textbooks in every subject, in every language”, I have the feeling this is something to volunteer for, even if it is simply to gain more knowledge on the subject itself. They gather librarians, educators, researchers... to start or help with getting projects realised. I am very tempted (which book first?!).

How does the Rebus community achieve this goal? By supporting initiatives to write, organise and publish open textbooks on specific subject matter, and in as many languages as possible. As it is a non-profit organisation, those willing to put an effort into creating an open textbook, will not be paid… but like in Wikipedia, every contributor adds to a greater good: available open textbooks.

Every open textbook is published under the Creative Commons Attribution license, where the copyright remains with the author(s), and readers have access to the content without any kind of payment. 

Forum-driven, but with social extensions and network

Their main medium to create these textbooks is a forum. Forums have been trialed, tested over decades and they work if they are actively moderated. In this case, it is a dynamic and focused forum moderation.

They partner up with institutions and organizations dedicated to Open Textbooks, including: The Open Textbook Network, BCcampus, eCampus Ontario and OpenOregon (University of Arizona, University of Washington, University of British Columbia, Cleveland State University, University of Saskatchewan, University of Minnesota, University of Massachusetts Amherst, Brigham Young University, University of Hawaii, University of Maryland, and Plymouth State University).

More practical FAQ’s can be found here: https://about.rebus.community/faq/

Some practical first findings

• The collaboration can take place on multiple levels: copy edit/proofread/illustrate (etc.).
• The forum is well organized, and clearly aims at promoting collaboration based on social interaction.
• They have monthly, online office hours/meetings: video meetings offering advise or sharing knowledge (one definitely worth watching is the “open textbook: internationalperspectives” video with guest speakers from South-Africa, Haiti, Chile, Australia and USA), all of the videos can be seen here, e.g. how to adapt open textbooks, as well as planning options (e.g. who is willing to work on what).
• Although the community relies heavily on a forum, there is a clear and well-designed social media integration, both for projects, posts as for social purposes (e.g. following).

The Rebus community describes itself as

The Rebus Community is a non-profit organization developing a new, collaborative process for publishing open textbooks, and associated content. Rebus is building tools and resources to support open textbook publishing, and to bring together a community of faculty, librarians, students and others working with open textbooks around the world.
We want to make it easy for the community to contribute to the creation of open textbooks (their own, or others’), and support the creation of new, high-quality open textbooks, available for free to anyone, in standard formats (web, EPUB, MOBI, PDF, and print).

Hybrid presence an emerging format #OEB16

Last week I had the pleasure of being part of a virtual connecting meeting at OnlineEducaBerlin. The initiative came from the VConnecting group. For this session, onsite buddies Christian Friedrich, Hoda Mostafa, and I spoke with guests Jeanine Reutemann (Jeanine researches the affordances of video and has great insights on it!). Ilona Buchem (Ilona has a long standing tech record, her latest research looks at open badges) and Aziza Ellozy (Aziza is a leader in faculty development, and making learning visible). The recording can be seen below (it was a hangout).

For those who are not familiar with the concept of Virtually Connecting through online buddies, have a look at the website. During Online Educa Berlin 2016 there were four virtual connecting meetings (I only could attend one, as I was chairing or speaking at the other moments), and it really provides an additional layer of interest to conferences. I had a previous experience with Whitney Kilgore at eMOOCs2015 which I blogged about here, and which worked inspiring as well.

The format has a basic idea behind it: connecting people with similar interests across conference boundaries (so those who can attend a conference, share knowledge that is provided within the conference to others who are unable to attend the venue).

Although the idea is simple enough, what is interesting is the emerging layer of knowledge that is transmitted. In some way those who attend get a meta layer going. Or at least that was what I felt when joining one of the virtual connecting sessions. When reflecting on why this extra - and to me meaningful layer of learning emerges - I had the idea that it might come from the available expertise in all who entered the conversation. The shared yet complementary expertise gave spice to the conversation, sparking new ideas and links to previous experiences on topic. And I think it was also related to similar interests that come together at that point, and drive the conversation forward. 

In the session that I was in, the conversation covered the plenary keynotes, some ideas coming from the keynote speakers and how we (participants in the virtual meeting) agreed or disagreed, the overall feeling of the conference, the formats and the consequent results of the sessions...

#OEB16 results from personalised learning session #personalLearning

This session, which I facilitated at OEB16, had one of the ‘slow cooking’ formats. It takes time for all the elements to come together, and you work with those elements you find in the room (so thank you to all the participants) and … somehow magic happened as you can see from the results shared below. Each of the participants got this synopsis sent to them. The participants had a background in volunteering (and supporting the volunteers across the country through offering online solutions to their questions), corporate environments (ranging from actual online developers, to medical support professionals, to management), and academics & teachers. All of us are faced with similar challenges as the world keeps coming up with technical solutions and keeps changing, where our task as educational technologists/trainers is to keep bridging the divides created by change and innovative technology.

The aim of this OEB session: enabling personalised learning by sharing experiences/knowledge

In this blogpost, I will first share the list of challenges that we (all who participated) came up with (pictures), then share the actions that could lead to solutions (also 5 pictures from the flip papers), and finally the way I interpret those challenges and solutions. To all, feel free to add your interpretation, as many brains make stronger solutions.

The list from the challenges we face: grouped as learning characteristics, technology and media, individual & collaborative learning, contexts, and organising learning.

The list of solutions we started to think off:

How can we enable personalised learning looking at what the participants shared. My interpretation of what we came up with:

From trainer/teacher perspective:

• Try to cater to intrinsic motivation: solutions for the learner, adding to the interest of the learner, using tools the learner feels comfortable with.
• Provide options for just-in-time learning (the concept comes from mobile learning, but the reality is that we live in a constantly connected world where just-in-time is more broadly available, yet under-used).
• Deliver authentic learning opportunities. This includes selecting people in the field/workfloor to become trainers/teachers (eg. Offer action cam to record actual processes).
• Crowdsourcing the learners for needs and solutions. Start from learning goals the learners might have: start from their learning goals to direct them to solutions, or – if the solutions is not yet existing – allow them to share a solution once they found it. This means following up on problems put forward by the learner. Maybe built a channel or list with problems or needs voiced by the learners.
• The learner-generated products (movies, written problem solving options… all media) must be made retrievable afterwards in order for these materials to be found: meaningful meta tagging, offer strands of learning (see next point).
• Offer strands of learning: e.g. offer Continued Professional Development options per field, where learners can register for updates on particular fields (e.g. if they work on language learning, provide a push-solution that notifies them when a new bit of information is available (a push-solution is a messaging service that pushes news towards either a mobile or internet-connected device to which people are registered. For instance: registering for an online list which only shares new information in one particular field). Another strand of learning is a blockchain learning option that can be build: one learner finds a solution for learning how to draw in YouTube (and shares it on a central list), another learner begins advanced learning by following a MOOC on it (and shares it)… where at the end the learners have collaboratively set up an informal curriculum for learning how to draw and become really good at it. Use micro-learning as a way to solve small needs, yet be able to organise these micro-learning moments into a larger learning pathway.
• Stimulate informal as well as formal learning inside and outside the institute/company/organisation: if someone faces a problem, but they found a solution outside the company/university… then tell them where they can share that location or solutions.
• Increase literacy skills by a variety of ways: using fun games, and formal dry options, … when digital literacy skills increase, more tech solutions can come from the learner.
• Make learners aware of copyright options.

From a manager perspective:

• We need to activate the experts: enabling durable sharing of expertise. Reach those who are willing to become champions for specific topics or skills.
• A sharing culture is something that needs to be visible and used at all levels: top managers sharing what they learn, as well as volunteers. Leadership in sharing and collaborating must happen at all levels.
• Make the outcomes of learning visible (indicators, productivity…) to show that investment in learning pays off.
• Provide socializing spaces and times: on many occasions people keep information to themselves, until they hear others are also facing the same problems. By creating more social spaces, more information exchange can take place.
• Allow learner-generated production time to take place (this is a way to compensate those learners who are willing to be champions in a specific field and allow them to deliver useful material).
• Set up a learning support task force (a new product is launched, or a new production line or workflow needs to be implemented; the support task force can help with building change enablers or customised content with the help of the learners/workers/volunteers): instructional designers, media savvy people that can help to make learner-generated media/products be disseminated across the group/department/peer experts.
• Provide a clear pathway from the moment a problem arises at the learner/worker/volunteer level: if something is a problem, to whom must they convey the problem and how. And once the problem is communicated, how will it be solved/acted upon (and by whom). Making these learning/teaching pathways transparent to all.
• Designate content curators: allow people with expertise to curate content for a group. Make the curated content available to the rest of the group, like digital newspapers that highlight potentially useful new insights.

From developers perspective:

• Integrate self-evaluation or visible learning options inside learning apps/designs/hard-& software.
• Allow inside and outside information to be gathered or linked to: to enable learners to add additional information that might help others.
• Use more learning solutions from the mobile learning evidence-based theories: make learning seamingless, use augmented/alternate reality options, just-in-time learning, provide access to immediate sharing of knowledge opportunities (e.g. mobile movies streaming from a device, sharing descriptions to an easily retrievable specific field content area).
• Allow collaborative learning to take place: enable group formation to communicate more efficiently or intuitively to work on a problem.
• Allow integration of existing tools (that way the learner can come into your tool, while still using their own preferred media).
• Make the data that users produce secure, yet allowing them to share on other platforms (if it is allowed, and they want to).
• Provide a granular approach, that can be embedded into existing systems, yet adds easy micro-learning options.
• Create ways to indicate the usefulness of any part of the solution.

From a learner perspective:

• Make learning visible for the learner: showing them the progress they have made (projects, building digital or real life artefacts), provide self-evaluation options (e.g. reflecting on the process, thus increasing meta learning skills).
• Learning how to describe an existing need: knowing how to isolate the problem, where to go to next, and describing it to others that might be able to help.
• Share with others (in corporate terms: Work Out Loud). Sharing can be quite scary at first, but sharing makes your own learning visible, it allows others to see you as a champion, and it increases your skills and knowledge as you automatically reflect deeper on any subject as you share with others.
• Daring to fail: learn that it is okay to fail at first, but simply keep doing something if you think it will be useful in the end.
• Built a network of people that are expert in your field of interest.

When looking at the above, I think that in most cases information is available, but enabling people to be able to find (and distinguish) good quality information, and resharing that new knowledge is still a challenge. The thought that sharing is caring, and will help all of us, must be either reinforced or reignited.