@Ignatia Webs: continued professional development

Showing posts with label continued professional development. Show all posts

Monday, 9 December 2019

#Learning monitoring in Belgium - based on #LearningDoctrine #synchronous

Just this morning I got a link to a video representing a new learning technology used at IMEC. As I looking into synchronous learning technology, this is of interest. But as I was watching the video, I felt a bit uneasy. This synchronous learning solution WeConnect is offered by Barco and is implemented at IMEC (which is connected to KULeuven, which will in the years become the major university in Belgium, as it is good in gaining and keeping established power).

Monitor the learner to push them into good followers
In this synchronous learning solution, online learners attending the synchronous classroom are monitored (facial expressions), psychophysiological data is captured (using wearables), engagement is measured (based on body movements) and interventions (quizzes, polls) are embedded in the lecture in order to keep the attention of learners. But again, this is leading the biggest batch of learners, the 'normal' learners, those who have an attention span lasting a full lecture. And it is aimed at lecture-based content (university content mainly), with of-course a teacher dashboard indicating engagement of the overall student population.

It is not about instruction, it is about stimulating creative thinking on subject areas of interest
I can see the benefits of this system, but it just annoys me intensely that it is again about instruction (absorbing information), not about actual learning (creating). For instance, if you use challenge-driven education and learners are working on their own projects.... surely the engagement and learning will skyrocket through the roof?

Adults learners need a digital shepherd?
When a child is young (even up to 18 years old), I can imagine you want to learn how to learn, how to stay attentive and what it can provide you with... but once you are an adult, surely you will know your own way forward? Surely, there should be more ways for any intelligent young adult to open their own world and live it the way they feel fit?
Why are technologists so scared a learner wouldn't be attentive, stare outside, have something on their mind... and then zoom in again on the subject that is given? To me, if a learner is not interested enough in the lecture... so what? If a teacher cannot grab your attention, what of it? Should we pressure learners into learning patterns they

Learning comes naturally
When you consider MOOCs, learners learn them and take them in their spare time. There is no 'optimization of learner posture'. People learn because they like the content because they are intrinsically motivated because they have a personal goal. I would think that tailoring content and delivery to nurture intrinsic motivation and personal goals is more useful, more fulfilling from the learner's point of view? Learning is in our genes, which makes all of learning unique yet natural in its uniqueness. With all of these technologies, I would think that human satisfaction would become more interesting as a subject for innovative technologies, then creating humans that learn alike, do alike, and follow digital indicators?

GDPR
Can a learner - using this system - decline being monitored? While still following the course or the lecture? Surely this should be the case? I would immediately ask to be non-monitored. But then this could be me.

Quantum supremacy surely makes 'proper old-school learners' obsolete?
I would be very surprised if the future would be all about the best learners (which human society has never been about either), but for those who can actually fill their spare time with actions that make them feel confident, useful, creative and ... happy. Subtracting new knowledge from data can become a processing-power based activity done by e.g. computers having the sycamore chip though granted, it will still take some years before it becomes fully functional for day-to-day actions. But still.... shouldn't we focus on getting humans more actively involved in a less-school-like higher education?

What do you think? Below is the link to the movie that sparked my sighed-based eye roll resulting in this blogpost. I will try to get my hands on using it for innovative learning.

LECTURE+ from imec on Vimeo.

Wednesday, 27 November 2019

Why is #AI useful to pro-actively prepare #learners in a changing world? #skills

Preparing for my talk today at Online Educa Berlin, after a great workshop-filled day yesterday (one of the workshops was on preparing for the 4th industrial revolution guided by Gilly Salmon - https://www.gillysalmon.com/presentations.html ) and a wonderfully inspiring and ideas provoking workshop with Bryan Alexander looking at methods to predict parts of the future).

Below you can find my slides for the session at Online Educa Berlin looking at ways that Artificial Intelligence can be used to pro-actively prepare learners for the skills of the future.

It covers the steps we have tackled at InnoEnergy with the skills engine. In the talk I will share our approach, and how this differs from what was previously done. The slides are rather minimal, but if you download the talk, you can look at the notes in the slides to get the full picture.

Building the Skills Engine: our dreams realise the future from Inge de Waard

Thursday, 19 September 2019

LiveBlog #Ectel2019 Rose Luckin @Knowldgillusion Keynote #AI & #education mindset

Rose Luckin takes the stage with a headset and immediately getting into her talk. The talk was very informative and to me it looked as though Rose is so knowledgeable about a range of topics, so I got a bit curious and envious in how her mind works [It I heard - I do not know if this is correct, will ask her ] that she only got into academic life later on in life?

Key topic: develop the right AI mindset for businesses

A perfect storm: data mass plus computing power and memory enhancements, sophisticated algorithms ... this made AI part of our lives and education.

3 routes to Impact on Education

using AI ED to tackle some of the big educational challenges
education people about AI so that they can use it safely and effectively
changing education so that we focus on human intelligence and prepare people for an AI world (hardest to do at the moment)

Working with select committee processes to try and take forward new developments. Debating on 4th industrial revolution and what it means that people understand AI (it is not coding, it is about the humans and their understanding of the fundamentals of machine algorithms, awareness, it is a much higher order we need to engage people with).

Need for multidisciplinary teams with equal input
As change happens, we need to change our educational systems (Singapore). Be resilient to change, be adaptive.
The above are not separate routes, it interconnects, and these interconnections increase AI and that we need to change and invest in our society using emerging ideas and realities of these three buckets.
We need to build bridges between communities: all stakeholders (parents, communities, government, coders...).
Currently separated communities need to work together to build a credible, societaly based AI solution.

Companies working with UCL EDUCATE
Not all companies are already using AI, but they want to understand more about it.
EDUCATE was from Europe, but turning into a global program from Jan 2020.
250 educational study start-ups (each start-up has to have a link with London, but they need to have some profile in London, so most UK-originated).
UCL provides training (labs, clinics, blended rooms, mentoring sessions)
It is free for the companies (years spend on figuring out the gaps between educational departments and industry. This was the case for hard sciences and industry, but not education). A lot of the reasons was because they did not know who to talk to, where to start => reason for starting with start-ups, embedding the educational mindset and to understand more about outcomes and validation of educational projects, so what it means when we say 'it works' (complexities... this results in the golden triangle: edtech developers, teachers & learners, academic researchers).

Start-ups are pushed to build a logic model, and the change being the learning that they want to take place. Opportunities they have to analyze the data, how should they demonstrate impact. We hope they will get to the last stage (see picture).
EdWards are set in place (awards to proof evidence applied and evidence aware awards).
120 companies became evidence aware, and 25 become evidence applied (last being much more difficult to achieve).

EDUCATE for schools
objective: build capacity in schools to identify and evaluate edtech that meets the needs of their teaching, learning or environment.
This approach can work in different educational programs.
Sit down, get head teacher in to pick two or three educational challenges - what they find tricky, than teachers are chosen to test it, to find out how the edtech works.
Currently this is under development:
all resources included in option 1, schools identify new or existing edtech to pilot
EDUCATE provides new resources to help schools plan their edtech pilot,
educate povides video and document resurces to walk schools through the pilot process
schools step through piloting process and recieve one hour of 1:1 video mentoring support
evaluate it (not sure I put this in correctly - this last step)

Sources
Century AI:
AI and big data powers personalised learning
Quipper: video insight, smart study planner, knowledge base
EvidenceB KidsCode : paths through materials, optimised parts through material

classic recommender systems (finding the right resources for the educator/student)
Bibblio
teachpitch

Chatterbox: refugee as expert native speaker with matching backgrounds (e.g. engineering background)
OyaLabs cloudbased monitor in the baby lounge and monitors interactions between baby and its cognitive developments for language developments
MyCognition algorithms automatically increase the number of training loops for the domains where you have the greatest need. If attention is your greatest needs you will receive more attention loops, building resilience in attention. As you progress the loops become more challenging. Looks at your attention, actions... assessment and report, which powers aquasnap and takes you to a underwater world (sea routes, fish names...) and adapted to your own cognitive status.

Building an AI mindset
Important for any company that wants to get into AI
What does it means to have the right data,
not just the tech team must understand the data and AI
as an individual it would be good to understand more about AI

Working with OSTC / ZISHI company: example of AI mindset collaboration. What they do: training for trader floors. They have to train everyone. They try to attract diversity in the workforce and pick them from less evident universities. ZISHI tries to use AI, AI for financial sector.
Financial sector has used AI for some time. AI used for assist in recruiting the best traders, assist in training the traders, help traders in improving performance, mentor the traders through out their careers.

Understanding OSTC's performance metrics

how can training behavior be measured?
can we profile traders by their trading behavior?
how do these profiles relate to performance?
can we then create a tool to help recruitment a tool to help traders and a tool to help managers?

The CEO of OSTC started out at the post floor of Lloyds and moved up. One's he saw the lack of training, he got into training and set up OSTC. Fundamentally what they try to do is creating AI mindset.

Much is not easy or obvious of what traders do

what others tell me that I do
what I think I do
what I really do
what family thinks you do...

Workflow
Nearly half their traders left less than one year in. So something was wrong, and investment was too costly for the results in the longterm.
Modeling using machine learning techniques to profile traders and make predictions (recruitment data from tests, interviews and videos, trading history data from trading platforms, multimodal data from eye-movements and button clicks, and behavioral data.
Masses of data from the tools used in the company.

Profiling 4 types of traders, using four identified characteristics:
data visualizations, using clustering techniques.
It turns out that the behavioral patterns relate to significantly different performance (risk management, bonuses... and different cognitive abilities & traits (openness to experiences, agreeableness...) [here my mind went off... must be something related to trader-vocabulary?]

Challenges to IA mindset

collaboration: is everybody onboard?
getting rid of AI's sci-fi fantasies and fears
digging in rich soil will bring out stuff. Are we ready to act upon it?
the appetite comes with the first byte - be ethically prepared to diet
data is har to collect, standardize, clean, #you-name-it

Opportunities for IA mindset

map the organisations' data information knowledge wisdom pyramid (and who is where
identify data sources: what is ready to be picked, what still needs to be ripened or sown
what can we learn from previous (successful of failed) experiments or pilots? what hypotheses they already have? what are their blind spots?
metrics - how do we know what success looks like?

OSTC - lessons

team members across different tiers need to embrace change
collect as much data
tech team in company not the same as data team
need new expertise to digitize documenten and learning content
develop coherent and consistent procedures in all offices across the globe despite the cultural bias
track the daily activities through logs and multimodal data
develop tools

Developing an AI mindset

AI is set to transform education
three core types of interconnected work: using AI, understanding AI, changing education because of AI
multi-stakeholder collaboration can help achieve these three types of work
EDUCATE is an example of a multi-stakeholder collaboration to help develop a research mindset in Edtech developers and educators
for AI companies, or companies who want to use their data and AI we also need to develop an AI mindset (or perhaps initially a data mindset)
Academic research partners need to be put in this mix

Barclays provided somebody (eagle) in branches, and they would help people to use technology (from simple to complex) to get people engaged about using and thinking about technology, and how they can get involved.

Monday, 16 September 2019

Academia & ageism?Looking for role models & #data #academia #ageism #success @EcTel19 @mLearn19

Iris Apfel overall fashion icon

As I am preparing to head out to mLearn/EcTel 2019, an issue turned up on potential ageism. Do you know of anyone who started their academic track at 50 or older and managed to gain access to a higher academic position? Please send me a message, I would love to interview them and know how they achieved that position. In case you have data regarding the below statements on age and academic positions, please inform me as well, would love to factualize my assumptions.

Academia is filled with older people!

If I look around at conferences, the biggest target population consists of older (old-ER) academics, who have achieved academic status, and doctoral students (mostly younger, present author and some of my friends excepted). So, if I walk around, it feels as though there is equal representation in terms of age.

But then I started to dig a bit deeper, while looking for successful role models within academia, who started their academic journeys later on in life. Now I wonder whether people that start their academic careers later in life, actually make it to higher positions within the academic world?

You just need a body of work …

It is a reality that you need to have some sort of body of work within a certain field to step up the professional ladder in most areas. But there seems to be a discrepancy in what is possible in the professional (read corporate) world and what is possible in the academic world. Or am I mistaken?

Forbes has this 30 under 30 people to follow. The list is comprised of people who are successful at a young age in something newsworthy. If you consider the age of 30, this means that even the ‘oldest’ ones only have 9 years maximum to reach this status of success. If you would translate this into academic tracks including bachelor, master, and phd finished, you have only about 4 to 5 years max to achieve potential success. This means you can achieve a successful status within this short amount of time: less than 5 years. Basically, if you start at 50+ you should be able to achieve success before keeling over and dying of old age :D

Now let’s get back to academia and tenure tracks for researchers starting their career later on in life.

Looking for numbers

We move towards a more data-driven world and with that, an increased belief that data is the final argument (not agreeing with this, just generalizing). So I wonder: what is the average post-doc age, and how does this average compare to average PhD age? Or better yet, how many 45+ people start a Ph.D. track, and how many 50+ people get into a post-doc function?

Just wondering, as I have the feeling that this doesn’t add up. And if this adds up, then how many of the tenure positions are held by academians starting out later in life? Can anybody get their hands on such numbers?

The reason I ask, is because some of us late academic bloomers can have a lot of citations (in open journals), written and published in a short amount of time. We also come in with transferrable skills: project leads (corporate), team skills, innovations… and I am just wondering whether these might be neglected when comparing candidates for academic positions. Could this be? Or am I wrong in assuming this? (again are there numbers?)

In a world where there is increasing pressure to combine academic with professional fields, this seems something that is missing. Because people with a prior corporate or governmental background, might be well placed in cross-over academic tenure positions? And in those countries where they urge people over 50 to stay employed or be employed, I just wonder if there are equal opportunities?

Or aren’t late bloomers part of academia status positions?

Who knows, excuses might be:

Yes, but they don’t have enough high profile papers,
Yes, but they didn’t supervise enough phd students,
Yes, but you need the 10 years of prior experience (not true, certainly not for 30 under 30)
Yes, but there is no ageism (without arguments to follow that statement),
Yes, but if you start late, you cannot expect to move up the academic ladder (that would be a crushing answer, would not it!).

Just looking for role models or numbers

Do you know of anyone who started their academic track at 50 or older and managed to gain access to a higher academic position? Please send me a message, I would love to interview them and know how they achieved that position.

If you have numbers regarding the above, oh!!! Please inform me as well, would love to factualize my assumptions.

In the meanwhile, writingly yours from EcTel and mLearn.

Monday, 26 August 2019

Working on the #LearningEngine matching #learning to #skillgaps #skills

Forget the search engine, ravel on the emergence of the Learning Engine (admittedly it is still a dream in progress, but we are getting closer)

What made search engines so innovative decades ago?

They created connections. Connections between online users and content. The search engine developers did not produce a lot of content, but they referred to content from outside providers, and that was what made it special: the immediate connection. It connected supply with demand, connecting small and big businesses, individuals and groups. The service built upon existing new developments that each of the content producers provided.

Content free and available. A great big benefit of the content that comes up in the search engines is of course that it is free, ... which is a lot more difficult if you are trying to build a learning engine. Professional courses are rarely free (MOOCs notwithstanding), and in a lot of cases even the courses themselves are behind closed walls: e.g. online courses only available for employees, for registered students...

Search engines are great, but Learning Engines are becoming a really urgent demand

The shift in our professional society is no longer about jobs that disappear due to automation, it is about jobs diversifying through the demands of change, driven by innovation. Learning to learn is becoming essential to being employed and moving forward (or at least it seems that way for some of the jobs in sectors driven by innovation and change).

In order to learn how to do a variety of jobs, we need to learn, and we need to personalize each of our learning journeys based on our previous experiences and skills, both hard and soft skills. This is where the Learning Engine comes in and takes shape. At InnoEnergy I am now co-developing learning for real life jobs. At present ‘addressing the skills gap’ is all the rave. LinkedIn is investing in its Economic Graph, Burning glass and alike are gathering data on Skills, countries and regions are building skills taxonomies (e.g. Nesta ), that can be used either in manual brainstorms and in Artificial Intelligence driven projects.

If you take into considerations these latest tech-innovations and options, it isn't difficult to imagine a true personalized Learning Engine.

The challenge is how to build a Futureproof Workforce? Maybe a Learning Engine

With the Learning Engine in my mind it combines innovation, AI and learning skills for the sustainable energy sector (as EIT InnoEnergy works within the sustainable energy sector). Basically, the project identifies industry needs, pinpoints emerging skill gaps in the sustainable energy sector, analysis the existing workforce to know where urgent skills gaps are situated and then refers employees (or employee groups) to a personalized learning trajectory to alleviate their skills gap.

The combination of these steps should ensure that the employees of the sustainable energy sector stay futureproof in a quickly changing working environment.

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

Just imagine that you go to the Learning Engine and you simply type in “Director of Innovation’s in offshore wind energy” and the engine immediately returns a tailored, personalized learning track consisting of a variety of certified trainings from both universities, corporate academies, open educational energy resources and coaching options! Personally, I think that would be quite a catch!

Learners mix and match already

In a way, we already see this shift towards a more quilted professional learning in the MOOC’s which are taken by professional learners to enhance their career opportunities. Those career-minded employees register for MOOCs developed by universities as well as businesses, and they take a few courses here, and a few courses there. Soon employees will be able to link different course certificates to ensure a future-proof career (whether we should be using blockchain in Education to validate the learning trajectory is something else (see some mails on this here and here).

Corporate academies will need to open part of their courses: are they willing?

As the project evolves, it is clear that the AI engines are running and becoming smarter as additional data is fed into the system. But the main challenge is still: how to get access to course descriptions so we can signpost learners to those courses. If we don't have access to courses, even descriptions than we cannot send learners to them.

I would think that corporate academies would benefit from sharing some of their courses: if they form a network, they will no longer need to develop all the courses, they could 'swap' or agree to develop specific courses and find other courses for their employees at competing companies. Because although they are competing, all of them have basic courses for their employees, and those course costs could be cut by coming to a course-development agreement.

(picture from http://wwwdev.kpbsd.k12.ak.us/departments.aspx?id=37724 )

Thursday, 6 December 2018

Session on #AI, #machineLearning and #learninganalytics #AIED #OEB18

This was a wonderful AI session, with knowledgeable speakers, which is always a pleasure. Some of the speakers showed their AI solutions, and described their process; others focused on the opportunities and challenges. Some great links as well.

Squirrel AI, the machine that regularly outperforms human teachers and redefines education by Wei Zhou

Squirrel AI is an AI to respond to the need for teachers in China. Based on knowledge diagnosis, looking for educational gaps. A bit like an intake at the beginning of a master education for adults.

Human versus machine competition for scoring education, and tailored learning content offerings. (collaborates with Stanford Uni). Also recognized by Unesco. (sidenote: it is clearly oriented at 'measurable, class and curriculum related content testing).

The ideas behind AI: adaptive learning is a booming market.

Knowledge graph + knowledge space theory: monitoring students real-time learning progress to evaluate student knowledge mastery and predict future learning skills. based on Bayesian network plus Bayesian inference and knowledge tracing and Item Response Theory. The system identifies the knowledge of the student based on the their intake or tests. Based on big data analysis the students get a tailored learning path. (personalised content recommendation using fuzzy logic, classification tree, and personalized based on logistic regression, graph theory, and genetic algorithm.). Adaptive learning based on Bayesian network, plus Bayesian inference, plus Bayesian knowledge tracing, plus IRT to precisely determine students current knowledge state and needs.

Nanoscale Knowledge Points: granularity is six time’s deeper. Used in medical field.

Some experiments and results: the forth Human versus AI competition, which resulted in AI being quicker and more adapt to score tests of students. Artificial Intelligence in Education conference (AIED18 conference link, look up video youtube.com, call for papers deadline 8 February 2019 for AIED19 here).

Claus Biermann on Approaches to the Use of AI in Learning

Artificial Intelligence and Learning: myths, limits and the real opportunities.

Area9 lyceum: also adaptive learning long-term company with new investments.

Referring to Blooms 2sigma problem.

Deep, personalized learning, biologically enabled data modeling, four-dimensional teaching approach.

How we differ: adaptive learning adapts to the individual, only shows content when it is necessary, takes into consideration what the student already knows, follows up on what the student is having trouble with. This reduces the time of learning, and increases motivation. Impact from adaptive learning, almost 50% reduction of learning time.

Supports conscious competence concept.

AI is 60% of the platform, but the most important part is the human being, learning engineers, the team of humans who work together makes it possible.

Marie-Lou Papasian from Armenia (Jerevan).

Tumo is a learning platform where students direct their own development. After school program, 2 hours twice a week, and thousands of students come to the centre of TUMO. Armenia and Paris, and Beirut.

14 learning targets ranging from animation, to writing, to robotics, game development…

Main education is based on self learning, workshops and learning labs.

Coaches support the students and they are in all the workshops and learning labs.

Personalisation: each students choose their learning plan, their topics, their speed. That happens through the ‘Tumo path’, which is an interface which enables a personalised learning path (cfr LMS learning paths, but personalized in terms of speed and choices of the students). After the self-paced parts, the students can go to a workshop to reach their maximum potential, to learn and know they can explore and learn. These are advanced students (12 – 18 years, free of charge).

Harnessing the power of AI: the AI solves a lot of problems, as well as provide freedom to personalise the students learning experience. A virtual assistant will be written to help the coaches to help the student guided through the system.

AI guided dog: a mascot to help the students.

The coaches, assistants… are their to learn the students to take up more responsibility.

For those learners who are not that quick, a dynamic content aspect is planned to support their learning.

Wayne Holmes from the OU, UK and center for curriculum redesign, US

A report commissioned about personalized learning and digital ... (free German version here , English version might follow, will ask Wayne HOlmes).

Looking at the ways AI can impact education

A taxonomy of AI in education

Intelligent Tutoring System (as examples mentioned earlier in the panel talk)

Dialogue-based tutoring system (Pearson and Watson tutor example)

Exploratory Learning Environments (the biggest difference with the above, is that this is more based on diversification of solving a specific problem by the student)

Automatic writing evaluation (tools that will mark assignments for the teachers, also tools that will automatically give feedback to the students to improve their assignments).

Learning network orchestrators (tools that put people in contact with people, e.g. smart learning partner, third space learner, the system allows the student to connect with the expert).

Language learning (the system can identify languages and support conversation)

ITS+ (eg.. ALP, Alt school, Lumilo. The teacher wears google glasses, and the students activity comes as a bubble visualizing what the student is doing).

So there is a lot of stuff already out there.

We assume that personalized learning will be wonderful, but what about participative or collaborative learning

Things in development

Collaborative learning (what one person is talking about might be of interest to what another person is talking about).

Student forum monitoring

Continuous assessment (supported by AI)

AI learning companions (e.g. mobile phones supporting the learning, makes connections)

AI teaching assistants (data of students sent to teachers)

AI as a research tool to further the learning sciences

The ethics of AIED

A lot of work has been done round ethics in data. But there are also the algorithms that tweak the data outcomes, how do we prevent biases, guard against mistakes, protect against unintended consequences….

But what about education: self-fulfilling teacher wishes…

So how do we merge algorithms and big data and education?

With great power comes great responsibility (Spiderman, 1962, or French revolution national convention, 1793)

ATS tool built by Facebook, but the students went on strike (look this up).

Gunay Kazimzade Future of Learning, biases, myths, etcetera (Azerbaijan / Germany)

Digitalization and its ethical impact on society.

Six interdisciplines overlap.

Criticality of AI-biased systems.

(look up papers, starting to get tired, although the presentation is really interesting)

What is the impact of AI on our children is her main research considerations. How is the interaction between children and the smart agents. And what do we have to do, to avoid biases while children are using AI agents.

At present the AI biases infiltrate our world as we know, but can we transform this towards less biases?

Wednesday, 14 February 2018

Workshops worth attending: #storytelling, #citizenship and #mobile learning

Great workshops and seminars are open for registration, and gladly listing three that caught my attention: two in Europe (Germany and France), one in Maryland, USA.

Beyond Storytelling 2018: Re-Authoring Futures

When: 8 – 9 June 2018

Where: Hamburg, Germany

Cost to attend: 1000 EUR.

Early bird: 790 EUR (28 February)

Information: http://www.beyondstorytelling.com/introduction/

Registration: http://www.beyondstorytelling.com/bst18tickets/

Program: http://www.beyondstorytelling.com/program/ (Keynotes from: Joe Lambert (Chief listener and convener), Chené Swart (Consultant and trainer), Sohail Inayatullah (UNESCO)

Description (from organisation)

Futures are unknown and cannot be known. Yet, individually and collectively, we need an image and an idea how the future will look like to inform and guide our decisions and actions in the here and now.

At the same time, we are tempted, as individuals, organizations and communities to project what we know into the future. All too often, these imagined futures are constrained by what we think is possible or impossible to do.

True change and innovation rests on our ability to re-imagine and re-author the futures we want to live into – to open new perspectives and new ways of thinking and doing.

At BEYOND STORYTELLING 2018 we want to explore the potential of narrative approaches and working with stories to support organizations, individuals and communities in exploring their futures anew.

UNESCO Mobile Learning Week 2018

When: 26 – 30 March 2018

Where: UNESCO headquarters, Paris, France.

Cost: registration mandatory. No cost to attend, but travel and stay at your own expense.

Information: https://en.unesco.org/mlw/2018

Registration: http://www.surveygizmo.com/s3/3517120/MLW-2018-Registration-Form-EN-FR

Description:

Mobile Learning Week is UNESCO’s flagship ICT in education conference. Mobile Learning Week 2018 is being organized in partnership with the International Telecommunication Union (ITU), the United Nations specialized agency for ICT.

The 2018 event will be organized under the theme “Skills for a connected world”. Participants will exchange knowledge about the ways governments and other stakeholders can define and achieve the skills-related targets specified by Sustainable Development Goal 4 (SDG 4).

The conference, consisting of four related sub-events, will facilitate actions to:

Defining and mainstreaming digital skills;

Innovating skills provision for jobs in the digital economy;

Closing inequalities and gender divides; and

Mapping and anticipating changing skill needs

The sub-themes and sub-events of the conference are explained in detail in the concept note. Overall, Mobile Learning Week 2018 will provide a platform to share exemplary practices in mobile learning, with a specific focus on blending ‘non-digital’ education approaches and mobile learning applications in order to reduce inequality, spur innovative approaches to teaching and learning, and bridge formal and non-formal systems.

Programme

Workshops - Monday 26 March

The Workshops will facilitate demonstrations of innovative policies, research, projects, and mobile learning solutions. Workshop presenters will be selected from wide range of international organizations, NGOs, governmental agencies, and academic institutions that are implementing digital skills development programmes. Sixteen workshops will be conducted.

Symposium – Tuesday 27 and Wednesday 28 March

The Symposium forms the core of Mobile Learning Week and will feature opening and closing remarks from UNESCO, ITU and other partner organizations, keynote speeches, high‐level plenary addresses, and over 60 breakout sessions.

Policy Forum – Thursday 29 March (invitation only)

The Policy Forum will offer a platform to discuss the different pathways that governments are using to support the development of the digital skills required in the digital economy.

► Download the Policy Forum agenda.

Strategy Labs - Friday 30 March

Strategy Labs will be hosted by UNESCO and ITU partner organizations to help guide the conceptualization and refinement of projects for defining frameworks, assessing digital skills across groups and across time, and anticipating the changing needs for digital skills.

Seminar: Citizenship in the American and Global Polity: An Interdisciplinary Seminar for College and University Faculty

When: 15 – 20 July 2018

Where: Aspen Wye River campus in Queenstown, Maryland, USA

Information: https://www.aspeninstitute.org/seminars/wye-academic-programs/

Registration: 1 March 2018 at the latest

Cost:
Full participant = $2,975

Accompanying spouse/guest = $2,100 (shared room, all meals)

All costs include lodging, meals, group events, and materials. Airfare and transportation to and from the closest airport is not included; early flight booking is strongly recommended.

Description:
Part of the Wey Academic Programs. The Wye Faculty Seminar is one of the premier faculty development programs. The seminar seeks to address what we believe is a central need of faculty members—to exchange ideas with colleagues from other disciplines and other institutions committed to liberal education, and to probe ideas and values that are foundational to liberal learning in a free society.

Modeled in the tradition of the Aspen Institute Executive Seminars, the Wye Faculty Seminar combines three essential goals:

to gather a diverse group of thoughtful individuals in intellectually rigorous discussions;

to explore great literature stretching from ancient to contemporary time; and

to translate ideas into action suitable to the challenges of our age.

Outcomes and Impact

Past participants have emphasized the following outcomes and impact of their participation in the Wye Faculty Seminar:

Personal and professional refreshment;

Deeper and broader knowledge of interdisciplinary approaches to classroom discussions;

Exposure to diverse academic and personal perspectives.

An example of past curriculum can be found here.

The Wye Faculty Seminar is offered to selected faculty members who have the honor of being nominated by their presidents and deans for their distinctive contributions to the quality of liberal education.

The Wye Faculty Seminar combines vigorous intellectual exchange with time to read, reflect, exercise, and socialize on the beautiful Aspen Wye River campus in Queenstown, Maryland. The seminar is supported jointly by AAC&U and the Aspen Institute.

(picture from http://blog.strategyzer.com/posts/2014/12/02/how-to-design-great-workshops )

Monday, 11 December 2017

Free report on #digital competences of educators #EUpolicy #education @EU_ScienceHub

This 95 page report on Digital Competences of Educators was brought to my attention by the fabulous Yannis Angelis, who is also a great twitter networker (@YannisAngelis). This recently published report offers a European Framework for the Digital Competence of Educators and is written by Christine Redecker and Yves Puni.

This is a really strong framework (really good read) and it does touch all the competences a contemporary educator should have (and already has in many occasions). I think this framework can easily be tailored for practical use inside educational institutions. Another thought that crossed my mind: look at the competencies and than try to come up with any profession that includes all of these competencies as well... not easy, as it implies communication skills, technological skills, social skills and pedagogical skills.... and all in an increasingly complex world of learners. So what I hope is that this report will see the start of a reappreasal of the educator in the whole of society... I mean, you got to love the teachers!

The tagline of the report is: the European Framework for the Digital Competence of (DigCompEdu) responds to the growing awareness among many European Member States that educators need a set
of digital competences specific to their profession in order to be able to seize the potential of
digital technologies for enhancing and innovating education.

Content of the report
The report focuses on 22 competences, organised in 6 areas:
Area 1: Professional engagement, using digital technologies for communication, collaboration
and professional development.
Area 2: Digital Resources sourcing, creating and sharing digital resources.
Area 3: Teaching and Learning Managing and orchestrating the use of digital technologies
in teaching and learning.
Area 4: Assessment using digital technologies and strategies to enhance assessment.
Area 5: Empowering learners using digital technologies to enhance inclusion,
personalisation and learners’ active engagement.
Area 6: Facilitating learners’ digital competence, enabling learners to creatively and responsibly use digital technologies for information, communication, content creation, wellbeing and problem-solving.

For each of these competences more information is given, including a description of what the authors define the competence to be, and how to achieve it.

Nice side note: self-regulated learning is part of the competences of an educator. I really like the addition of this aspect to the teaching and learning competence.

Take into account competence levels of the educators
Another nice point of attention used in this report is the levels given to the competences in relation to the digital experience of the educator: in the first two stages of DigCompEdu, Newcomer (A1) and Explorer (A2), educators assimilate new information and develop basic digital practices; at the following two stages, Integrator (B1) and Expert (B2), educators apply, further expand and reflect
on their digital practices; at the highest stages, Leader (C1) and Pioneer (C2), educators pass on their knowledge, critique existing practice and develop new practices.
The labels for each competence level were selected to capture the particular focus of digital technology use typical for the competence stage. the descriptors also relate to an educator’s
relative strengths and roles within a professional community. And within the report a clear proficiency progression by area is also provided (page 31). Adding examples to make this theoretical framework a practical document (e.g. finding digital resources and what this entails for all 6 competency levels). A lot of work is put into making this theoretical framework accessible for practical implementation, an aspect I really appreciate and like a lot.

background of publication
This publication is a Science for Policy report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service, which you can follow @EU_ScienceHub. It aims to provide evidence-based scientific support to the European policymaking process, but it also offers great insight into what policy makers find of interest, and where they think educators will benefit from in order to ensure digitally competent education.

Abstract from the report
As educators face rapidly changing demands, they require an increasingly broader and more sophisticated set of competences than before. In particular, the ubiquity of digital devices and the duty to help students become digitally competent requires educators to develop their own digital competence. On an international and national level a number of frameworks, self-assessment tools and training programmes have been developed to describe the facets of digital competence for educators and to help them assess their competence, identify their training needs and offer targeted training. Based on the analysis and comparison of these instruments, this report presents a common European Framework for the Digital Competence of Educators (DigCompEdu). DigCompEdu is a scientifically sound background framework which helps to guide policy and can be directly adapted to implementing regional and national tools and training programmes. In addition, it provides a common language and approach that will help the dialogue and exchange of best practices across borders.
The DigCompEdu framework is directed towards educators at all levels of education, from early childhood to higher and adult education, including general and vocational education and training, special needs education, and non-formal learning contexts. It aims to provide a general reference frame for developers of Digital Competence models, i.e. Member States, regional governments, relevant national and regional agencies, educational organisations themselves, and public or private professional training providers.

Sunday, 8 October 2017

Free webinar: language learning apps and MOOCs for refugees

This one hour free webinar focuses on language learning apps and some used within MOOCs for refugees. The idea is to increase social inclusion and enhance employability for new arrivals. However, the language learning apps can also be an addition to other formal learning (e.g. for students who recently came to live in a new country and are attending regular school but who can use personalised language support, anyone moving to another country where they need to learn another language (ex-pats, immigrants), to anyone simply interested in keeping up to date with a language they have learned (e.g. my French needs refreshing).

Free webinar link and registration information:
https://moonliteproject.eu/events/webinars/language-learning-apps-moocs-for-refugees/

When: Wednesday 25 October, 15.00-16.00 CEST (Central European Summer Time, to know when the webinar takes place in your timezone you can look at Time Zone Converter here: https://www.timeanddate.com/worldclock/converter-classic.html )
Where: Online via Adobe Connect (so check the link to the webinar once it is sent to you).
You need to register for this free webinar (link here), this means you need to add your firstname, name and organisation (if you are not linked to an organisation, simply put 'virtual network' or similar).

The link to the webinar room will be sent to all registered participants one day before the event.

Speakers:
Agnes Kukulska-Hulme: mobile language learner by excellence, The Open University, UK
Timothy Read: computer languages and systems (also set up first MOOCs in Spain), UNED, Spain
Alastair Creelman: elearning specialist, Linnaeus University, Sweden.

What to expect
The question being considered in this webinar is whether such resources represent an effective learning approach for refugees given their changing geographical, sociocultural and technological circumstances?
An important part of social inclusion is having the foreign language skills necessary for day to day life. ICT, including mobile apps and open online courses, forms an important part of the way in which languages are learnt in our modern society. The improvement in communication networks and online tools, accessible from a range of mobile devices and desktop computers, facilitate activities developed to improve the four basic language competences (written and oral comprehension and production). Furthermore, the wide availability of free language learning apps can help to supplement the online learning experience, especially when network access is limited.

The webinar is organised by the Erasmus+ project MOONLITE in cooperation with EDEN (European Distance and E-learning Network), NVL Distans (Nordic Network for Adult Education) and the Swedish Network for IT in Higher Education (ITHU). The Moonlite project focuses on MOOCs for social inclusion and employability.

Thursday, 1 June 2017

Free: Handbook of Learning Analytics #LAK #learninganalytics #data

This is simply a must have for anyone into learning: the Handbook of Learning Analytics by Charles Lang, George Siemens, Alyssa Wise and Dragan Gašević. Really, it is an astonishing bundle (350 pages!) of learning analytics insights, which will get anyone with an interest in learning analytics up to speed with current challenges and ideas.
The publisher made this introduction:

"It aims to balance rigor, quality, open access and breadth of appeal and was devised to be an introduction to the current state of research. The Handbook is a snapshot of the field in 2017 and features a range of prominent authors from the learning analytics and educational data mining research communities. The chapters have been peer reviewed by committed members of these fields and are being published with the endorsement of both the Society for Learning Analytics Research and the International Society for Educational Data Mining."

Bluntly copying the table of content below to give an idea of who contributed and what you can expect from the papers.