Online Educa Berlin 2017 – rough notes

I recently attended my first Online Educa Berlin conference and found it to be very interesting. With over 2,000 attendees there are enough sessions for you to really dive into whatever is your particular edtech passion. There are also a large number of exhibitors. The focus of the event is largely US and European, but for me this was a breath of fresh air after almost always attending developing country events.

I presented the key findings from the forthcoming landscape review Digital Inclusion for Low-skilled and Low-literate People.

Below are my rough notes from the event, with key takeaways in highlight.

Learning and Working Alongside AI in Everyday Life

Donald Clark, Plan B Learning, UK

• Recommended book: Janesville: An American Story.
• 47% of jobs will be automated in next 20 years — claimed by Frey and Osborne, 2013. He says it’s not true.
• Top 10 market cap companies in the world: 8 of 10 use AI or tech.
• AI is already in our lives. We have all watched a Netflix show or bought a book on Amazon because of a software-based recommendation.
• AI in learning:
  • One of the biggest uses of AI in ed is to check for plagiarism. We can do more.
  • Coursera uses AI for online assessmenta (face recognition).
  • Check out: Wildfire (automated learning content creation), PhotoMath (Scan a maths problem for an
    instant result plus working out), Cogbooks (advanced adaptive learning platform).
  • Opportunity: AI can analyse and assess data without bias (unlike humans).
• AI affects what we should teach, how we teach it, why we teach it. We need to rethink the education offering in the age of AI.

Tarek R. Besold, City, University of London, UK

Key message: AI is useful, but not everything is AI and AI is not good at all things. We need to think more carefully about what AI does well, what humans do well, and how we can work together.

• Not all tech is AI, e.g. VR is not AI.
• Intelligent tutoring only works well on well-defined, narrow domains for which we have lots of data.
• Learning analytics is best used to track learner and teacher activities so as to identify individual needs and preferences to inform human intervention.
• He pushes back against the popular call for all young people to learning coding. He says they don’t need to all learn programming, but rather logical thinking, procedural thinking, reasoning.
• AI will not create equal access to education because of inequality in ICT infrastructure.
• AI is good at taking over the “declarative knowledge” part of teaching, which can give human teachers/educators more time to focus on skills and the social aspects.
• See the “human touch” as a value proposition beyond AI.
• In automation, AI can take over mechanistic and repetitive tasks, giving human workers time to focus on decision-making, creative tasks.
• Impact of AI on labour market: We need a societal decision: less workers or shorter working week for everyone (we can push back at tech companies)?
• Must read for the AI-savvy decision maker: Artificial Intelligence and Life in 2030 (Stanford University report).

I asked: If AI should augment teaching and learning, with both humans and AI having strengths, how do we move AI into education (that could perceive it as a threat)?

• Donald: Practical level: introduce spaced learning, adaptive learning, content creation to demonstrate the benefit.
• Tarek: Political level: take the market approach out of education. Ensure humans will not lose jobs because of technology, shift societal perspectives on putting humans first.

LMS

• Rethinking Learning Management Systems as Next Generation Digital Learning Environments (NGDLE) — see this article.
  Not an LMS but an LMX (Learning Method Experience).

• It can be difficult to choose the right standards. Below is what Marieke de Wit, SURFnet B.V. shared:

LTI standard apparently rather poor on documentation right now.

Jeff Merriman, Associate Director of MIT’s Office of Educational Innovation and Technology and co-founder of the DXtera Institute:

• MIT has a growing open-source Educational Infrastructure Service (EIS).
• No UI, they are “headless”.
• Integration challenge is huge.
• How can chatbots interface with a LMS? Use existing software, example Slack, as the LMX. Chatbot integration is then back-ended by, for example, an assessment service.

 

Chatbots in teaching and learning

Donald Clark, Plan B Learning, UK

• BabyQ and Little Bing (by Microsoft in China) – now censored by Chinese gov for anti-govt posts.
• Nima – the non-emergency NHS bot
• Meetcleo.com – finance bot

• Learning bots:
  • Onboarding bots: chiefonboarding
  • Find stuff: Invisible LMS. Engagement not management
  • Learner engagement: differ.chat
  • Learner support: Deakin’s campus genie student services / IBM and “Jill Watson”
  • Teach courses: Duolingo bots for language learning
  • Practice dfficult learner’ bot for teachers
  • Well-being: Woebot
• 7 interface benefits:
  • Natural, easy to use interface
  • Frictionless interface
  • Less cognitive overload
  • In line with current online interfaces
  • Suitable for younger audiences
  • Less formal but still structured
  • Presentation separate from AI drivers

 

Emerging Technology to Develop Learner Engagement and Increase Impact on Language Learning Outcomes

Geoff Stead, Cambridge Assessment English, UK

• Cambridge English Beta
  • “Curious about how to shape our future products? Cambridge English Beta is the place to find out about our latest digital developments and get early access to trial versions of our English language learning products.”
• Quiz Your English live challenge
  • Free game
  • 2.5m games played
  • 70k players
  • Top players play over 7k games per month
  • 70% of installed users drop off in first week
  • Features:
    • Social clues, people challenging you
    • Leaderboard
    • Next steps
• The Digital Teacher
  • Resources to help you build your confidence and develop the skills you need to take your next step in digital language teaching.
• Cambridge English MOOCs
  • 6 Moocs, run 14 times
  • 132,000 active students
  • Partner with FutureLearn (UNESCO is also a partner)
  • Successes:
    • Lots of use of video clips of real teachers, real learners and real lessons
    • Tasks to accompany each video
    • Community of learners

Chris Cavey, British Council

• British Council MOOCs
  • 13 MOOCs run 50 times
  • Again, using video for teaching
  • Lots of tasks: what do think of? Tell us about your day?
  • Facebook Live sessions. Lots of discussion and interaction during MOOC. At end, send students to FB group. For BC their FB group has 200,000 users. Throughout, lots of social media interaction and sharing.
  • MOOCs do not assess language skills, they help prepare users for traditional assessments. It is a spring board and platform for peer sharing and learning.  MOOCs can measure time on task, engagement level, etc.

 

UNV e-Campus

https://learning.unv.org/

• Moodle-based.
• Mandatory training (ethics, volunteering, etc.) as well as supplementary courses, e.g. language learning, life skills, business development (courses are bought by UNV for the users).
• Engagement: Communities-of-practice, remote coaching, online chat events, webinars.

 

Myths And Facts About the Future of Schooling

Pasi Sahlberg, director general of the Centre for International Mobility in Helsinki, Finland

He compared …

Unsuccessful education policies (Global Education Reform Movement) – England, USA, Australia, Chile:

• Competition
• Standardisation
• De-professionalisation (anyone can become a teacher, as long as you love children)
• Test-based accountability
• Market-based privatization

Successful education policies (Global Education Reform Movement) – Japan, Canada, Estonia, Finland:

• Co-operation
• Encourage risk-taking and creativity
• Professionalism
• Trust-based responsibility
• Equitable public education for all

Next predicted indicator group:

• Health and well-being of children, not only equity and excellence

 

Longevity, Learning, Technology

Abigail Trafford, author and leader in the movement to fight ageism, USA:

• Not years at the end, but healthy decades in the middle.
• 50s and 60s: second adolescence. What do I want to do?
• We need infrastructure to help older people for their next career, e.g. training, learnerships, internships.
• Wide open opportunity for new curriculum development and part-time learning and work.
• Over 1/3 of US is over 50.
• Brain is plastic, it keeps learning.
• Older people are better at analysis and strategy; younger better at quick learning and short term memory.
• A long way to go to mainstream education and learning across the lifespan.
• Old think: 9-5 work until retirement.
• New think: 24/7 production and services.
• We all need to expose and fight ageism.