Visiting the conference was well worth it. Lots of good international contacts and discussions with colleagues from literally all over the world. Good access to speakers and experts on subjects of interest. I think there is enormous value in attending this conference. It is too much to handle on your own so I would love to have some colleagues join so we can cover more of the workshops and presentations.
Will you join me in Berlin next year? November 27-29, 2019.
Patti Shank gave a fantastic and informative workshop on Managing Memory for Deep Learning. Slides are here. There are three types of memory; sensory, working and long-term memory.
She presented a top 10 of skills needed in 2020 (compared with 2015) including complex problem solving, critical thinking and creativity.
Ben Williamson, senior researcher at Edinburgh University gave his perspectives based on his new book; Big Data in Education: The digital future of learning, policy and practice. He presented 8 datalessons. Two are presented below.
Patti Shank - Tactics that help memory and learning
Patti Shank gave a fantastic and informative workshop on Managing Memory for Deep Learning. Slides are here. There are three types of memory; sensory, working and long-term memory.
We get better learning and performance outcomes when using tactics that work with memory. Her latest book on memory has 21 strategies to design learning. Take the three types of memory into consideration. Design so what is important is noticed by the senses. Don’t overload working memory. Intentionally build accurate schema for long-term memory.
We should write for clarity. Test the readability of what we write. Use shorter, more familiar words. Reduce sentence length. Manage memory by checking and fixing understanding.
There are tools we can use to check how ‘readable’ our text is. Such as the tool in Word. Or the Flesch readability formula. A score between 60 and 70 is considered standard to fairly easy. For standard communication we should write for Grade 8 level. Are we dumbing things down? We have to read so much every day. Being concise and using familiar words will help you communicate your message. And it can be read more quickly.
How does this help memory? By reducing the mental effort needed to learn from new information.
This was a really excellent session. I will use what I learned from now on, on a daily basis. Thank you Patti!
Getting to the heart of education
Esther Wojciki gave a superb introduction to why and how we should teach. Her journalism program at Palo Alto High School is regarded as the best in the United States and has more than 600 students. If you want to see a good example of how to teach what is relevant, with engaged students and real work projects, check out what she is doing.
Students produce weekly and monthly newspapers and magazines that are all self-created, and of a high level. Her 2015 book ‘Moonshots in Education’ explores successes in digital and online learning. It was very inspiring
Students produce weekly and monthly newspapers and magazines that are all self-created, and of a high level. Her 2015 book ‘Moonshots in Education’ explores successes in digital and online learning. It was very inspiring
She presented a top 10 of skills needed in 2020 (compared with 2015) including complex problem solving, critical thinking and creativity.
We do not need people who think like computers. We need people with social and emotional skills including empathy, compassion, kindness, respect and creativity.
Anders Flodström, Edu director at European Institute of Innovation and Technology European Institute of Innovation and Technology stressed the importance of us educating innovators. 96% of the Chief Academic Officers of schools say they educate students for work but only 11% of industry employers believe that is the case.
Ben Williamson, senior researcher at Edinburgh University gave his perspectives based on his new book; Big Data in Education: The digital future of learning, policy and practice. He presented 8 datalessons. Two are presented below.
#datalessons 2
Students, the media and public have ideas, perceptions and feelings about technology that are different to companies’ aspirations – claims of social responsibility compete with feelings of ‘creepiness’ about commercial tracking & concern about private sector influence in public education.
#datalessons 5
Secrecy and lack of transparency in use of data analytics & algorithms do not win trust in the education sector – teacher unions and education press may reject AI and algorithmic assistance if not believed to be transparent, fair or context sensitive.
#datalessons 7
‘Reading’ the brain for signals, or seeking to ‘write back’ into the plastic learning brain, raises huge ethical and human rights challenges – ‘brain leaks’, neural security, cognitive freedom, neural modification, and thoughts and images captured as ‘brain data’ as targets of future investigations.
The future of education and technology - Debate
Does machine learning lead to less critical thinking? Will teaching fundamentals stay the same but be augmented by technology? Are we losing control of formal education as we move toward informal learning? Complete Video of Key Note 1:31:36
Geoff Mulgan of the innovation foundation NESTA told us to act now to prepare for the world for jobs of tomorrow. Be sceptical of casual, lazy futurology that does not use data.
Skills identified as most likely to see growing demand include judgement and decision making, fluency of ideas, active learning, systems evaluation, originality and learning strategies. At number one was animation, followed by design and process engineering, employee development, clinical research and teaching. At the bottom of the list was accounting, payroll, office administration and HR management.
Labour intensive jobs such as artists, window dressers, photographers, tailors, florist, restaurant and retail managers, sales supervisors and chefs are most similar to the job skills we’ll need in the future.
Future skills will require collective intelligence and the emergence of companies like Duo lingo. Assembling intelligence, linking observations, models and predictions will lead to creative innovations. Google Maps is an example where several companies were bought, connected together, and then the rest of the world provided the content through intelligence assembly. Nesta is making a virtual map for jobs and employees to help us all navigate through it to our future careers.
Bryan Caplan, author of ‘Locked-in; Why fixing education is so hard’ gave a more cynical take on the (American) college system. Why had online education not already won (it’s cheaper, more convenient, higher quality instruction as we learn from the best)?
Students jump through hoops, sharing conformity and we produce docile sheep. Getting a university is only a passport to the real training that happens on the job. We should focus on learning how to learn which is extremely specific. You don’t become a pilot by going to critical thinking classes. Employers should pay you for what you know now, now what you knew then.
Anita Schjøll Brede, founder of www.iris.ai asked us whether machines can love? She got her first of many implanted chips several years ago. [Oh no, half way to cyborg! An augmented human].
When machines can learn it will change how humans learn, and change what we need to learn. We can’t say AI and machine learning works like the human brain, because we don’t know how the human brain actually works.
Iris.ai is developing AI that can read thousands of research papers on a given subject and synthesise it into a literature review on any subject. Through hypothesis extraction from papers, argument mining AI can build a truth tree document (easier in harder than softer sciences). Succeeding in this goal will mean a radical change how we do research and much more knowledge to understand. The human role will be to interpret and apply.
But our brains are biased. Very biased! As outlined by this fantastic synthesis of all of Wikipeida’s Cognitive Biases presented in this awesome overview.
We need to teach the following skills;
1 - Critical Thinking. Understanding and critiquing sources is of great importance. Who built the machine and what is their purpose?
2 – Complex problem solving skills are essential. When machines make the choices we need to ask why and how they are doing this?
3 – Creativity – mix and match created parts and make it your own.
4 – Empathy is essential. Machines are tools. Will we build evil machines, or evil human beings?
As the Buda said, ‘Believe no one’ (I’m not sure whether I should believe that or not?).
And what happens when machines become more empathetic to other machines? Humans are more and more intertwined with technology. Will some machines favour humans that are more like machines (those humans with embedded chips?). And how can we avoid building racism into our algorithms? This was an interesting debate that raised many questions.
What are we doing to Generation Z?
A local teacher from an international school in Berlin had invited six of his International students studying Abitur/IB to talk about their lives studying with technology.
A local teacher from an international school in Berlin had invited six of his International students studying Abitur/IB to talk about their lives studying with technology.
Gen Z/millennials/iGen are born in the 90’s. Growing up in highly diverse technology, they may be referred to as ‘multi, multi-taskers’ with all the world’s information right there at the fingertips. How are they using technology in their life and to help them study?
I was quite shocked to see the pressure these students are under 24/7. Woken by their phones, they are online the whole day, buying power packs to keep their devices charged. No phone means not being able to find your classroom. Communicating with teaches via WhatsApp and project members. Books as pdfs, reading online summaries instead of books, intuitively feeling when a site is a reliable source. They use Google Drive for all documents and know they are being followed by the giant algorithm, but don’t mind because they are not doing anything wrong.
Boredom and daydreaming are an important process in the brain for synthesising new information. But this generation are never bored since there is no down time. But it’s so exhausting, it’s a job that never ends, the phone tears them out of bed. And there are so many distractions such as NetFlix. There are no bounds, it is just unlimited. Some young teachers say, ‘Don’t even take notes, I’ll send it to you’. But reading from your phone is not the same as reading from a book.
There are so many screens on the whole day. Although they accept humans can’t multi task they are in a constant state of task switching. To really focus go to the library, off line, and lock all your technology in a box, stay away from Instagram, FaceBook and NetFlix.
There is a lack of sleep and general health with enormous mental pressure to be ‘on’ the whole time. And limited time to develop empathy and social skills.
‘We expect people to be on the same level of machines, to always give everything, to always function, not to miss school. But we are not machines.’
Retention of what is learned in the last period is almost zero as it is dumped out after the exam.
Future employers should provide structure and freedom and value their strengths.
This was one of the more intense moments I’ve experienced for quite a while. Six highly educated, eloquent young-adults, sharing the incredible pressure they are under in a public forum. They spoke honestly and openly. This generation will live another 80 years and will be running the world when we are retired.
It might sound a little dramatic when Jean Twenge asked in her 2017 Atlantic Article, Has the smartphone destroyed a generation? Listening to these students, it made me seriously question not so much the technology, but society’s acceptance of this status quo. Do we really consider this to be normal or acceptable behaviour? No one has designed this system. It has evolved based on what technology makes possible.
But I am genuinely concerned for the long-term physical and mental health of this generation of ‘always on’ students. This was a real insight into the world of Gen Z, and I will raise this subject with my teaching colleagues as something that needs to be taken much more seriously.
But I am genuinely concerned for the long-term physical and mental health of this generation of ‘always on’ students. This was a real insight into the world of Gen Z, and I will raise this subject with my teaching colleagues as something that needs to be taken much more seriously.
Optimising Mobile Learning Experiences
I presented with Davina Beegoo-Price and Louise Olney from the Open University UK. Our session was called ‘Optimising Mobile Experiences’. The OU presented the mobile app they are currently developing for their distance learning for students who never meet each other in person. They have 180,000 active users (students/staff) in the Virtual Learning Environment. They have established 8 profiles of users. This shows the diverse needs of the different groups and the challenges to make the right app
I presented on distractions in the class and how we can develop strategies for metacognition and self-regulation. During the learning café format we had over 50 participants attend, about one third of them teachers, the rest were app developers or learning experts. My slides are here.
This model plots Academic ad non-academic use inside and outside the classroom.
The attendees suggested strategies to develop metacognition and self-regulation. They suggested apps to monitor screen time, agreeing a framework with students, gamification to incentive focused learning, focus on real-time meetings, A/B test with/without phones in the classroom, notifications when you’ve reached a certain limit (habit forming goals), notifications to regain classroom focus, embrace and think about mobile earlier.
There was a very positive response to the discussion and good to get feedback from the diverse group of international participants. Managing digital distractions will be an ongoing challenge for the future.
There was a very positive response to the discussion and good to get feedback from the diverse group of international participants. Managing digital distractions will be an ongoing challenge for the future.
Collecting better data to analyse learning
At a pre-conference workshop, Will Thalheimer showed how to collect better data from learner feedback. The workshop goal was to show how to write effective learner-survey questions to capture useful data. He has developed The Learning-Transfer Evaluation Model. Some points we can improve on when collecting learner data:
<>·····Learning Landscape Model (1:50 to 6:50) examines how and where learning takes place and then relates this to how, when, where and what we evaluate from the learning results. Humans forget information (learning and forgetting curves). Three biases in measuring learning are; only measuring at the end of learning, only in the learning context and only with knowledge questions. (I’m guilty of all three!).
Learners may engage, pay attention, actively participate, like the learning event and say they’ve experienced effective learning. But this does not mean learning has taken place.
Video Has Graduated
Karsten Wolf of University Bremen has researched Video Pedagogy for the last ten years. More than 1 million explanatory videos are uploaded to online platforms every day (many of them on YouTube). There are benefits of student generated video. The learning effect is greater for students when they produce it rather than just view it increasing deeper learning, explaining it in their own words and by answering relevant questions.
He shared a schedule for a 90 minute video production in class. 10 mins brainstorming, pitching and deciding ideas. 10 mins to discuss topic. 10 mins create ideas for explanation. 20 mins create collaborative storyboard. 10 mins to build props and visualisations, models. 20 mins to record and produce video. 10 mins post production and viewing.
Set realistic expectations regarding quality of finished product (it’s not Hollywood). It’s to be shown in class or to parents. However, visual communication is now considered very important. Every teacher (and student) needs to know how to do this.
Karsten Wolf of University Bremen has researched Video Pedagogy for the last ten years. More than 1 million explanatory videos are uploaded to online platforms every day (many of them on YouTube). There are benefits of student generated video. The learning effect is greater for students when they produce it rather than just view it increasing deeper learning, explaining it in their own words and by answering relevant questions.
He shared a schedule for a 90 minute video production in class. 10 mins brainstorming, pitching and deciding ideas. 10 mins to discuss topic. 10 mins create ideas for explanation. 20 mins create collaborative storyboard. 10 mins to build props and visualisations, models. 20 mins to record and produce video. 10 mins post production and viewing.
Set realistic expectations regarding quality of finished product (it’s not Hollywood). It’s to be shown in class or to parents. However, visual communication is now considered very important. Every teacher (and student) needs to know how to do this.
Algorithm, AI and Personalisation
In the workshop I attended, Davor Orlic of Knowledge 4 All is setting up a set of mega algorithms to connect and find all knowledge on earth. There is an ocean of content, they are building a NetFlix for education in the knowledge economy.
Joel Johnston of Let Me Learn showed how they have developed online personal coaches which help students in primary and high school. Identifying learning patterns of users. The tool can be used to develop your own learning strategies
Albert Vlaardingerbroek and Jacob Poortsraat MBO College Noorderpoort in Groningen showed their programme to develop the role of the teacher in online classes. They examined what interventions should be made based on students’ online behaviour. Are we autonomous learners or being managed?
Kelly Marten of the University of Antwerp explained the video communication channel they had set up. They started with subjects students found most difficult; Accounting, maths, stats and economics. Professors interested in blended learning follow a workshop.
Richard Aldridge of Stenden University shared insights from his almost 50 years in e learning. He explained progression through different types of studios and recording set-ups in classrooms and lecture halls. He has overcome various challenges from sound and professors who are too mobile.
Some companies to look into further
Proctorio, an online learning integrity platform. I hope to run a pilot with them in January for some students who need to sit exams at another location.
MyVirtualClassroom who are focusing on developing a digital (video) teaching didactic for the online classrooms they facilitate
GoReact who provide a feedback format for student videos. This is to practice certain skills (e.g., presenting, or conducting an orchestra). The assessor and peers can then give time-stamped feedback based on a rubric. The evaluation of competences via video is arriving!
iversity – video based learning courses including MOOCs, Professional Development and short micro-learning.
Some books that were mentioned and may be of interest
Muller, J.Z. (2018). The Tyranny of Metrics, Jerry Z. Muller (mentioned in three presentations!)
Shank, P. (2018). Manage Memory for Deeper Learning: 21 evidence-based and easy-to-apply tactics that support memory while learning and beyond.
Williamson, B. (2018). Big Data in Education: The digital future of learning, policy and practice
Wojciki, E. (2015). Moonshots in Education: Blended Learning in the Classroom
And a list of recommended reading on memory and learning from Patti Shank.