The future of tech and education; will we still need teachers?

www.radams.co.uk @dickyadamswww.radams.co.uk richard@radams.co.ukSlidesharewww.radams.co.uk @dickyadamswww.radams.co.uk richard@radams.co.ukSlideshare

Will we still need teachers?A Provocation by

Richard Adams

http://www.radams.co.uk/

http://www.twitter.com/dickyadams

mailto:richard@radams.co.uk

http://www.slideshare.net/dickyadams

www.radams.co.uk @dickyadamswww.radams.co.uk richard@radams.co.ukSlideshare

Twenty+ years in digital

Coder

Product Developmen

t Director

Creative Director

Digital Architect/ Strategist

Programme Manager

Visiting Senior Fellow at University of Lincoln Recently Senior Academic Program Manager at Microsoft

Studios Worked with Marc Lewis to create and be initial Principal of

School of Communication Arts 2.0 www.schoolcommunicationarts.com

Birkbeck College - Taught Digital Creativity to MA/MSc business students

Former Visiting professor of Digital at Salford University Founding Head of Digital Arts at Thames Valley University

Taught, coding, gameplay design, critical theory, digital art and more

External examiner at two universities Qualified and experienced school teacher of Art and Music Qualified trainer/assessor in the workplace

http://www.schoolcommunicationarts.com/

RICHARD F ADAMS ON KINDLE OR WWW.RADAMS.CO.UK OR @DICKYADAMS

Church Industry Big State

Centralization/

Decentralization

Our education system reflects our society

Data

Big Analytics The

second economy

– machine

to machine

The new economic

s of money

The social

economy

Mobile economy

Security

Behavioural

Science

HORSEPOWER TO BRAINPOWER

THE 8 PILLARS OF THE NEW ECONOMY

The 1000lb Gorilla

Big Data & Behavioural

Science

http://www.johnnybees.com/wp-content/uploads/2012/08/gorilla-inefficiency.jpg

(This is being trialled in Korea) http://cdn3.dogomedia.com/pictures/6434/content/robot_teacher.jpg?1294953723

Predictive tech

Photo by Alamy http://www.theguardian.com/teacher-network/teacher-blog/2013/jun/19/technology-future-education-cloud-social-learning

http://www.theguardian.com/teacher-network/teacher-blog/2013/jun/19/technology-future-education-cloud-social-learning

Multimodal/ Blended learning

Short courses online Deeper online

engagement – leverage of existing and

private networks

Collaborative learning – built in

course development

New forms of qualifications

externally delivered

In-partner delivery

New tech for delivery

Lectures/ worskhops

Hangout tutorials

Free, Freemium, Sponsored and

Paid

Iterative

Here's what I think (And I am unlikely to be around to collect on bets)

In 50 years time….

A true and deep blend of online and real world instruction delivered via tech and real

teachers, still teaching

Image analysis (Art), automated text and voice

analysis of presentations and essays delivered virtually, virtual personal exchange

environments for presentations, no language barriers, marking and grading done by machine

We will have full datasets on each pupil and adult able to suggest what we should be

learning and pushing us down the next chapter of our learning

story, following each person through life

In 100 years time schools exist solely as places for human socialisation with people as moderators… the role of

teachers changing/diminishingWhat you

need to learn will be

predicted and delivered,

organised and setup

automatically throughout

your life

Education primarily

delivered and accessed from wherever the

student is based.

Your actual and likely

behaviour is understood

and predicted

Schools become social

spaces for human to

human interaction

Kids go there to learn to

validate, mix and get on

with people.

Merging of schools and

Uni’s as learning is

totally lifelong and

embedded for social utility

reasons

Kids will need counsellors, guides and

mentors

“Schools” could be

anywhere in any institution

Here's what I think (2) (And I will definitely not be around to collect on bets)

Thank You

Appendices

Probability of jobs disappearing 1. Telemarketer Probability of Automation: 99%

2. Loan OfficersProbability of Automation: 98%

3. ReceptionistProbability of Automation: 96%

4. Paralegals and Information ClerksProbability of Automation: 94%

5. Bike RepairerProbability of Automation: 94%

6. Retail SalespersonProbability of Automation: 92%

7. Automotive Body RepairerProbability of Automation: 91%

8. Real Estate AppraisersProbability of Automation: 90%

9. Bakers

Probability of Automation: 89% 10. Construction LaborersProbability of Automation: 88%

11. Carpet InstallersProbability of Automation: 87%

12. Subway and Streetcar OperatorsProbability of Automation: 86%

13. Power Plant OperatorsProbability of Automation: 85%

14. Tailors, Dressmakers, and Customer ServersProbability of Automation: 84%

15. Brickmasons, Blockmasons, Stonemasons, and Tile and Marble Setters Probability of Automation: 83%

http://www.military.com/veteran-jobs/career-advice/job-hunting/top-15-jobs-threatened-by-technology.html

So, how the bloody hell does Big Data work?Take a pot of data, mix it with an understanding of behaviour, stir in an ontology and leave it to cook or generate probabilities.

You have all these ingredients and you can make many pizzas from different choices and mixes.

http://image.shutterstock.com/display_pic_with_logo/1436666/134376011/stock-vector-vector-color-icon-set-of-pizza-ingredients-134376011.jpg

You can analyse things like frequency of use and popularity, seasonality of ingredients and so on

http://qph.is.quoracdn.net/main-qimg-270d61f882e0a112b5f5993761035b5b?convert_to_webp=true

You can then look at delivery, postcodes, social factors, times, calendar events

You can then create an ontology that has all the ingredients in and all the other factors, variables, weightings and so on

As your dataset grows over time you can start using techniques such as Bayesian probability to make accurate forecasts that given a set of circumstances it is highly likely that X will happen. This of course can be automated…

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