EIT Digital Academy: Online

1. t
EIT Digital Academy:
OnLine
AF/Rome/2011019
Who is she? Of equal importance to Marie Curie

2. 2
Super Artificial Intelligence
Time
Biological IQ
Artificial IQ more and faster
Super artificial IQ
smarter
The Intelligence lies
in the data not in the
algorithms

3. 3
The Perception of a University
1636
21 000 students
$ 37 billion
Bologna
(1200)
Humboldt
(1800)
US Research
or Ivy League
(1950)
EUA 1000

4. t
The New Classroom
The global education market x3 the media market

5. 5
William Bamoul – potential Nobel
Prize Laureate in Economics
• Productivity
• Healthcare, Education, Transport and Construction
(Building)
• Full or Zero Marginal Cost
• Self and Automated Diagnosis
• Online Education
• Autonomous cars
• IKEA Robotics

6. 6
Innovation and Jobs
6
Innovation
DeletedCreated ?

7. 7
Education - Matching People and
Jobs
7
It is not about finding a needle in hay-stack? It is about
matching a stray in one hay-stack with its mate in another and
to pair them through education.
People and People
Competencies
Jobs and Job Profiles
Digital
Data Science
Big Data
Coolabilities
Aspergers Syndrome

8. Competencies
Technical
Digital
(generic)
I&E
(generic)
Delivery:
MOOPs
MOOCs
SPOCs
Mobile
Blended
Classroom
First pan-European Quality System
Based on a Set of unique Overarching
Learning Outcomes
EIT Label
Master School
Doctoral School
Professional School

9. Focussed Sustainable Online Education
Infrastructure to move Digital
Transformation in Europe
• 3 MOOPs (7)
• 50 MOOCs (100)
• 90 ECTS (210)
• 3 Semesters (8)
EIT Digital + University Partners in Europe and US
EIT Digital X + Coursera Platforms

10. 10
EIT Digital Academy – the Map
Online
Platforms
EIT Label
Degrees and
Certificates
I&E (Generic)
Skills
Development
MSL
Campus
MSL
Campus
DSL
Campus PSL
F2F
MOOC
500
SPOC
250
5000
(500)
10000
(5000)
Alumni (500)
Partner Universities (20) and Institutes (5)
50000
250

11. Context: Overview and Focus
within EIT Digital Academy

12. Context: Supporting EIT Digital Academy Goals
Master School
• Create T-shaped engineers
• Create a world renowned EIT Digital
Master School brand
Doctoral School
• Create digital technology leaders
with deep technical expertise
• Create world renowned EIT Digital
Doctoral School brand
Professional School
• Raise the competence level of
Europe’s professionals
• Create a world renowned
Professional School brand
EIT generic: X-KIC
• Stimulate MOOC creation between
EIT Digital and other KICs: EIT Health,
EIT Raw Materials, EIT InnoEnergy, EIT
Climate KIC.
• Offer excellent online
support for all KICs
• Support EIT Digital Academy and EIT (X-KIC) education in general at
key digital technological areas and I&E:

13. 13
Online Formats – a Tutorial
Hierarchy
Nuggets Unit Lesson/Module Course Programme
1 2 3 4 5 6
Unit
Nuggets (Seconds)
Online LMS
MOOC/SPO
C
Classroom
Units (Minutes)
Module
SPOCMOOC 1 MOOC 2 Capstonr
Modules
Course
Over 300 Nuggets
Design Software
LMS: Sakai or EIT Digital X
2 Programmes IoT and DS
Each Programme 30 ECTS or 6
Courses
1 Course or 4 MOOCs
A Semester is 24 MOOCs
Coursera or EIT Digital

14. Goal: Transform to Blended
From on-campus Master School programmes to online
The Blended Master
programmes are based on
the on-campus Master
Programmes and involved
partner universities.
Goal: transform the 1st
semester On-Campus
programmes into On-Line
programmes

15. 1st year 2nd year
EIT Digital Blended Master Programme Concept
Online programmes:
• Internet of Things
through Embedded
Systems
• Data Science in Action

16. Admission requirements for on campus programme

17. Admission Process for on Campus Programme
Coursera Certificate Technical Course
Intro
Exam taken
Remote at
local university
Achievements
Evaluated
Coursera Certificate Technical Course
Oral Exam
taken at
student’s home
Achievements
Evaluated
Winter School
Exemptions/
ECTS provided
at Winter
School when
passing
required
exams
Coursera Certificate
I&E Specialization
Exam at
Winter School
Achievements
Evaluated
Invitation to
Winter School
Selection
based on
admission
requirements
and achieving
all required
Coursera
Certificates
and accomp.
Exams.
Scholarships/fee
waiver cf. MS rules

18. Blended Master Programme
Online Programmes
Missions/Goals:
• Improve reputation by demonstrating European
Universities & EIT Digital Education Excellence
• Innovate both Online and blended education
(Coursera and EIT Digital X)
• Improve technical and I&E courses in Master
School dual degree programmes
• Create basis for further cooperation between
European Universities

19. Tasks and Relations in blended Masters for 2017
Marketing &
Dissemination
DevelopmentQuality
Online
Programmes /
Blended
Masters
Activity
Blended Master
programmes
(IoT through)
Embedded
Systems
Creative yet
standardized
approach
With industry
web lectures
EIT Digital
Communication
and Coursera
Data Science (in
Action)
Creative yet
standardized
approach
With industry
web lectures
EIT Digital
Communication
and Coursera

20. Blended Master Data Science
Creative Process
Principles:
• Combine content, media, & online techniques
• General marketing strategy blended master
• Learner centred & Data Driven Approach
Basic components:
• Transformation on campus course to online (ECs)
• Teacher, director, and didactic expert combine
Presentator’s strengths, Story line course(s), &
Online techniques
• Checklists and alignment: LOs, quizzes, content.
• Company web lectures (1 per course) included
demonstrating practical use

21. Blended Master Data Science
Creative Process
Overview steps creative process:
1) Creating content
• Director, author
2) Composing scenarios
• Didactic experts/instructional designers
3) Media production
4) Adaptation for marketing strategy
5) Site publication, course testing, & Final delivery
6) Analysis of interaction data
7) Improvement of courses and marketing

22. Blended Master Data Science
Creative Process
Details in steps creative process:
1) Creating content – creativity first
• Includes artistic Director + Author
• Emphasis on logos, ethos, pathos, and
story line and examples in practice
2) Composing scenarios – loosely planned
• Didactic experts/instructional designers
• Alignment in concepts: learning
outcomes, content, quizzes. Traceability.
• Observe guidelines for LOs, quizzes
• Describe expectations
• Review by committee, improve

23. Blended Master Data Science
Creative Process
Steps:
3) Media production – strict planning till step 6
• Based on scripts/scenarios
• Follows studio guidelines
• Follow slide guidelines
4) Adaptation on general Blended Master
Marketing strategy
• Reputation based, setup measuring
(before/after)
• Include social media
• Quality driven feedback mechanism

24. Blended Master Data Science
Creative Process
Steps:
5) Site publication, course testing, & Final delivery
• LMS implementation first on
update.eitdigital.eu as closed course for
beta testing and future flipped class room
• Review by committee, improve course
• Improve courses based on student
feedback (minimise web lecture changes)
• Author in Coursera environment
• Coursera’s review, small improvements
• The course is launched

25. Blended Master Data Science
Creative Process
Steps:
6) Analysis of interaction data (dashboard)
• Feedback from the platform (learners)
• Video analysis on (frequency) order,
bottle necks, activity peaks, time analysis
• Compare to expectations (See step 2)
• Check traces from peer reviews to quizzes
and web lectures
• Surveys to students to clarify actions
• Peer reviewed assignment analysis
• Differences between courses

26. Blended Master Data Science
Creative Process
Steps:
7) Improvement of courses and marketing
• Improvements based on analysis also
compared to other courses, programs,
and degrees
• Plan long-term
• Improvement of this process

27. Internet of Things through Embedded Systems
• iMinds-Gent, Gielen, Timmerman - 2IMN15 Internet of Things -5 ECTS
Introduction IoT (3 courses)
• TU/e, Cuijpers, Utwente, Remke - 2IMN25 Quantitative Formal Methods - 5 ECTS
QFM & WCPA (1 course) + QFM Markov Chains (1 course)
• TU/e, Groote - 2IMF30 System validation - 5 ECTS
System Validation (4 courses – SPOC capstone)
• Turku-Åbo, Plosila, Ramirez Licona, Halmbacka - 2IMN20 Real‐time systems – 5 ECTS
Web Con.,Security , Emb.HW & OS, RT Systems (3 courses)
• TUB, Juurlink - 2IMA10 Advanced algorithms - 5 ECTS
Advanced Computer Algorithms (4 courses)
• KTH, Martin Vendel – 1ZM20 Technology entrepreneurship – 5 ECTS
I&E courses (specialization with 3 courses & capstone)
Online programme:
Online equivalents of
on-campus courses;
5 technical courses, 1
I&E.
2016

28. Proposal Data Science in Action (in preparation)
•UPM (?) – 2,5 ECTS
Introduction Data Science/Statistical tools for data scientists
•Mark de Berg, TU/e – Advanced Algotihms - 5 ECTS
Advanced Algorithms (Approx., External Mem., Streaming, Geo.)
•Paolo Cremonesi, Polimi - - 5 ECTS
Recommender Systems
•(?) Francoise Baude, UNS - - 2,5 ECTS
Web semantics
•Mykola Pechenizkiy, TU/e - 2? ECTS
Data Mining
•TU/e, UPM (?) – 5 ECTS
Visualisation
•Koo Rijpkema, TU/e in cooperation with (maybe UNS, UPM)- - 5 ECTS
Advanced statistics
•KTH, Martin Vendel – 1ZM20 Technology entrepreneurship – 5 ECTS, UPM(?)
I&E courses (specialization with 4 courses) Additions in Digital Transformation (?)
Online programme:
Online equivalents of
on-campus courses;
>5 technical courses, 1
I&E.
2017

29. Sustainability – MSL Blended Programmes and
Courses
• MSL Blended Programmes (per programme)
• 1 Semester Open Online (MOOC)
• Massive Recruitment
• Certificates – 300€x5000 learners = 1,5 M€
• Admission fees (Winter School)
• 1 Semester Closed Online (SPOC)
• Targeted Recruitment
• Tuition fees – 10k€x1000 learner = 10 M€
• MSL Blended Courses for Campus Education
• Learning enhancement and effectiveness
• Labour market integration
• Learners Time and Cost saving

30. 30
Business Models II – Professional School
• Added value F2F activities of different kind:
• Paid Networks (Social Media)
• Workshops
• Consulting
• Thematic Industrial Programmes (Digital nano Degrees)
• Autonomous Transport
• Digital Cities
• Wellbeing
• Industrial and Public Contracts

31. 31
Present Status of IoT and Data Science
Programmes
ES
16723 learners (increasing day by day and course by course) involved in
any of the ES courses. 49 learners are enrolled in all, and 229 in 75%. All
of these learners have received the appropriate e-mail notification that
they need to register on all courses and got an e-mail address to
register as Master programme applicants.
Learners have already signed up as candidates for the blended IoT
Master programme and from the e-mail registration they seem highly
motivated.
Data Science
Team is there. Production has commenced. Pilot run in early spring. On
the market in the autumn semester 2017
Thematic Nanodegree in Autonomous Transport
Team is there, including industrial partners. Programme design in
progress.

32. eitdigital.eu