t

EIT Digital Academy: OnLine

AF/Rome/2011019

Who is she? Of equal importance to Marie Curie

2

Super Artificial Intelligence

Time

Biological IQ

Artificial IQ more and faster

Super artificial IQsmarter

The Intelligence lies in the data not in the algorithms

3

The Perception of a University163621 000 students$ 37 billion

Bologna(1200)Humboldt(1800)US Researchor Ivy League (1950)

EUA 1000

t

The New ClassroomThe global education market x3 the media market

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

Innovation and Jobs

6

Innovation

DeletedCreated ?

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

DigitalData ScienceBig Data

CoolabilitiesAspergers Syndrome

Competencies

Technical

Digital(generic)

I&E(generic)

Delivery:MOOPsMOOCsSPOCsMobileBlendedClassroom

First pan-European Quality SystemBased on a Set of unique OverarchingLearning OutcomesEIT Label

Master SchoolDoctoral SchoolProfessional School

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 USEIT Digital X + Coursera Platforms

10

EIT Digital Academy – the Map

OnlinePlatforms

EIT Label Degrees and Certificates

I&E (Generic) Skills

Development

MSLCampus

MSL Campus

DSLCampus PSL

F2F

MOOC

500

SPOC

250 5000(500)

10000(5000)

Alumni (500)

Partner Universities (20) and Institutes (5)

50000250

Context: Overview and Focus within EIT Digital Academy

Context: Supporting EIT Digital Academy Goals

Master School•Create T-shaped engineers•Create a world renowned EIT Digital Master School brandDoctoral 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 brandEIT 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:

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Online Formats – a TutorialHierarchy

Nuggets Unit Lesson/Module Course Programme

1 2 3 4 5 6

Unit

Nuggets (Seconds)

Online LMS MOOC/SPOC Classroom

Units (Minutes)

Module

SPOCMOOC 1 MOOC 2 Capstonr

Modules

Course

Over 300 NuggetsDesign SoftwareLMS: Sakai or EIT Digital X

2 Programmes IoT and DSEach Programme 30 ECTS or 6 Courses1 Course or 4 MOOCsA Semester is 24 MOOCsCoursera or EIT Digital

Goal: Transform to BlendedFrom 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

1st year 2nd year

EIT Digital Blended Master Programme Concept

Online programmes:• Internet of Things

through Embedded Systems

• Data Science in Action

Admission requirements for on campus programme

Online Coursera Certificates for:

Around 40 Coursera MOOCs equivalent to 6

on Campus courses

1 I&E Specialization

Exemptions at enrolment based on Exams taken either:

Remote at local university

Proctored (oral exam at student’s home)

At Winter School

Admission requirements,

selection based on:Relevant Bachelor Degree

& Grades (≥60 ECTS)

Quality Bachelor University

English Language Eligibility

I&E motivation

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 SchoolExemptions/ ECTS provided at Winter School when passing required exams

Coursera Certificate I&E Specialization Exam at Winter School Achievements Evaluated

Invitation to Winter SchoolSelection based on admission requirements and achieving all required Coursera Certificates and accomp. Exams.Scholarships/fee waiver cf. MS rules

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

Tasks and Relations in blended Masters for 2017

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

Activity

Online Programmes / Blended Masters

Quality

Development

Marketing & Dissemination

Blended Master Data Science Creative Process

Principles:• Combine content, media, & online techniques• General marketing strategy blended master• Learner centred & Data Driven ApproachBasic 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

Blended Master Data Science Creative Process

Overview steps creative process:1) Creating content

• Director, author2) Composing scenarios

• Didactic experts/instructional designers3) Media production4) Adaptation for marketing strategy5) Site publication, course testing, & Final delivery6) Analysis of interaction data7) Improvement of courses and marketing

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 practice2) 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

Blended Master Data Science Creative ProcessSteps: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

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

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

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

Internet of Things through Embedded SystemsIntroduction IoT (3 courses)

• iMinds-Gent, Gielen, Timmerman - 2IMN15 Internet of Things -5 ECTS

QFM & WCPA (1 course) + QFM Markov Chains (1 course)

• TU/e, Cuijpers, Utwente, Remke - 2IMN25 Quantitative Formal Methods - 5 ECTS

System Validation (4 courses – SPOC capstone)

• TU/e, Groote - 2IMF30 System validation - 5 ECTS

Web Con.,Security , Emb.HW & OS, RT Systems (3 courses)

• Turku-Åbo, Plosila, Ramirez Licona, Halmbacka - 2IMN20 Real time systems – 5 ECTS‐

Advanced Computer Algorithms (4 courses)

• TUB, Juurlink - 2IMA10 Advanced algorithms - 5 ECTS

I&E courses (specialization with 3 courses & capstone)

• KTH, Martin Vendel – 1ZM20 Technology entrepreneurship – 5 ECTS

Online programme:Online equivalents of on-campus courses; 5 technical courses, 1 I&E.

2016

Proposal Data Science in Action (in preparation)Introduction Data Science/Statistical tools for data scientists

• UPM (?) – 2,5 ECTS

Advanced Algorithms (Approx., External Mem., Streaming, Geo.)

• Mark de Berg, TU/e – Advanced Algotihms - 5 ECTS

Recommender Systems

• Paolo Cremonesi, Polimi - - 5 ECTS

Web semantics

• (?) Francoise Baude, UNS - - 2,5 ECTS

Data Mining

• Mykola Pechenizkiy, TU/e - 2? ECTS

Visualisation

• TU/e, UPM (?) – 5 ECTS

Advanced statistics

• Koo Rijpkema, TU/e in cooperation with (maybe UNS, UPM)- - 5 ECTS

I&E courses (specialization with 4 courses) Additions in Digital Transformation (?)

• KTH, Martin Vendel – 1ZM20 Technology entrepreneurship – 5 ECTS, UPM(?)

Online programme:Online equivalents of on-campus courses; >5 technical courses, 1 I&E.

2017

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

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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

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Present Status of IoT and Data Science Programmes

ES16723 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 ScienceTeam is there. Production has commenced. Pilot run in early spring. On the market in the autumn semester 2017Thematic Nanodegree in Autonomous TransportTeam is there, including industrial partners. Programme design in progress.

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