Keynote presentation OOFHEC2016: Anders flodström
Transcript of Keynote presentation OOFHEC2016: Anders flodström
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EIT Digital Academy: OnLine
AF/Rome/2011019
Who is she? Of equal importance to Marie Curie
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Super Artificial Intelligence
Time
Biological IQ
Artificial IQ more and faster
Super artificial IQsmarter
The Intelligence lies in the data not in the algorithms
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The Perception of a University163621 000 students$ 37 billion
Bologna(1200)Humboldt(1800)US Researchor Ivy League (1950)
EUA 1000
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The New ClassroomThe global education market x3 the media market
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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
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Innovation and Jobs
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Innovation
DeletedCreated ?
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Education - Matching People and Jobs
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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
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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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