1. 1. European Data Science Academy John Domingue Knowledge Media Institute The Open University, UK & STI International edsa-project.eu
2. 2. Agenda The Context and Problem Approach Curricula and Resources Delivery Channels Data Aspects Learning Analytics Summary
3. 3. THE CONTEXT AND PROBLEM
4. 4. Big Data is the foundation and fuel of a new economy. Neelie Kroes Vice-president and digital agenda commissioner, October 2014 206 billion to the European economy by 2020
5. 5. Data Science Skills Gap (just in the UK) Tenfold increase in Big Data staff demand over last 5 years 41% increase in the past year 77% of Big Data roles were hard-to-fill 160% increase in demand for Big Data specialists 2013-2020 to 346,000 new jobs
6. 6. MACROECONOM IC Source: IDC estimates on Eurostat Labour Force by occupation and NACE II industry code, 2013 2013 5.77 Million 2014 6.10 Million 3% of total EU employment Total Number of Data Workers in the EU28 (2013 vs. 2014)
7. 7. MACROECONOM IC The Occupational Mix of Data Workers, total EU (2013) Source: IDC estimates on Eurostat Labour Force by occupation and NACE II industry code, 2013 9% 23% 28% 40% Clerical support workers Managers Technicians and associate professionals Professionals 0% 10% 20% 30% 40% 50% Where can we find Data Workers?
8. 8. To add value to data, data workers need an important mix of skills Analytical core skills Technical core skills Domain and business knowledge Soft skills Competencies
9. 9. APPROACH
10. 10. Overview 1. Curricula and courseware Modular, media-rich, available in several languages Covering a mix of core, domain-specific, and technology-specific topics Informed by demand analysis (surveys and data monitoring) 2. Training Webinar series, video lectures, annual summer school, on demand professional training Informed by student feedback and learning analytics 3. Community engagement Highly visible eLearning channels: iTunes U, FutureLearn, videolectures.net Collaborate with relevant stakeholders to align programs, organize joint training, collect feedback Informed by social media monitoring
11. 11. Self Regulated Learning
12. 12. Flipped Classroom Paradigm
13. 13. Initial Version of Module Final Module: eBook & Course Webinar Final Recording Webinar First Recording Collection of Module Materials Slides First Version Slides Final Version Stakeholder Communities Industrial Advisory Board Demand Analysis Reflection Module Dissemination Online & F2F LearningAnalytics Curricula EDSA Analytics Dashboard Reconfiguring & Repurposing Learners Learning Delivery End to End approach
14. 14. CURRICULA AND RESOURCES
15. 15. Initial EDSA Curriculum
16. 16. Rich Interactive OERs
17. 17. DELIVERY CHANNELS
18. 18. VideoLectures.NET Content Events : 950 Authors: 13, 000 Lectures: 17, 600 Videos: 20, 000 Organisations: 7000 Categories : 600 Comments: 8500 Website Video views: 6.5 million Page views: 29 million Signed in users: 25, 000 Average time: 36 min Attachments: 620, 000 Files: 1,5 million 8 servers New Visitor: 60.83% Licenses: Creative Commons Users Top countries: United States, India, Slovenia, UK, Germany, China, Canada Tutorials: 350 Keynote: 800 Interviews:250
19. 19. iTunes U
20. 20. OU iTunes U Stats Open University on iTunes U was launched on 3rd June 2008 Now 58 iTunes U Courses 68,138,000 downloads Over 9,015,700 visitors downloaded files Currently averaging 87,500 downloads a week 449 collections containing 3,485 tracks (1,638 audio, 1,847 video) 423 OpenLearn study units as eBooks (ePub), representing over 5,000 hours of study Currently delivering an average of 0.3 TB of data a week
21. 21. Mooc Illustration: Adam Simpson MOOCs
22. 22. Example MOOCs
23. 23. PAGE # Over 1,800,000 FutureLearn sign-ups Over 2,200,000 course sign-ups PROGRESS SINCE LAUNCH In just over a year, FutureLearn has built a large userbase
24. 24. Channels
25. 25. DATA ASPECTS
26. 26. EDSA Dashboards Jobs and skills Interviews Advisory board Learning analytics Available courses
27. 27. Monitoring Engagement
28. 28. Monitoring Engagement (2)
29. 29. Video Lecture Interactions
30. 30. LEARNING ANALYTICS
31. 31. Important VLE activities XXX1: Forum (F), Subpage (S), Resource (R), OU_content (O), No activity (N) Possible activities each week are: F, FS, N, O, OF, OFS, OR, ORF, ORFS, ORS, OS, R, RF, RFS, RS, S FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
32. 32. Start FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS Pass Fail No submit TMA-1time VLE opens Start Activity space FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
33. 33. FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS Start FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS Pass Fail No submit TMA-1time VLE opens Start VLE trail: successful student FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
34. 34. FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS Start FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS Pass Fail No submit TMA-1time VLE opens Start VLE trail: student who did not submit
35. 35. All VLE Paths for a Module time TMA1 VLE start
36. 36. Summary European Data Science Academy Demand Analysis Data mining of job websites Surveys Questionnaires Data Science Curricula Rich interactive learning materials Engagement monitoring Learning Analytics