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Blockchains and new educational models v 2.0

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Blockchains and new educational models v 2.0

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The lastest on the OU blockchain experiments and thoughts on the application of this technology in the Higher Educational space. In particular for accreditation, ePortfolios and uber style educational disaggregation.

The lastest on the OU blockchain experiments and thoughts on the application of this technology in the Higher Educational space. In particular for accreditation, ePortfolios and uber style educational disaggregation.

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Blockchains and new educational models v 2.0

  1. 1. Blockchains and New Educational Models Prof. John Domingue (@johndmk) Director, Knowledge Media Institute & Patrina Law, Head of Free Learning The Open University, UKkmi.open.ac.uk blockchain.open.ac.uk
  2. 2. Open University Context
  3. 3. The Open University • Established in 1969 • The UK’s largest university • No qualification barrier to entry • Over 170,000 students registered last year – 22,000 have a disability • More than 2 million students have studied its courses since its foundation. • 117 postgraduate and 325 undergraduate courses • Over 21,000 academic awards annually • 5,000 associate lectures • Role model for many other institutions worldwide © Simon Buckingham Shum 3
  4. 4. 1970s Home Experiment Kits Home Chemistry Kit Home Geology Kit
  5. 5. Sample
  6. 6. E117 Introduction to Sport and Fitness
  7. 7. Major Blockchain and Education Initiatives
  8. 8. Characteristics of Blockchain DApps • Shared database • Multiple writers • Absence of trust • Disintermediation • Transaction interaction • Set rules • Validators • Asset backing http://www.multichain.com/blog/2015/11/avoiding-pointless-blockchain-project/
  9. 9. MSc Certificates on Blockchain http://digitalcurrency.unic.ac.cy/certificates 10
  10. 10. Learning Machine
  11. 11. For example, after taking an examination to demonstrate his or her academic proficiency level, an individual could direct the testing organization to share the test results with one or more third-party evaluating organizations. With this diversification and the changes it brings about, different evaluating organizations may come to utilize individuals' test results in different ways, each in accordance with its own evaluation methods. http://www.sony.net/SonyInfo/News/Press/201602/16-0222E/index.html
  12. 12. Blockchain and Education at the OU
  13. 13. Student Controlled Education
  14. 14. openbadges.org
  15. 15. OpenLearn Badges on the blockchain
  16. 16. Smart Contract Badge Services • Job Hunting • Promotion • Mandatory CPD training • Networking • Reconfiguration • Course recommendations
  17. 17. Demos of movies available at: http://blockchain.open.ac.uk/ Peer Reputation and Badging
  18. 18. Reputation Contract Functions: Storage: sendReputation getPersonBalance() getReputationAttribute attribs[address = > Attrib] Attrib { uint balanceOf; mapping(string => uint); string[] attribStrings } Reputation Attribute token Balances Reputation Smart Contract Tokens left to assign My Reputation Peer Reputation Page Kevin’s Reputation View Communication: 14 Collaboration: 06 Organisation: 12 Ethics: 05 Problem Solving: 10 Engagement: 04 your Ethereum address password to private key Signing this transaction will transfer stated Reputation Tokens + ETH gas payment from your account. Estimated gas cost is 0.02 ETH. Maximum gas cost is set to 0.05 ETH Transfer Reputation Tokens Left: 57 number of tokens to transfer Assign Reputation My Reputation Peer Reputation Page Michelle’s Reputation View Communication: 06 Collaboration: 02 Organisation: 10 Ethics: 12 Problem Solving: 08 Engagement: 16 your Ethereum address password to private key Signing this transaction will transfer stated Reputation Tokens + ETH gas payment from your account. Estimated gas cost is 0.02 ETH. Maximum gas cost is set to 0.05 ETH Transfer Reputation Tokens Left: 68 number of tokens to transfer Assign Reputation Signed TX Reputation Attribute token Balances Tokens left to assign Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  19. 19. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  20. 20. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  21. 21. Block no: 45566778 Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  22. 22. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  23. 23. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  24. 24. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  25. 25. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  26. 26. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  27. 27. Michelle transfers 4 Reputation tokens for ‘Organisation’ to Kevin
  28. 28. Student ePortfolio Explorer
  29. 29. Student ePortfolio Explorer
  30. 30. Rise of the Uber University
  31. 31. Uber-style Education (1/2)
  32. 32. Uber-style Education (2/2)
  33. 33. Collaborations Copyright http://dilbert.com/
  34. 34. Startups in the CV/Accreditation Space
  35. 35. Global Higher and Further Education Blockchain
  36. 36. Future/Other Work and Summary Copyright http://dilbert.com/
  37. 37. Linking to Linked Open Data
  38. 38. Semantic Indexing of Blockchains • Related data spread across blocks • No high-level semantics for contracts • Need – An index onto blockchain – To connect blockchain data to Linked Data – To allow richer contract semantics • Linked Data index for blockchain
  39. 39. BLONDiE Contract Ethereum Transaction Bitcoin Transaction Output Bitcoin Transaction Input Bitcoin Transaction hasBitcoin Transaction Output hasBitcoin Transaction Input Message Call Ethereum Transaction Contract Creation Ethereum Transaction Ethereum Transaction has Ethereum Transaction has Ethereum Payload hasOmmer Ethereum Ommer has Ethereum Blockheader hasPayload Ethereum Blockheader Normal Ethereum Transaction has Bitcoin Blockheader has Bitcoin Payload hasTransaction has Blockheader Bitcoin Blockheader https://github.com/hedugaro/Blondie
  40. 40. Learning Analytics: OU Analyse (1/3)
  41. 41. Learning Analytics: OU Analyse (2/3)
  42. 42. Learning Analytics: OU Analyse (3/3)
  43. 43. Open Anonymised Learning Analytics Dataset
  44. 44. Learning Analytics on the Blockchain • Learner-controlled learning analytics data – Provenance assured by blockchain – Access permitted/denied by audience/purpose • Zero-knowledge proofs over data – Ask questions without accessing data – Provably correct answers
  45. 45. Scientific Knowledge on DLsBlockchain April 2017 Figure 1: Research Publications in Blockchain
  46. 46. Summary: Blockchain Benefits • Inbuilt identity management • Data controlled/owned by students rather than any single institution • Increases transparency • Reduces risk of fraud • Enables collaboration/interoperability • Permits disintermediation – Badge issuing based on badge collection • Lowering of process costs – Lowers entry barriers to education market – ‘university of one’
  47. 47. Acknowledgements • KMi@OU Implementation Team – Michelle Bachler – Kevin Quick – Allan Third – Chris Valentine – Umar Mir
  48. 48. blockchain.open.ac.uk

Editor's Notes

  • Over 300,000 engage with the OU around Frozen Planet – nice e.g. of ‘engagement funnel’

    309, 530 visitors to OpenLearn,
    204,000 requests for the Frozen Planet poster
    10,889 visitors to Frozen Planet Interactive on OpenLearn
    614 students on first presentation (Dec 2011) of the new short course, The Frozen Planet , 12% more than predicted
    10 point course, costs £170 and includes specially filmed material
  • “Anybody can use the registered content provided that they meet the terms of the policy. The right to do so is transferred automatically through the smart contract. Payments are delivered instantly and automatically using smart contracts and digital currency. An open platform facilitates infinite potential roles, applications and business models”

    The blue arrows show the smart contract allowing a student access to certain course materials.
    The red arrows show the monetary transactions with Ether coming out from the student and being paid automatically in predefined percentages to the admin team, the Content Providers and the Learning Delivery people.

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