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IEEE p1589 'ARLEM' virtual meeting, September 9, 2015

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Special foci: xAPI and Requirements Bazaar

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IEEE p1589 'ARLEM' virtual meeting, September 9, 2015

  1. 1. A Standard for Augmented Reality Learning Experience Models (AR-LEM) Fridolin Wild1), Christine Perey2) 1) The Open University, UK 2) Perey Research and Consulting, CH
  2. 2. Call for Potentially Essential Patents If anyone in this meeting is personally aware of the holder of any patent claims that are potentially essential to implementation of the proposed standard(s) under consideration by this group and that are not already the subject of an Accepted Letter of Assurance:  Either speak up now or  Provide the chair of this group with the identity of the holder(s) of any and all such claims as soon as possible or  Cause an LOA to be submitted
  3. 3. Overview and discussion xAPI integration 3 Fridolin Wild1), Paul Lefrere1), Maurizio Megliola2), Gianlugi De Vito2), Roberto Sanguini3) 1) The Open University, UK 2) Piksel, Italy, 3) AgustaWestland, Italy
  4. 4. “control of one's bodily motions, the capacity to handle objects skillfully, a sense of timing, a clear sense of the goal of a physical action, along with the ability to train responses” -- Gardner, 2011 Bodily-Kinaesthetic Intelligence 4
  5. 5. • World of Repetition (that enabled long cycles of training to be cost-justified) … is gone! • Short-run or personalised production (with advanced machinery and lower demand in physical dexterity) … is emerging! • Learning Design Languages (Laurillard & Ljubojevic, 2011; Fuente Valentín, Pardo, & Degado Kloos, 2011; Mueller, Zimmermann, & Peters, 2010; Koper & Tattersall, 2005; Wild, Moedritscher, & Sigurdarson, 2008) enable modelling of experiences, but fall short of Capturing and codification – Handling hybrid (human-machine) experiences Context: Professional training 5
  6. 6. BLUE COLLAR WORKER EXPERIENCE Enquire Mix Match Optimise ? Traces Need, Problem Activity XML incl. Constraint s Report, Analytics Suggestion, Recommendation Classifiable? Known? Unknown? • Navigational positioning in taxonomy • Discovery support • Selection of existing mixes with ranked search • Authoring of new or modified mixes • Personalised suggestions for improvement of mix / experience tracking Constraints: • e.g. returned tool 15 • e.g. watched video A • e.g. 14/15 in PT session • e.g. 0 FOD problems • e.g. energy < daily limit activities: • e.g. job cards • e.g. tasks • e.g. learning paths • Queries • (Reasoning) Learning by Experience (Wild et al., 2014; Wild et al., 2013)
  7. 7. The eXperience API 7
  8. 8. curl -X POST --data @example.json -H "Content-Type: application/json" -- user 465ea716cebb2476fa0d8eca90c3d4f594e64b51 http://www… API call 8
  9. 9. Example statement 9
  10. 10. Example trace (Helicopter Industry) 10 user cleaned ‘corrosion inhibitors’
  11. 11. Open Source LRS: LearningLocker 11
  12. 12. Analytics: cRunch 12 = t(im) %*% im plot(net, usearrows = TRUE, usecurve = T)
  13. 13. “verbs that refer to physical actions are naturally grounded in representations that encode the temporal flow of events“ -- Roy, 2005:391 Verbs of handling and motion 13
  14. 14. • Specify force dynamics (out of a limited set) • Specify temporal Allen relations (A ends after B, A starts with B, …) • Specify valency (number of arguments, cf. Palmer et al., 2005) • Primitives are ‘movement’, ‘path’, and ‘location’ (Chatterjee, 2001)  Any higher-level composition can be traced back to these atomic relations Verbs of handling and motion 14
  15. 15. General taxonomy across applications (Robertson and MacIntyre, 2009) – ‘Style’ strategies: ‘include’, ‘visible’, ‘find’, ‘label’, ‘recognizable’, ‘focus’, ‘subdue’, ‘visual property’, ‘ghost’, and ‘highlight’ (p.149f) – Communicative goals signified by these styling operations for visual overlays are: ‘show’, ‘property’, ‘state’, ‘location’, ‘reference’, ‘change’, ‘relative-location’, ‘identify’, ‘action’, ‘move’, and ‘enhancement’ (p.148) Need to be complemented with workplace specific taxonomy (of handling and motion) Communicative intent 15
  16. 16. xAPI verb statements Helicopter Industry 16
  17. 17. • Application-driven versus tracking-driven drop statements • Behaviour validation using automated tracking: – State-based: Removed cap: cap was there, cap not there – Location-based: Removed screw: returned screw to used parts bucket – Dependancy-based: Removed screw: picked up replacement screw • Related industries (Furniture + Textiles): common core? Challenges 17
  18. 18. Ralf Klamma, RWTH Aachen, Germany Requirements Bazaar 18
  19. 19. Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke 19 Learning Layers Requirements Bazaar – Involving End Users in Requirements Engineering  End User Involvement – Open Innovation [Chesbrough, 2003] – ideas from the long tail [Anderson, 2006] – emerging from practices, needs adoption [Denning, 2004]  Requirements Bazaar [Klamma et al., 2011], [Renzel et al., 2013] – social continuous innovation platform – listening to the long tail communities – mobile first Web application
  20. 20. Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke 20 Learning Layers https://requirements-bazaar.org
  21. 21. Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke 21 Learning Layers DevOps Life Cycle  Rapid release cycles  Strong feedback loop  Continuous integration  Continuous delivery  Continuous deployment  Containerized microservices
  22. 22. Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke 22 Learning Layers DevOpsUse Life Cycle for Continuous Innovation Involving end users in the design and development process  ideas and needs  co-design  beta testing  context adaptation  awareness
  23. 23. Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke 23 Learning Layers Requirements Bazaar 2.0 for Continuous Innovation  Redeveloped version launched in April 2015 – Increased maintainability – Based on componentized architecture – Mobile first responsive Web design  Incorporating DevOpsUse practices Requirements Bazaar Kanban Board Responsive Design
  24. 24. Open Problems 24
  25. 25. Task Force and Open Problems  Task Forces identified: – Use Cases, Storyboards, and Requirements – Test Battery (Authoring of ARLEMs) – Reference Implementations – Validator Service – Pilots: Running Code  Open Problems – Real-time messaging (multiuser, multi-device, smart objects) – Revision needed: xAPI auto-logging – query language for constraint validation – Performance analytics – LEM aggregator (‘Open LEM’)
  26. 26. The END

Special foci: xAPI and Requirements Bazaar

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