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Mumbai
7-12 January 2013
Su White




     @suukii




Web Science: Expanding the Notion of Computer Science White
and Vafopoulos http://eprints.ecs.soton.ac.uk/22710/
University of Southampton
Founded 1862, Charter 1952
25,000 FTE Students
Russell Group, Top 15 UK, WUN
Excellence in: (Opto)Electronics, Computer Science,
Oceanography, Engineering (esp. Nautical and Aero) Acoustics


     Electronics and Computer Science
                                                               Excellence in teaching
                                                               and research
                                                               Opto Electronics
                                                               Nano Electronics
                                                               Computer Science
                                                               Web Science
                                                               (and others)
                                                               ~110 academics
                                                               ~200 research staff
                                                               ~300 PhD
                                                               ~800 UG, ~350 MSc
Web Science at Southampton

                      —  Web and Internet
                         Science Group
                      —  20 Faculty Members
                         (subsuming Learning
                         Societies Lab)

                      —  Doctoral Training
                         Centre
                      —  Research areas include
                         —  Open Data
                         —  Semantic Web
                         —  Memories for Life
                         —  Trust, privacy and
                             provenance
                         —  Learning with the Web
Specialisms – me and my
immediate colleagues




                          6
Conceptual Structures for STEM data:
linked open rich and personal
Conceptual structures
Thinking           Knowledge
  and                 and
learning         representation
epiSTEME 5
ICCS2013




             Socio Politico Dimensions
             Nation State
             Universal education
             Equality, diversity, change
Conceptual Structures for STEM data:
linked open rich and personal
                 Thinking and Learning
                          and
              Knowledge and Representation
                    STEM Education
                 Educational Processes


         Change-> Beliefs->Experience -> Practice ->
Conceptual Structures
   Teachers (instructors and Curriculum Designers)
          Researchers (Theorists, Evaluators)
Learners (young, adult, CPD, independent, informal ++)

                     Classroom
                        Lab               What?      Where?
                        Wild              Why?       How?
       Change-> Beliefs->Experience -> Practice ->
acknowledge
The world is changing…
The world is changing…
     Our beliefs, actions and behaviours are shaped by our experiences

Our beliefs actions and behaviours are shaped by our (vicarious) experiences

 Culture, tradition, popular culture, texts, books, cinema, TV, mass media,
                                      web
The Web




The most successful information architecture in history
                                                Nigel Shadbolt
The Web
exponential growth and impact
Internet in India and the world
Perhaps 121 million of India’s 1.2
    billion population on internet 2012




c.f.
China 38% 513m
US, 78% 245 m
In, 10% 121 m
http://imgs.xkcd.com/comics/online_communities_small.png
The two magics
          (Tim Berners Lee, 2006, 2007)
The Web
exploiting emergent networks




           emerging new business models
Emergent/open content and
collective intelligence
The new web landscape
                                   Context
                         Shop      mobile     Vehicle
                        window
                                               texts
                         ebay,
                                               video
                        amazon

             Platform
                                                         Searching
              citizen
                                                        Information
             science



          Meme
         machine                   Digital                   creation
         apps and
           apps
                                 literacies                   blogs




 From rent a coder, to wikilogia, from flikr to Pinterest, itunesu to Tedx
sharing, ownership, micro-charging, new models, Tripit meme machines
Educationally…




Situated cognition, peer instruction, informal learning, digital literacies,
self efficacy, social construction, co-creation – but these are not mobiles…
—  How many devices can you buy
                                          for the cost of a teacher
                                       —  Diversity, not instead of, but as
                                          well as?
                                       —  Example: syria wikilogia,
                                          facebook informal learning,
                                          digital literacies
                                       —  Texts, campaigns, employment?
                                       —  Models: co-creation, deduction,
                                          application memes
                                       —  Informal and accidental
                                          learning
                                       —  Blogging for reflective journals,
                                          collaborative texts via wikis


     We can still use flashcards, and social games, learn from texts etc
But…powerful affordances may emerge, evolve…’games’ as vehicles for learning
Open and linked data
             Text and links were not enough
Via social web “software that supports group interaction”
                 Web 2.0, perpetual beta
               Consumers and producers?
                    The read write web
              Machine and human readable
         Lightweight and heavyweight modelling
Open Data




                                                                    Big Data



Students might contribute to collecting assembling open data e.g. vocabularies
  geographic data, plant census, open mapping, disease and health markers
 opportunities for authentic activities, situated learning, reward, contribution
ASBOs, Dentists and Tubes




And Haiti
a citizen open map in two weeks
… with millions of users
the Indian context will emerge
Open Access: ePrints
10 years old
EdShare – Repositories meet Web
  2.0




Learn from the success and methods of collections in the wild
Semantically Driven Web Sites (ECS
Web Site)
Crowd sourced open data map
—  Mashup of crowd sourced
   data plus official data

—  Amateur effort
—  Useful and visible
—  Interrogate the data points
   interactively




           http://opendatamap.ecs.soton.ac.uk
We want to climb over the walls…




         With apologies….
         Adapted from image used by tbl, originally from the economist I think
OERs, OCW and MOOCs
open educational resources
massively open online courses
Potential?
 —  Modelling (theory to
    practice)
    —  Shared curriculum design?
    or
    —  Emerging the curriculum
         from resources



 —  Learning environments
    —  Multi-faceted
    —  Automation – assembling,
        aggregating
    —  Collaboration for community
        enterprise
    —  Standardisation?
        Customisation?



Remembering: face to face/social may be more important
The challenges
—  Ride on the wave of change
—  Empower learners to take
   charge of their destinies
—  Craft a future for the
   citizens of tomorrow
   embracing diversity and
   mastering the whole
   spectrum of technologies
—  Shape and craft the
   classroom for maximum
   mutual benefit – the citizen
   and the nation state
Thank You J

Dr Su White

Electronics and Computer Science

University of Southampton



saw@ecs.soton.ac.uk

@suukii
References
Becher, T. The Significance of Disciplinary Differences. Studies In Higher Education 19, 151 (1994).
Berners-Lee, T. The process of designing things in a very large space: Keynote Presentation. WWW2007 (2007).
Berners-Lee, T., Hendler, J. & Lassila, O. The Semantic Web. Scientific American 284, 34–43 (2001).
Berners-Lee, T.,Weitzner, D J., Hall, W., O'Hara, K., Shadbolt, N., Hendler, J., A Framework for Web Science. Foundations and
Trends® in Web Science 1, 1–130 (2006).
Biggs, J. Teaching for quality learning at university: what the student does. (Open University Press in association with The Society
for Research into Higher Education: Buckingham, 1999).
Biglan, A. Relationships between subject matter characteristics and the structure and output of university departments. Journal of
Applied Psychology 57, 204–213 (1973).
Biglan, A. The characteristics of subject matter in different academic areas. Journal of Applied Psychology 57, 195–203 (1973).
Cabinet Office Open Data White Paper Unleashing the Potential Unleashing the Potential Open Data White Paper. 52 (London,
2011).at http://www.cabinetoffice.gov.uk/resource-library/open-data-white-paper-unleashing-potential
Campbell, L. M. UK Learning Object Metadata Core Working Draft Version 0.3 1204. (2004).
Cassel, L. N., Davies, G., LeBlanc, R., Snyder, L. & Topi, H. Using a Computing Ontology as a Foundation for Curriculum
Development. SW-EL’08 conjunction with ITS 2008 (2008).
Davis, H. C. Carr, L. A., Hey, J. M. N., Howard, Y., Millard, D. E., Morris, D., & White, S., Bootstrapping a Culture of Sharing to
Facilitate Open Educational Resources. IEEE Transactions on Learning Technologies 3, 96–109 (2010).
Hall, W., Davis, H. C. & Hutchings, G. Rethinking Hypermedia the Microcosm Approach. (Kluwer: Boston, MA, 1996).
IEEE Learning Standards Committee (LTSC) IEEE P1484.12 Learning Object Metadata Working Group; WG12. at
http://ltsc.ieee.org/wg12/
Koper, R. Modelling units of study from a pedagogical perspective the pedagogical meta-model behind EML. (2001).
Laurillard, D. Rethinking University Teaching: a Framework for the Effective Use of Educational Technology.
(Routledge: London, 1993).
Long, P & Siemens, G. Penetrating the Fog: Analytics in Learning and Education. Educause Review 46, 31–40 (2011).
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O’Reilly, T. What Is Web 2.0 – Design Patterns and Business Models for the Next Generation of Software http://oreilly.com/web2/archive/
what-is-web-20.html last accessed June 2010. (2005).
O’Reilly, T. What is Web 2.0: Design patterns and business models for the next generation of software. Communications & strategies 1, 17–
37 (2007).
Shadbolt, N. R., Gibbins, N., Glaser, H., Harris, S. & m.c. schraefel CS AKTive Space or how we stopped worrying and learned to love the
Semantic Web. IEEE Intelligent Systems 19, 41–47 (2004).
Shadbolt, N., Berners-Lee, T. & Hall, W. The Semantic Web Revisited. IEEE Intelligent Systems 21, 96–101 (2006).
Shirky, C. A group is its own worst enemy - A speech at ETech, April, 2003. Clay Shirky’s Writings About the Internet: Economics & Culture,
Media & Community, Open Source http://www.shirky.com/writings/group_enemy.html, (2003).
Shotton, D., Portwin, K., Klyne, G. & Miles, A. Adventures in semantic publishing: exemplar semantic enhancements of a research article.
PLoS computational biology 5, e1000361 (2009).
Siemens, G. & Downes, S. Connectivism and connective knowledge: Course delivered at University of Manitoba, September to November,
2008. Available from http://ltc.umanitoba.ca/connectivism/. (2008).
Siemens, G. & Gasavic, D. Learning and Knowledge Analytics. Journal of Educational Technology & Society 15, 1–2 (2012).
Siemens, G. Connectivism : A Learning Theory for the Digital Age. International Journal of Instructional Technology and Distance Learning,
2, 1–8 (2005).
Siemens, G. Learning Analytics: Envisioning a Research Discipline and a Domain of Practice. Second International Conference on Learning
Analytics and Knowledge (LAK’12) 4–8 (2012).
Tattersall, C. “Comparing Educational Modelling Languages on a CaseStudy: An Approach using IMS Learning Design. “Sixth International
Conference on Advanced Learning Technologies, 1154 – 1155 (2006).
Tiropanis, T, Davis, H., Millard, D., Weal, M., White, S., Wills, G., JISC - SemTech Project Report. 28 (Bristol, 2009).
White, S. & Liccardi, I. Harnessing Insight into Disciplinary Differences to Refine e-learning Design. Frontiers in Education Conference, 36th
Annual 5–10 (2006).doi:10.1109/FIE.2006.322553
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Conceptual Structures in STEM education

  • 2. Su White @suukii Web Science: Expanding the Notion of Computer Science White and Vafopoulos http://eprints.ecs.soton.ac.uk/22710/
  • 3.
  • 4. University of Southampton Founded 1862, Charter 1952 25,000 FTE Students Russell Group, Top 15 UK, WUN Excellence in: (Opto)Electronics, Computer Science, Oceanography, Engineering (esp. Nautical and Aero) Acoustics Electronics and Computer Science Excellence in teaching and research Opto Electronics Nano Electronics Computer Science Web Science (and others) ~110 academics ~200 research staff ~300 PhD ~800 UG, ~350 MSc
  • 5. Web Science at Southampton —  Web and Internet Science Group —  20 Faculty Members (subsuming Learning Societies Lab) —  Doctoral Training Centre —  Research areas include —  Open Data —  Semantic Web —  Memories for Life —  Trust, privacy and provenance —  Learning with the Web
  • 6. Specialisms – me and my immediate colleagues 6
  • 7. Conceptual Structures for STEM data: linked open rich and personal
  • 8. Conceptual structures Thinking Knowledge and and learning representation
  • 9. epiSTEME 5 ICCS2013 Socio Politico Dimensions Nation State Universal education Equality, diversity, change
  • 10. Conceptual Structures for STEM data: linked open rich and personal Thinking and Learning and Knowledge and Representation STEM Education Educational Processes Change-> Beliefs->Experience -> Practice ->
  • 11. Conceptual Structures Teachers (instructors and Curriculum Designers) Researchers (Theorists, Evaluators) Learners (young, adult, CPD, independent, informal ++) Classroom Lab What? Where? Wild Why? How? Change-> Beliefs->Experience -> Practice ->
  • 13. The world is changing…
  • 14.
  • 15. The world is changing… Our beliefs, actions and behaviours are shaped by our experiences Our beliefs actions and behaviours are shaped by our (vicarious) experiences Culture, tradition, popular culture, texts, books, cinema, TV, mass media, web
  • 16. The Web The most successful information architecture in history Nigel Shadbolt
  • 17.
  • 19. Internet in India and the world
  • 20. Perhaps 121 million of India’s 1.2 billion population on internet 2012 c.f. China 38% 513m US, 78% 245 m In, 10% 121 m
  • 22. The two magics (Tim Berners Lee, 2006, 2007)
  • 23. The Web exploiting emergent networks emerging new business models
  • 25. The new web landscape Context Shop mobile Vehicle window texts ebay, video amazon Platform Searching citizen Information science Meme machine Digital creation apps and apps literacies blogs From rent a coder, to wikilogia, from flikr to Pinterest, itunesu to Tedx sharing, ownership, micro-charging, new models, Tripit meme machines
  • 26.
  • 27. Educationally… Situated cognition, peer instruction, informal learning, digital literacies, self efficacy, social construction, co-creation – but these are not mobiles…
  • 28. —  How many devices can you buy for the cost of a teacher —  Diversity, not instead of, but as well as? —  Example: syria wikilogia, facebook informal learning, digital literacies —  Texts, campaigns, employment? —  Models: co-creation, deduction, application memes —  Informal and accidental learning —  Blogging for reflective journals, collaborative texts via wikis We can still use flashcards, and social games, learn from texts etc But…powerful affordances may emerge, evolve…’games’ as vehicles for learning
  • 29.
  • 30. Open and linked data Text and links were not enough Via social web “software that supports group interaction” Web 2.0, perpetual beta Consumers and producers? The read write web Machine and human readable Lightweight and heavyweight modelling
  • 31.
  • 32. Open Data Big Data Students might contribute to collecting assembling open data e.g. vocabularies geographic data, plant census, open mapping, disease and health markers opportunities for authentic activities, situated learning, reward, contribution
  • 33. ASBOs, Dentists and Tubes And Haiti a citizen open map in two weeks … with millions of users the Indian context will emerge
  • 35. EdShare – Repositories meet Web 2.0 Learn from the success and methods of collections in the wild
  • 36. Semantically Driven Web Sites (ECS Web Site)
  • 37. Crowd sourced open data map —  Mashup of crowd sourced data plus official data —  Amateur effort —  Useful and visible —  Interrogate the data points interactively http://opendatamap.ecs.soton.ac.uk
  • 38. We want to climb over the walls… With apologies…. Adapted from image used by tbl, originally from the economist I think
  • 39. OERs, OCW and MOOCs open educational resources massively open online courses
  • 40. Potential? —  Modelling (theory to practice) —  Shared curriculum design? or —  Emerging the curriculum from resources —  Learning environments —  Multi-faceted —  Automation – assembling, aggregating —  Collaboration for community enterprise —  Standardisation? Customisation? Remembering: face to face/social may be more important
  • 41. The challenges —  Ride on the wave of change —  Empower learners to take charge of their destinies —  Craft a future for the citizens of tomorrow embracing diversity and mastering the whole spectrum of technologies —  Shape and craft the classroom for maximum mutual benefit – the citizen and the nation state
  • 42. Thank You J Dr Su White Electronics and Computer Science University of Southampton saw@ecs.soton.ac.uk @suukii
  • 43. References Becher, T. The Significance of Disciplinary Differences. Studies In Higher Education 19, 151 (1994). Berners-Lee, T. The process of designing things in a very large space: Keynote Presentation. WWW2007 (2007). Berners-Lee, T., Hendler, J. & Lassila, O. The Semantic Web. Scientific American 284, 34–43 (2001). Berners-Lee, T.,Weitzner, D J., Hall, W., O'Hara, K., Shadbolt, N., Hendler, J., A Framework for Web Science. Foundations and Trends® in Web Science 1, 1–130 (2006). Biggs, J. Teaching for quality learning at university: what the student does. (Open University Press in association with The Society for Research into Higher Education: Buckingham, 1999). Biglan, A. Relationships between subject matter characteristics and the structure and output of university departments. Journal of Applied Psychology 57, 204–213 (1973). Biglan, A. The characteristics of subject matter in different academic areas. Journal of Applied Psychology 57, 195–203 (1973). Cabinet Office Open Data White Paper Unleashing the Potential Unleashing the Potential Open Data White Paper. 52 (London, 2011).at http://www.cabinetoffice.gov.uk/resource-library/open-data-white-paper-unleashing-potential Campbell, L. M. UK Learning Object Metadata Core Working Draft Version 0.3 1204. (2004). Cassel, L. N., Davies, G., LeBlanc, R., Snyder, L. & Topi, H. Using a Computing Ontology as a Foundation for Curriculum Development. SW-EL’08 conjunction with ITS 2008 (2008). Davis, H. C. Carr, L. A., Hey, J. M. N., Howard, Y., Millard, D. E., Morris, D., & White, S., Bootstrapping a Culture of Sharing to Facilitate Open Educational Resources. IEEE Transactions on Learning Technologies 3, 96–109 (2010). Hall, W., Davis, H. C. & Hutchings, G. Rethinking Hypermedia the Microcosm Approach. (Kluwer: Boston, MA, 1996). IEEE Learning Standards Committee (LTSC) IEEE P1484.12 Learning Object Metadata Working Group; WG12. at http://ltsc.ieee.org/wg12/ Koper, R. Modelling units of study from a pedagogical perspective the pedagogical meta-model behind EML. (2001).
  • 44. Laurillard, D. Rethinking University Teaching: a Framework for the Effective Use of Educational Technology. (Routledge: London, 1993). Long, P & Siemens, G. Penetrating the Fog: Analytics in Learning and Education. Educause Review 46, 31–40 (2011). . O’Reilly, T. What Is Web 2.0 – Design Patterns and Business Models for the Next Generation of Software http://oreilly.com/web2/archive/ what-is-web-20.html last accessed June 2010. (2005). O’Reilly, T. What is Web 2.0: Design patterns and business models for the next generation of software. Communications & strategies 1, 17– 37 (2007). Shadbolt, N. R., Gibbins, N., Glaser, H., Harris, S. & m.c. schraefel CS AKTive Space or how we stopped worrying and learned to love the Semantic Web. IEEE Intelligent Systems 19, 41–47 (2004). Shadbolt, N., Berners-Lee, T. & Hall, W. The Semantic Web Revisited. IEEE Intelligent Systems 21, 96–101 (2006). Shirky, C. A group is its own worst enemy - A speech at ETech, April, 2003. Clay Shirky’s Writings About the Internet: Economics & Culture, Media & Community, Open Source http://www.shirky.com/writings/group_enemy.html, (2003). Shotton, D., Portwin, K., Klyne, G. & Miles, A. Adventures in semantic publishing: exemplar semantic enhancements of a research article. PLoS computational biology 5, e1000361 (2009). Siemens, G. & Downes, S. Connectivism and connective knowledge: Course delivered at University of Manitoba, September to November, 2008. Available from http://ltc.umanitoba.ca/connectivism/. (2008). Siemens, G. & Gasavic, D. Learning and Knowledge Analytics. Journal of Educational Technology & Society 15, 1–2 (2012). Siemens, G. Connectivism : A Learning Theory for the Digital Age. International Journal of Instructional Technology and Distance Learning, 2, 1–8 (2005). Siemens, G. Learning Analytics: Envisioning a Research Discipline and a Domain of Practice. Second International Conference on Learning Analytics and Knowledge (LAK’12) 4–8 (2012). Tattersall, C. “Comparing Educational Modelling Languages on a CaseStudy: An Approach using IMS Learning Design. “Sixth International Conference on Advanced Learning Technologies, 1154 – 1155 (2006). Tiropanis, T, Davis, H., Millard, D., Weal, M., White, S., Wills, G., JISC - SemTech Project Report. 28 (Bristol, 2009). White, S. & Liccardi, I. Harnessing Insight into Disciplinary Differences to Refine e-learning Design. Frontiers in Education Conference, 36th Annual 5–10 (2006).doi:10.1109/FIE.2006.322553 Wilson, S. Community-driven Specifications: xCrI, sword, and Leap2a. International Journal of IT Standards and Standardization Research 8, 74–86 (2010).