A Learning Environment for the 21st Century Learner
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  • 1. A Learning Environment for the 21st Century Learner: By: Robert Glynn August 6, 2010 The Potential of Personalized Learning Environments, The Semantic Web and Augmented Reality
  • 2. A 21 st Century Ecology Employment Community Innovation Personal Life
  • 3. Three Trends for 21 st Century Learning
  • 4. Personal Learning Environments
    • What is a personal learning environment (PLE)?
    • “ … a set of the different applications, services and various other types of learning resources gathered from different contexts. It is constructed by an individual and used in everyday life for learning. It is not an application or a system but a personal assemblage supporting new learning modalities induced by ubiquitous technologies and social software.” (Henri, Charlier & Limpens, 2008, p. 3766)
  • 5. PLE Conceptual Model – More than a LMS Note: From Henri, F., Charlier, B. & Limpens, F. (2008). Understanding PLE as an essential component of the learning process. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 (pp. 3766-3770). Chesapeake, VA: AACE.
  • 6. Current LMS/VLE environments vs. PLE Current e-learning environment Future e-learning environment Note: Adapted from Shaffert, S. & Hilzensauer, W. (2008). On the way towards personal learning environments: Seven crucial aspects. eLearning Papers, 9.
  • 7. Future Personal Learning Environment Note: From Henri, F., Charlier, B. & Limpens, F. (2008). Understanding PLE as an essential component of the learning process. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 (pp. 3766-3770). Chesapeake, VA: AACE.
  • 8. Anticipated Benefits of PLEs PLEs
  • 9. The Semantic Web
    • “ methods and technologies that allow machines to understand the meaning of information on the Web “
    • Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American , 284, 34–43.
  • 10. Ontology
    • An ontology “comprises a set of knowledge terms, including the vocabulary, the semantic interconnections, and some simple rules of inference and logic for some particular topic.” (pp. 30)
    • Hendler, J. (2001). Agents and the semantic web. IEEE Intelligent Systems, 16(2), 30-37.
  • 11. Semantic Web Architecture
    • Machine-processable, global Web standards
    • Assigning unambiguous names (URI)
    • Expressing and linking data, including metadata (RDF)
    • Capturing ontologies (OWL)
    • Query, rules, transformations, deployment, application spaces (in progress), logic, proofs, trust
    Note: Adapted from World Wide Web Consortium (2007). Semantic web, and other technologies to watch . Retrieved August 3, 2010 from http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/#%2824%29.
  • 12. Metadata Helps Describe Web Content (XML) Current HTML markup Same content with XML markup Note: Adapted from Devedzic, V. (2004). Education and the semantic web. International Journal of Artificial Intelligence in Education , 14, 39-65.
  • 13. Learning on the Semantic Web Note: From Devedzic, V. (2004). Education and the semantic web. International Journal of Artificial Intelligence in Education , 14, 39-65.
  • 14. Learning Benefits of Semantic Web
  • 15. Augmented Reality (AR)
    • “AR allows the user to see the real world, with virtual objects superimposed upon or composited with the real world. Therefore, AR supplements reality, rather than completely replacing it ” (Azuma, 1997, pp. 2)
  • 16. Reality + Mobile learning and augmented reality [Image] (n.d.). Retrieved August 6, 2010 from http://www.avatarlanguages.com/teaching/guide.php
  • 17. Virtual vs. Augmented Reality Medieval slaughter [Image] (n.d.). Retrieved August 6, 2010 http://www.all-freeware.com/results/strategy/game Virtual Reality Augmented Reality
  • 18. Example Learning Model with Augmented Reality Education through experience Enhanced motivation Authentic learning + + +
  • 19. Future Learning: A Vision for the Future Learning Environment of the Future
  • 20. Challenges for Future ICT Learning Environments
  • 21. References
    • Anido L.E., Fernandez M.J., Caeiro M., Santos J.M., Rodrıguez J.S. & Llamas M. (2002). Educational metadata and brokerage for learning resources. Computers and Education , 38, 351–374. 
    • Aviram, A., Ronen, Y., Somekh, S., Winer, A. & Sarid, A. (2008). Self-regulated personalised learning (SRPL): Developing iClass's pedagogical model. eLearning Papers , 9.
    • Azuma, R. (1997). A survey of augmented reality. Teleoperators and Virtual Environments , 6(4), 355-85.
    • Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American , 284, 34–43.
    • Brown, J.S. & Adler, R.P. (2008). Minds on fire: Open education, the long tail, and Learning 2.0. EDUCAUSE Review , 43(1), 16-32.
  • 22. References
    • Dewey, J. (1938). Experience and Education . Simon & Schuster.
    • Hendler, J. (2001). Agents and the semantic web. IEEE Intelligent Systems, 16(2), 30-37.
    • Henri, F., Charlier, B. & Limpens, F. (2008). Understanding PLE as an essential component of the learning process. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 (pp. 3766-3770). Chesapeake, VA: AACE.
    • Huang, W., Webster, D., Wood, D. & Ishaya, T. (2006). An intelligent semantic e-learning framework using context-aware Semantic Web technologies. British Journal of Educational Technology , 37(3), 351-373.
  • 23. References
    • Johnson, L., Levine, A., Smith, R., & Stone, S. (2010). The 2010 Horizon Report . Austin, Texas: The New Media Consortium.
    • Katz, I. R., & Macklin, A.S. (2007). Information and communication technology (ICT) literacy: Integration and assessment in higher education. Systemics, Cybernetics and Informatics 5(4), 50-55.
    • McLoughlin, C. & Lee, M.J. (2010). Personalised and self regulated learning in the Web 2.0 era: International exemplars of innovative pedagogy using social software. Australasian Journal of Educational Technology , 26(1), 28-43.
    • Narciss, S., Proske, A. & Koerndle, H. (2007). Promoting self-regulated learning in web-based environments. Computers in Human Behavior , 23(3), 1126-1144.
  • 24. References
    • Ohler, J. (2008). The semantic web in education. EDUCAUSE Quarterly , 31(4), 7-9.
    • Rosenbaum, E., Klopfer, E. & Perry, J. (2006). On location learning: Authentic applied science with networked augmented realities. Journal of Science Education and Technology , 16(1), 31-45.
    • Stojanovic L., Staab S. & Studer R. (2001). ELearning based on the semantic web. In Proceedings of the WebNet2001 – World Conference on the WWW and Internet . Florida, USA.
    • Stubbé, H. E. & Theunissen, N. C. M. (2008). Self-directed adult learning in a ubiquitous learning environment: A meta-review. In M. Kalz, R. Koper, V. Hornung-Prähauser & M. Luckmann (Eds), Proceedings of the First Workshop on Technology Support for Self-Organized Learners (pp. 5-28). Aachen, Germany: RWTH Aachen University.
    • Van’t Hooft, M., Swan, K., Cook, D. & Lin,Y (2007). What is ubiquitous computing? In: van t Hooft M, Swan K (eds.) Ubiquitous computing in education . Lawrence Erlbaum Associates, Mah- wah, NJ.