Taming Digital Traces for Informal Learning: A Semantic-Driven Approach

  • Dhavalkumar Thakker
  • Dimoklis Despotakis
  • Vania Dimitrova
  • Lydia Lau
  • Paul Brna
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7563)


Modern learning models require linking experiences in training environments with experiences in the real-world. However, data about real-world experiences is notoriously hard to collect. Social spaces bring new opportunities to tackle this challenge, supplying digital traces where people talk about their real-world experiences. These traces can become valuable resource, especially in ill-defined domains that embed multiple interpretations. The paper presents a unique approach to aggregate content from social spaces into a semantic-enriched data browser to facilitate informal learning in ill-defined domains. This work pioneers a new way to exploit digital traces about real-world experiences as authentic examples in informal learning contexts. An exploratory study is used to determine both strengths and areas needing attention. The results suggest that semantics can be successfully used in social spaces for informal learning – especially when combined with carefully designed nudges.


Semantic Data Browser Social Semantic Web Semantic Augmentation Adult Informal Learning 


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  1. 1.
    Cara Group Plc., How Informal Learning is Transforming the Workplace, A Pulse Survey – Social Media’s Impact on Informal Workplace Learning (2010)Google Scholar
  2. 2.
    Redecker, C., Ala-Mutka, K., Punie, Y.: Learning 2.0 - The Impact of Social Media on Learning in Europe, Policy Brief, European Commission, Joint Research Centre, Institute for Prospective Technological Studies (2010)Google Scholar
  3. 3.
    Knowles, M.S., Holton, E.F., Swanson, R.A.: The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development. Elsevier (2005)Google Scholar
  4. 4.
    Ananiadou, K., Claro, M.: 21st Century Skills and Competences for New Millennium Learners in OECD Countries. OECD Education Working Papers, No. 41 (2009)Google Scholar
  5. 5.
    Lynch, C., Ashley, K., Pinkwart, N., Aleven, V.: Concepts, structures, and goals: Redefining ill-definedness. Int. Journal of AI in Education 19, 253–266 (2009)Google Scholar
  6. 6.
    Kravcik, M., Klamma, R.: On Psychological Aspects of Learning Environments Design. In: Kloos, C.D., Gillet, D., Crespo García, R.M., Wild, F., Wolpers, M. (eds.) EC-TEL 2011. LNCS, vol. 6964, pp. 436–441. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Weber, N., Schoefegger, K., Bimrose, J., Ley, T., Lindstaedt, S., Brown, A., Barnes, S.-A.: Knowledge Maturing in the Semantic MediaWiki: A Design Study in Career Guidance. In: Cress, U., Dimitrova, V., Specht, M. (eds.) EC-TEL 2009. LNCS, vol. 5794, pp. 700–705. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Dimitrova, V., Lau, L., O’Rourke, R.: Semantic Social Scaffolding for Capturing and Sharing Dissertation Experience. IEEE-TLT 4, 74–87 (2011)Google Scholar
  9. 9.
    Markkanen, B.: Schrey-Niemenmaa: Knowledge Practices Laboratory Overview (2008)Google Scholar
  10. 10.
    Karlsen, K.: Supporting reflection and creative thinking by carers of older people with dementia. In: Proceedings of PervasiveHealth 2011, pp. 526–529 (2011)Google Scholar
  11. 11.
    Westerhout, E., et al.: Enhancing the Learning Process: Qualitative Validation of an Informal Learning Support System Consisting of a Knowledge Discovery and a Social Learning Component. In: Wolpers, M., Kirschner, P.A., Scheffel, M., Lindstaedt, S., Dimitrova, V. (eds.) EC-TEL 2010. LNCS, vol. 6383, pp. 374–389. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Rizzo, G., Troncy, R.: NERD: Evaluating Named Entity Recognition Tools in the Web of Data. In: WEKEX 2011 @ ISWC 2011, Bonn, Germany (2011)Google Scholar
  13. 13.
    Popov, I.O., Schraefel, M., Hall, W., Shadbolt, N.: Connecting the Dots: A Multi-pivot Approach to Data Exploration. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 553–568. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Thakker, D., Dimitrova, V., Lau, L., Karanasios, S., Yang-Turner, F.: A Priori Ontology Modularisation in Ill-defined Domains. In: I-Semantics 2011, pp. 167–170 (2011)Google Scholar
  15. 15.
    Sunstein, C., Thaler, R.: Nudge: Improving Decisions about Health, Wealth, and Happiness. Penguin Books, New York (2009)Google Scholar
  16. 16.
    Cheng, G., Tran, T., Qu, Y.: RELIN: Relatedness and Informativeness-Based Centrality for Entity Summarization. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 114–129. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  17. 17.
    Zhang, X., Cheng, G., Ge, W., Qsssu, Y.: Summarizing Vocabularies in the Global Semantic Web. Journal of Computer Science and Technology 24(1), 165–174 (2009)CrossRefGoogle Scholar
  18. 18.
    Ammari, A., Lau, L., Dimitrova, V.: Deriving Group Profiles from Social Media to Facilitate the Design of Simulated Environments for Learning. In: LAK 2012, Vancouver (2012)Google Scholar
  19. 19.
    Despotakis, D., Lau, L., Dimitrova, V.: A Semantic Approach to Extract Individual Viewpoints from User Comments on an Activity. In: AUM@UMAP 2011 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dhavalkumar Thakker
    • 1
  • Dimoklis Despotakis
    • 1
  • Vania Dimitrova
    • 1
  • Lydia Lau
    • 1
  • Paul Brna
    • 1
  1. 1.University of LeedsLeedsUK

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