Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Learning Networks

  • Caroline HaythornthwaiteEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_67



Absorptive capacity

Ability of a network to capitalize on new knowledge

Adaptive structuration

The negotiation and continuous emergence of practices around technology use and group needs


An actor who sits between and connects two or more networks or cliques within a network

Cognitive social structure

Perceptions of actors about the interrelations among actors in the network

Formal, nonformal, informal learning

Formal – structured learning associated with degree-granting institutions and credentials; nonformal – structured learning not associated with credentials, for example, learning for hobbies; informal – unstructured learning, such as learning norms and cultural conventions


Similarity between actors, for example, in race, gender, education, and attitudes

Latent tie structure

A technical or social structure that puts actors in virtual...


Social networks 
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  1. Benkler Y (2006) The wealth of networks: how social production transforms markets and freedom. Yale University Press, New HavenGoogle Scholar
  2. Borgatti SP, Cross R (2003) A relational view of information seeking and learning in social networks. Manag Sci 49(4):432–445zbMATHCrossRefGoogle Scholar
  3. Budhathoki N, Haythornthwaite C (2013) Motivation for open collaboration: crowd and community models and the case of OpenStreetMap. Am Behav Sci 57(5):548–575CrossRefGoogle Scholar
  4. Burt R (1992) Structural holes: the social structure of competition. Harvard University Press, CambridgeGoogle Scholar
  5. Cohen WM, Levinthal DA (1990) Absorptive capacity: a new perspective on learning and innovation. Adm Sci Q 35:128–152CrossRefGoogle Scholar
  6. Cummings J, Kiesler S (2008) Who collaborates successfully? Prior experience reduces collaboration barriers in distributed interdisciplinary research. In: Proceedings of the ACM conference on computer-supported cooperative work CSCW ’08, San Diego. ACM, New YorkGoogle Scholar
  7. Daly AJ (ed) (2010) Social network theory and educational change. Harvard Education Press, CambridgeGoogle Scholar
  8. Dawson S (2010) ‘Seeing’ the learning community: an exploration of the development of a resource for monitoring online student networking. Br J Educ Technol 41(5):736–752CrossRefGoogle Scholar
  9. Dawson S, Bakharia A, Lockyer L, Heathcote E (2011a) ‘Seeing’ networks: visualising and evaluating student learning networks. Final Report 2011. Australian Learning and Teaching Council Ltd, Canberra. Available online at: http://wenger-trayner.com/documents/Wenger_Trayner_DeLaat_Value_creation.pdf
  10. Dawson S, Macfadyen LP, Lockyer L, Mazzochi-Jones D (2011b) Using social network metrics to assess the effectiveness of broad based admission practices. Australas J Educ Technol 27(1):16–27CrossRefGoogle Scholar
  11. Dawson S, Pei-Ling Tan J, McWilliam E (2011c) Measuring creative potential: using social network analysis to monitor and develop learners’ creative capacity. Australas J Educ Technol 27(6):924–942CrossRefGoogle Scholar
  12. De Laat MF (2011) Bridging the knowledge gap: using social network methodology for detecting, connecting and facilitating informal networked learning in organizations. In: Proceedings of the 44th IEEE annual Hawaii international conference on system sciences, Kauai. IEEEGoogle Scholar
  13. DeSanctis G, Poole MS (1994) Capturing the complexity in advanced technology use: adaptive structuration theory. Organ Sci 5(2):121–147CrossRefGoogle Scholar
  14. Girard M, Stark D (2007) Socio-technologies of assembly: sense-making and demonstration in rebuilding lower Manhattan. In: Mayer-Schönberger V, Lazer D (eds) Governance and information technology: from electronic government to information government. MIT Press, Cambridge, pp 145–176Google Scholar
  15. Granovetter MS (1973) The strength of weak ties. Am J Sociol 78:1360–1380CrossRefGoogle Scholar
  16. Gruzd A (2009) Studying collaborative learning using name networks. J Educ Libr Inf Sci 50(4):243–253Google Scholar
  17. Hansen MT (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Adm Sci Q 44:82–111CrossRefGoogle Scholar
  18. Haythornthwaite C (2002a) Strong, weak and latent ties and the impact of new media. Inf Soc 18(5):385–401CrossRefGoogle Scholar
  19. Haythornthwaite C (2002b) Building social networks via computer networks: creating and sustaining distributed learning communities. In: Renninger KA, Shumar W (eds) Building virtual communities: learning and change in cyberspace. Cambridge University Press, Cambridge, pp 159–190CrossRefGoogle Scholar
  20. Haythornthwaite C (2005) Social networks and internet connectivity effects. Inf Commun Soc 8(2):125–147CrossRefGoogle Scholar
  21. Haythornthwaite C (2006) Articulating divides in distributed knowledge practice. Inf Commun Soc 9(6):761–780CrossRefGoogle Scholar
  22. Haythornthwaite C (2009) Crowds and communities: light and heavyweight models of peer production. In: Proceedings of the 42nd Hawaii international conference on system sciences, Maui. IEEE Computer Society, Los AlamitosGoogle Scholar
  23. Haythornthwaite C, Andrews R (2011) E-learning theory and practice. Sage, LondonCrossRefGoogle Scholar
  24. Haythornthwaite C, Gruzd A (2012) Exploring patterns and configurations in networked learning texts. In: Proceedings of the 45th Hawaii international conference on system sciences. IEEE Computer Society, Los AlamitosGoogle Scholar
  25. Haythornthwaite C, Lunsford KJ, Bowker GC, Bruce B (2006) Challenges for research and practice in distributed, interdisciplinary, collaboration. In: Hine C (ed) New infrastructures for science. Knowledge production. Idea Group, Hershey, pp 143–166CrossRefGoogle Scholar
  26. Hollingshead AB, Fulk J, Monge P (2002) Fostering intranet knowledge sharing: an integration of transactive memory and public goods approaches. In: Hinds P, Kiesler S (eds) Distributed work: new research on working across distance using technology. MIT, Cambridge, pp 335–355Google Scholar
  27. Kelton K, Fleischmann KR, Wallace WA (2008) Trust in digital information. J Am Soc Inf Sci Technol 59(3):363–374CrossRefGoogle Scholar
  28. Klein JT (1996) Crossing boundaries: knowledge, disciplinarities, and interdisciplinarities. University Press of Virginia, CharlottesvilleGoogle Scholar
  29. Krackhardt D (1987) Cognitive social structure. Soc Netw 9:109–134MathSciNetCrossRefGoogle Scholar
  30. Macfadyen L, Dawson S (2010) Mining LMS data to develop an “early warning system” for educators: a proof of concept. Comput Educ 54(2):588–599CrossRefGoogle Scholar
  31. Moreland R (1999) Transactive memory: learning who knows what in work groups and organizations. In: Thompson L, Levine J, Messick D (eds) Shared cognition in organizations. Lawrence Erlbaum, Mahwah, pp 3–31Google Scholar
  32. Orlikowski WJ (2002) Knowing in practice: enacting a collective capability in distributed organizing. Organ Sci 13(3):249–273CrossRefGoogle Scholar
  33. Raymond ES (1999) The cathedral & the bazaar: musings on Linux and open source by an accidental revolutionary. O’Reilly, CambridgeGoogle Scholar
  34. Resnick P (2002) Beyond bowling together: sociotechnical capital. In: Carroll J (ed) HCI in the new millennium. Addison-Wesley, Boston, pp 247–272Google Scholar
  35. Schreurs B, De Laat MF (2012) Network awareness tool: learning analytics in the workplace: detecting and analyzing informal workplace learning. In: Proceedings of the learning analytics & knowledge conference, Vancouver. ACMGoogle Scholar
  36. Smith-Lovin L, McPherson M, Cook J (2001) Birds of a feather: homophily in social networks. Annu Rev Sociol 27:415–444CrossRefGoogle Scholar
  37. Suthers DD, Chu K-H (2012) Multi-mediated community structure in a socio-technical network. In: Proceedings of the learning analytics and knowledge conference, VancouverGoogle Scholar
  38. Suthers DD, Dwyer N, Medina R, Vatrapu R (2010) A framework for conceptualizing, representing, and analyzing distributed interaction. Int J Comput Support Collab Learn 5(1):5–42CrossRefGoogle Scholar
  39. Wenger E, Trayner B, De Laat MF (2011) Promoting and assessing value creation in communities and networks: a conceptual framework. Ruud de Moor Centrum, Open Universiteit, Heerlen. Available online at http://wenger-trayner.com/documents/Wenger_Trayner DeLaat Value creation.pdf

Recommended Reading

  1. Gruzd A, Haythornthwaite C (2011) Networking online: cybercommunities. In: Scott J, Carrington P (eds) Handbook of social network analysis. Sage, London, pp 167–179Google Scholar
  2. Haythornthwaite C, De Laat MF (2011) Social network informed design for learning with educational technology. In: Olofsson AD, Lindberg JO (eds) Informed design of educational technologies in higher education: enhanced learning and teaching. IGI Global, Hershey, pp 352–374Google Scholar
  3. Haythornthwaite C, De Laat M, Dawson S(eds) (2013) Learning analytics. Am Behav Sci, whole issue 57(10)Google Scholar
  4. Romero C, Ventura S, Pechenizkiy M, Baker RSJ (eds) (2011) Handbook of educational data mining. CRC/Taylor & Francis, Boca RatonGoogle Scholar
  5. Siemens G, Dragan G (eds) (2012) Learning and knowledge analytics. Educ Technol Soc 15(3):1–343Google Scholar

Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  1. 1.School of Information StudiesSyracuse UniversitySyracuseUSA

Section editors and affiliations

  • Talel Abdessalem
    • 1
  • Rokia Missaoui
    • 2
  1. 1.telecom-paristechParisFrance
  2. 2.Department of Computer Science and EngineeringUniversité du Québec en Outaouais (UQO)GatineauCanada