Glossary
- Formal, Nonformal, and 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
- Homophily:
-
Similarity between actors, for example, in race, gender, education, and attitudes
- Adaptive Structuration:
-
The negotiation and continuous emergence of practices around technology use and group needs
- Socio-Technical Capital:
-
Social capital associated with managing and prospering through the use of information and communication technologies
- Absorptive Capacity:
-
Ability of a network to capitalize on new knowledge
- Technological Guru:
-
An actor who facilitates the recognition and integration of new knowledge into group practice
...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Benkler Y (2006) The wealth of networks: how social production transforms markets and freedom. Yale University Press, New Haven
Borgatti SP, Cross R (2003) A relational view of information seeking and learning in social networks. Manag Sci 49(4):432–445
Budhathoki N, Haythornthwaite C (2013) Motivation for open collaboration: crowd and community models and the case of OpenStreetMap. Am Behav Sci 57(5): 548–575
Burt R (1992) Structural holes: the social structure of competition. Harvard University Press, Cambridge
Cohen WM, Levinthal DA (1990) Absorptive capacity: a new perspective on learning and innovation. Adm Sci Q 35:128–152
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 York
Daly AJ (ed) (2010) Social network theory and educational change. Harvard Education Press, Cambridge
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):736–752
Dawson S, Bakharia A, Lockyer L, Heathcote E (2011) ‘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
Dawson S, Macfadyen LP, Lockyer L, Mazzochi-Jones D (2011a) Using social network metrics to assess the effectiveness of broad based admission practices. Australas J Educ Technol 27(1):16–27
Dawson S, Pei-Ling Tan J, McWilliam E (2011b) Measuring creative potential: using social network analysis to monitor and develop learners’ creative capacity. Australas J Educ Technol 27(6): 924–942
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. IEEE
DeSanctis G, Poole MS (1994) Capturing the complexity in advanced technology use: adaptive structuration theory. Organ Sci 5(2):121–47
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 145–176
Granovetter MS (1973) The strength of weak ties. Am J Sociol 78:1360–1380
Gruzd A (2009) Studying collaborative learning using name networks. J Educ Libr Inf Sci 50(4):243–253
Hansen MT (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Adm Sci Q 44:82–111
Haythornthwaite C (2002a) Strong, weak and latent ties and the impact of new media. Inf Soc 18(5):385–401
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 159–190
Haythornthwaite C (2005) Social networks and internet connectivity effects. Inf Commun Soc 8(2):125–147
Haythornthwaite C (2006) Articulating divides in distributed knowledge practice. Inf Commun Soc 9(6):761–780
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 Alamitos
Haythornthwaite C, Andrews R (2011) E-learning theory and practice. Sage, London
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 Alamitos
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 143–166
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 335–355
Kelton K, Fleischmann KR, Wallace WA (2008) Trust in digital information. J Am Soc Inf Sci Technol 59(3):363–374
Klein JT (1996) Crossing boundaries: knowledge, disciplinarities, and interdisciplinarities. University Press of Virginia, Charlottesville
Krackhardt D (1987) Cognitive social structure. Soc Netw 9:109–134
Macfadyen L, Dawson S (2010) Mining LMS data to develop an “early warning system” for educators: a proof of concept. Comput Educ 54(2):588–599
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 3–31
Orlikowski WJ (2002) Knowing in practice: enacting a collective capability in distributed organizing. Organ Sci 13(3):249–273
Raymond ES (1999) The cathedral & the bazaar: musings on Linux and open source by an accidental revolutionary. O'Reilly, Cambridge
Resnick P (2002) Beyond bowling together: sociotechnical capital. In: Carroll J (ed) HCI in the new millennium. Addison-Wesley, Boston, pp 247–272
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. ACM
Smith-Lovin L, McPherson M, Cook J (2001) Birds of a feather: homophily in social networks. Annu Rev Sociol 27:415–44
Suthers DD, Chu K-H (2012) Multi-mediated community structure in a socio-technical network. In: Proceedings of the learning analytics and knowledge conference, Vancouver
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):5–42
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
Gruzd A, Haythornthwaite C (2011) Networking online: cybercommunities. In: Scott J, Carrington P (eds) Handbook of social network analysis. Sage, London, pp 167–179
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 352–374
Haythornthwaite C, De Laat MF, Dawson S (eds) (forthcoming) Learning analytics. Am Behav Sci, whole issue
Romero C, Ventura S, Pechenizkiy M, Baker RSJd (eds) (2011) Handbook of educational data mining. CRC, Boca Raton/Taylor & Francis
Siemens G, Dragan G (eds) (2012) Learning and knowledge analytics. Educ Technol Soc 15(3), whole issue, pp 1–343
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this entry
Cite this entry
Haythornthwaite, C. (2014). Learning Networks. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6170-8_67
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6170-8_67
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6169-2
Online ISBN: 978-1-4614-6170-8
eBook Packages: Computer ScienceReference Module Computer Science and Engineering