You are here:

Advancing a Complex Systems Approach to Personalized Learning Communities: Bandwidth, Sightlines, and Teacher Generativity ARTICLE

, Pepperdine University, United States

Journal of Interactive Learning Research Volume 26, Number 1, ISSN 1093-023X Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC


Educational technologies have advanced one of the most important visions of educational reformers, to customize formal and informal learning to individuals. The application of a complex systems framework to the design of learning ecologies suggests that each of a series of ten desirable and malleable features stimulates or propels the other ten, interacting to create important emergent properties, such as personalized learning communities (PLCs) or the powerful blending of individualization within community. This paper furnishes two examples of technologically-mediated learning environments that illustrate the interactivity of the ten features as constituent elements of higher order PLCs. One involves collaborative “what you see is what I see” network spaces that emphasize high bandwidth “sightlines” as entrée to a discussion of featural interactions and an emerging PLC. The other involves reliance on teachers as they participate in the user-generated content revolutions in society more generally. In this example, the entrée is creativity.


Hamilton, E. (2015). Advancing a Complex Systems Approach to Personalized Learning Communities: Bandwidth, Sightlines, and Teacher Generativity. Journal of Interactive Learning Research, 26(1), 89-104. Waynesville, NC: Association for the Advancement of Computing in Education (AACE). Retrieved August 22, 2018 from .

View References & Citations Map


  1. Bell, P. (2013). Using argument map representations to make thinking visible for individuals and groups. CSCL2: carrying forward the conversation, 449485.
  2. Bloom, B. (1984). The 2 Sigma Problem: the Search for methods of Group instruction as Effective as one-to-one tutoring. Educational Researcher, 13(6), 4-16.
  3. Bull, S., & Kay, J. (2013). Open learner models as Drivers for metacognitive Processes International Handbook of Metacognition and Learning Technologies (pp. 349-365): Springer.
  4. Fischer, G., & Scharff, E. (1998). Learning technologies in support of self-directed learning. Learning, 98, 4.
  5. Hamilton, E. (2005). Affective composites: autonomy and Proxy in Pedagogical agent networks. In J. Tao, J. Tan& R.E. Picard (Eds.), Affective Computing and Intelligent Interaction (ACII2005) (Vol. 3784, pp. 898-906).
  6. Hamilton, E. (2010). PrEDicatE Project: targeted research on teacher creativity at the intersection of content, Student cognition, and Digital media: award DUE104478, national Science Foundation.
  7. Hamilton, E. (2013). A cyber-ensemble of inversion, immersion, collaborative workspaces, query and media-making in mathematics classrooms: national Science Foundation award iiS-1321162.
  8. Wilensky, U., & Shapiro, B. (2003). Networked Participatory Simulations: Classroom Collaboration in Exploring the Dynamics of Complex Systems. Paper presented at the cScl 2003 (, Bergen, norway.

These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact