CCST9048 Scientific and Technological Literacy
Simplifying Complexity

[This course is under the thematic cluster of ‘Sustaining Cities, Cultures, and the Earth’.]

Course Description

This course will introduce the concept of complexity examining both the methods used in complexity science and examples of complexity found in nature and everyday life. Complexity science is an interdisciplinary field that seeks to explore the behaviour of strongly interacting systems made of simple components with no central control. It represents a new framework for science as a departure from a reductionist or “bottom-up” framework in favour of a “top-down” or systems level framework. We will explore the story of Mandelbrot and the beautiful patterns of fractals. An introduction of chaos will show how scientific measurement and prediction can fail even in simple examples. We will show how patterns can emerge and discuss the concept of computational irreducibility and computational equivalence with a study of cellular automata. With the tools of networks we will see the role of science in dealing with global issues such as the intricate relationships between humanity and the global environment. We will explore our everyday lives through the study of social networks, learning and urban ecology. Finally, this course will bring us to the frontiers of sciences as we learn how complexity shapes our current understanding of the global climate, ecological characteristics and animal behaviours.

Course Learning Outcomes

On completing the course, students will be able to:

  1. Identify complexity in the global society in multiple fields ranging from biology to physics.
  2. Utilize the methods of complexity theory to propose possible solutions to unsolved problems.
  3. Explain the key differences between systems based approaches and reductionism.
  4. Evaluate how complexity is shaping the interaction between humanity and the global environment.

Offer Semester and Day of Teaching

First semester (Wed)

Study Load

Activities Number of hours
Lectures 24
Tutorials 10
Reading / Self-study 24
Assessment: Problem sets (incl preparation) 25
Assessment: Essay / Report writing 30
Assessment: Presentation (incl preparation) 10
Assessment: Portfolio 20
Total: 143

Assessment: 100% coursework

Assessment Tasks Weighting
Problem sets 35
Portfolio 15
Final project presentation and research report 40
Class discussion 10

Required Reading

Mitchell, M. (2009). Complexity: A guided tour. Oxford; New York: Oxford University Press.

Recommended Reading

  • Barabási, A. -L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512. 
  • Barabási, A. -L., &  Zoltán, N. O. (2004). Network biology: Understanding the cell’s functional organization, Nature Reviews Genetics, 5(2), 100.
  • Bassett, D. S., & Bullmore, E. (2006).  Small-world brain networks. Neuroscientist, 12, 512.
  • Crutchfield, J. P., Farmer, J. D., Packard, N. H., & Shaw, R. S. (1986, December). Chaos. Scientific American, 255, 46-58.
  • Gardner, M. (1970, October). Mathematical games: The fantastic combinations of John Conway’s new solitaire game “life”. Scientific American, 120-123.
  • Horgan, J. (1995). From complexity to perplexity. Scientific American, 272(6), 104. 
  • Kauffman, S. A. (1993).  The origins of order: Self organization and selection in evolution. New York: Oxford University Press.
  • Kleinfeld, J. S. (2002). The small world problem. Society, 39(2), 61-66.
  • Leff, H. S., & Rex, A. F. (1990). Maxwell’s demon entropy, information, computing. Bristol: Adam Hilger. 
  • Mandelbrot, B. (1967). How long is the coast of Britain? Statistical self-similarity and fractional dimension. Science, 156, 636-638.
  • Milgram, S. (1967, May). The small-world problem. Psychology Today, 1(1), 61-67.
  • Montoya, J. M., & Soleda, R. V. (2002). Small world patterns in food webs. Journal of Theoretical Biology, 214, 405-412.
  • Shannon, C. E., Weaver, W., & Wiener, N. (1950). The mathematical theory of communication. Physics Today, 3(9), 31. 
  • Watts, D. J., & Strogatz, S. H. (1998).  Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440.
  • West, G. B., Brown, J. H., & Enquist, B. J. (1999). The fourth dimension of life: Fractal geometry and allometric scaling of organisms. Science, 284(5420), 1677-1679. 

Course Co-ordinator and Teacher(s)

Course Co-ordinator Contact
Dr T.D. Wotherspoon
Faculty of Science
Tel: 3917 5420
Teacher(s) Contact
Dr T.D. Wotherspoon
Faculty of Science
Tel: 3917 5420
Dr T.K. Kwong
Deparment of Mathematics, Faculty of Science
Tel: 2857 8579
Dr T.C. Bonebrake
School of Biological Sciences, Faculty of Science
Tel: 2299 0675 / 3917 7830