The Avida-ED Project

 


Technology for Teaching Evolution and
the Nature of Science using Digital Organisms

Robert T. Pennock

 

 

I am currently completing the final year of a 3-year +1-year NSF-funded project to develop a digital evolution educational software platform for use in biology courses. My co-PIs on the project are Charles Ofria, Richard Lenski, and Diane Ebert-May.

UPDATE 2/15/06: Avida-ED is discussed in the 10 Feb. 2006 issue of Science.

UPDATE 10/1/06: Avida-ED is now in the formal classroom phase and should be ready for national distribution in the Spring.  If you are an instructor interested in using Avida-ED in your course, please contact me at <pennock5{at}msu.edu>.

UPDATE 6/19/07: Avida-ED officially introduced and publically released at the Society for the Study of Evolution meeting in Christchurch, New Zealand.

To download please go to our new (and still very rough) public site.
Avida-ED Home Page

 

Project Background

Although evolutionary theory is the fundamental explanatory principle in biology, it continues to be widely misunderstood and even rejected by a majority of Americans. In a recent poll, only 29% agreed that evolution was “mostly accurate” or “completely accurate”. The remaining 71% said it was “mostly not accurate,” “completely not accurate,” “not sure” or “might or might not be accurate, you can never know for sure.” [1] A college education improves understanding, but not as much as one would hope; in another poll, 32% of students answered “no” to the question “Do you think that the modern theory of evolution has a valid scientific foundation?” [2] Particularly disturbing is the finding that nearly 40% of high school biology teachers think “there are sufficient problems with the theory of evolution to cast doubts on its validity” [3].

Even students who accept the validity of evolution in general turn out to have many specific misconceptions about it. For instance, students commonly think that the environment itself causes traits to change in an organism over time. They do not view genetic variation as important. They think that all individuals slowly change in their traits over time, rather than recognizing evolution as involving changes in populations of individuals with discrete traits [4].

As Theodosius Dobzhansky famously observed, “Nothing in biology makes sense except in the light of evolution.” [5] National standards thus properly emphasize the centrality of evolution as a major unifying theme in the science curriculum as well as the overarching importance of understanding the nature of science [6]. There is also a significant trend in science education to get students involved in inquiry-based and active learning as a better way for them to learn scientific methods of inquiry [7]. However, the evolutionary process is difficult or impossible to demonstrate in the classroom. Our project aims to solve this problem and meet this need by adapting an established artificial life research platform for use as a novel educational tool.

Artificial life research is a core area of what has become an exciting cross-fertilization between evolutionary biology and computer science and engineering. Computer scientists and engineers, inspired by the workings of evolution in nature, realized that they could apply the same powerful Darwinian mechanism in computers for their own purposes, such as for complex industrial design. This technology has recently progressed to the point that biologists can use it for their own research. One of the most advanced artificial life systems is known as Avida, and it has become the platform of choice for certain difficult questions in experimental evolution. We believe that this digital evolution platform can also now become a revolutionary new educational tool that can help undergraduate students—our future researchers and teachers—understand and appreciate not only the power of the evolutionary mechanisms to produce biocomplexity, but also the nature of scientific reasoning itself.

Observing evolutionary design is scarcely feasible in a natural system, but it can occur on very short time scales in the digital environment of Avida. This makes it possible for the first time for students to run evolution experiments in a laboratory course. Students can explore, observe, and test evolutionary concepts in a game-like computational environment, allowing them to gain first-hand experience on a topic that might otherwise seem quite abstract. With evolutionary methods, students can learn to manipulate complex systems and observe their emergent properties. Guided exercises built around such inquiry-based experiments can also help students learn about the nature of scientific evidence and reasoning and come to understand that evolution by natural selection not only has a valid scientific foundation, but is exemplary as a well-confirmed, powerful scientific principle.

• REFERENCES
1. People for the American Way Foundation, 2000. Evolution and creationism in public education: an in-depth reading of public opinion. http://www.pfaw.org/issues/education/creationism-poll.pdf
2. Lord, T., and S. Marino. 1993. How university students view the theory of evolution. Journal of College Science Teaching. 22:353-357.
3. Eve, Raymond A. and D. Dunn. 1990. "Psychic powers, astrology and Creationism in the classroom? Evidence of pseudoscientific beliefs among high school biology and life-science teachers." The American Biology Teacher 52 (Jan.): 10-21.
4. Alters, B., C. Nelson. 2002. Perspective: Teaching Evolution in Higher Education. Evolution. (Vol. 56, No. 10, pp. 1891-1901)
5. Dobzhansky T. 1973. Nothing in biology makes sense except in the light of evolution. The American Biology Teacher 35: 127-9
6. National Academy of Science. 1998. Teaching about Evolution and the Nature of Science. Washington DC, The National Academies Press
7. National Research Council. 2000. Inquiry and the National Science Education Standards. Washington DC, The National Academies Press

Fig. 1: A view in the virtual Petri dish. The population viewer allows the user to monitor the population's fitness, genotype distribution, metabolic rate, and other characteristics.

Fig. 2: The Organism Viewer shows an animation of the execution of a digital organism's genome.


Created 5/27/04. Last updated 10/23/07.
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