Avida-Ed: Exploring Evolution in Silico
At the NABT Conference in Atlanta in the fall of 2007, Brad Williamson talked me and a few others who were loitering around to come to a workshop presentation on Avida-Ed software as a means of fostering inquiry of evolutionary processes. After the presentation, Brad suggested that I write a post about the experience. At the time, I didn’t have much to say.
Having had time to play around with Avid-Ed and to make my way through most of the unedited model lessons downloadable from the Avida-Ed website, I have decided to make the post. The best place to start is to download the software developed by Robert T. Pennock from the Avida-Ed website at Michigan State University, and to read the Discover magazine article written by Carl Zimmer highlighting Robert Pennock’s development and use of the research version of the software to study the process of evolution (The first activity below has pre-activity questions that require students to read this article). The links below will get you that far.
- Avida-Ed Website
- Testing Darwin by Carl Zimmer in February 2005 edition of Discover magazine.
If you are a self learner, after downloading the Avida-Ed, open it, drag the @ancestor into the black area of the Petri Dish window to the right, select the play button, and have fun. Otherwise, keep reading…
Well, as I said, I have had the time to make my way through the unedited model lessons posted on the Avida-Ed website. In effort to prepare to introduce my freshman honors biology and AP Biology student for the software, I have cut and pasted, edited, and created (in some cases) more detailed step-by-step instructions for the activities presented in their models lesson. In a few cases, I have even collected and attached data in a teachers section at the end of the student friendly documents that help you understand what the students will be doing prior to your own exploration of the software.
Explorations in Evolution Series
- I – Introduction to Avida-Ed
- II – Observing an Instance of Evolution in Avida-Ed
- III – How do Resource Availability & Mutation Rate influence Avidian Fitness?
- IV – Observing Mutations in the Genomes of Evolving Avidians
- V – Common Misconceptions of Evolution
I look forward to your comments and criticism of the activities but realize that I am just beginning to use these activities in my class for a second time.
As a justification for activities such as these, if you take the time to read the Bio2010 published by the National Academies as well as the most recent bulletin from HHMI (read Thinking like an Engineer and Add 56), you will quickly learn that we should be doing more to motivate our keen biology students to appreciate the importance of other scientific perspectives (mathematics, computer science, physic and engineering). Similarly, we should be reaching out equally to those that are already bent toward study in these other fields and show them that they can fulfill there interests while helping to make new discoveries in the biological sciences.
Download the non-education version of Avida.
Enjoy!
I appreciate your comments Harry and Brad, and am certainly not the one to judge whether working with Avida-Ed is just a “simulation” or an actual “instance of evolution.” Although I must say that this in itself makes a great topic of discussion…
I would very much appreciate learning of any real laboratory experiments that I could implement in which my student could witness evolution in action whether the data is messy or not, with the realization of the time and conent constraints of the AP Biology curriculum.
Otherwise, in response to Brad I was out of the classroom with sick children both days the students worked through the first four assignments and we spent today discussing their results and conclusions.
I only wish that felt I could devote more time to inquiry with this educational tool. For example, I jokingly told my students that during their next test I would give them time to evolve an avidian that could complete one of the more complex functions given their knowledge of Avida-Ed, natural, and artificial selection and that the one who evolved the function in the fewest number of generations would get the A and I would work down from there…
Nice report Eric. I’ll be anxious to hear about your students work with Avida-Ed this year.
HarryK…..
Actually, working in Avida or Avida Ed is actually doing experiments. Both pieces of software are experimental, evolutionary environments—they are not simulations. What’s the difference? In a simulation the investigator or author generally uses mathematical function(s) and perhaps a bit of stochastic process to model a natural situation–valuable tools in themselves but generally the results are predictable within a range of parameters. Alternatively, the simulation may be based on agent-based programming where the results are a bit less predictable and perhaps more surprising. Both agent-based models and function based models have their place in education and in research. You’ve alluded to some of the possible limitations though I think you overstate the case for “… help students learn what those scientists believe inasmuch as those beliefs are well-captured in the software.” It’s my contention that mathematical modelling should be an essential component of science education just so that students can learn the limitations as well as their power mathematical/computer models.
Avida, though, is different. It is a sophisticated artificial life computer environment that can evolve given certain parameters. This is not just an exercise in semantics. Avida creates a Darwinian computer environment where evolutionary theory can be tested in computer time rather than geological time. Rather than organisms interacting with themselves and their environment, Avida has bits of computer code as “organism” that mutate, reproduce and compete for limited computer processing time. Every run is different and Avida has actually produce novel new adaptations. Unlike nature you can replay scenarios making it easier to test hypotheses. Avida and similar computer environments are simply the empirical environment where you’ll find much of the research in experimental evolutionary biology is carried out today. In fact some of those scientist that were working primarily with organisms have largely switched to the Avida environment. Students who work with Avida Ed will be working in essentially the same experimental system (with a more student friendly interface added) as some of today’s best experimental evolutionary biologists. Which of course implies that given sufficient sophistication in their experimental exploration and sufficient analysis they too could not just “confirm” theory but discover new principles.
BW
Check out this summer’s paper for more ideas on how to use this tool in the classroom:
Using Avida-ED for Teaching and Learning About Evolution in Undergraduate Introductory Biology Courses, July 23rd, 2009
by Bray Speth, Elena; Long, Tammy M.; Pennock, Robert T.; Ebert-May, Diane
in the journal: Evolution Education and Outreach
From what I see in a short exploration, Avida-Ed is a very nice simulation. Of course, it’s not a lab. It presents what some scientists say will happen under the simulated conditions and so will help students learn what those scientists believe inasmuch as those beliefs are well-captured in the software.
Looks like a good learning tool. When you use it, be sure to emphasize that it’s only one group’s approximation of what might happen if you really did these experiments. If you did them for real, you might end up with very different results but would likely (but not certainly) come to the same conclusions. Of course, real experiments have uncertainty for a number of reasons. The simulations clear away those uncertainties and so provide an alternative (and nicely interactive approach) to textbooks and videos. In all of these cases, a sophisticated person will now the results ahead of the experience.
Here’s yet another quality learning tool on the non-lab side of your science courses. Be sure to expose your students to enough real-world lab experience so that they will encounter ambiguous data with errors that must be explained.