ABSTRACT
Evolution, and how to teach it, is perhaps the most controversial topic in American schools today. Biologists attest to the ubiquity of evolution, and assert that evolutionary explanations undergird their entire science and are of fundamental import. Yet, according to recent surveys (Gallup, 2008), 44% of Americans say they do not accept evolution in any form, and a shockingly small number, only 14%, say they believe in naturalistic evolution. A century and a half after the publication of The Origin of Species, there remains considerable cultural resistance to teaching this “controversial” subject in schools. Many explanations have been proffered for this disconnect between scientific consensus and citizen acceptance. Prominent among these explanations is that conflict with religious belief is the principal cause of objections to evolution (Numbers, 1992; Scott & Branch, 2003; Witham, 2002; Evans, 2001). While acknowledging the importance of religious objections, this chapter proceeds from the assumption that another major cause of rejection of evolution is the cognitive difficulty of understanding the evolutionary process. In this regard, we place evolution in a class of processes known as emergent pro cesses that are notoriously difficult for people to understand (Centola, Wilensky, & McKenzie, 2000; Penner, 2000; Resnick & Wilensky, 1993; Wilensky, 2001; Wilensky & Centola, 2007; Wilensky & Resnick, 1999; Centola, McKenzie, & Wilensky, 2000). Indeed the history of science is replete with scientific knowledge claims that came into sharp conflict with religious beliefs. To take one example, the claim that the Earth is not flat but spherical, which was put forth by the Greeks and Indians before the advent of Christianity, was met with Christian religious objections in the Middle Ages as it conflicted with biblical verses about “the four corners of the earth.” As late as the 19th century, even scientists such as William Carpenter (1871) and Samuel Rowbotham (1865) published proofs of a flat Earth. Yet these objections eventually subsided. Now, except for a few fringe “flat earthers,” religious and non-religious alike accept the spherical Earth and are not bothered by the “four corners.” How did this
change in beliefs come about? Major factors in fostering this change of attitude were new technologies that enabled us to view the Earth from afar and other celestial bodies from up-close. For those of us old enough to have been conscious in 1969, how can we forget the first color photographs of the Earth from space taken by Apollo astronauts and published in Life magazine (Figure 10.1)? The new technologies made vivid to our eyes the roundness of the Earth. Is it possible to develop a technology that would make equally visible and vivid the process of evolution? In this chapter we present a sample collection of computer models from a larger “curriculum” of computer-based activities called BEAGLE (Biological Experiments in Adaptation, Genetics, Learning and Evolution), in which we attempt to do just that-to use the computational technology to enable us to “see” evolution in action. Technologies such as telescopes and spaceships are able to compress space, enabling us to
encompass large distances and faraway objects in a single view. Similarly, computational technologies enable us to compress time, so that large stretches of evolutionary time can be seen in a single viewing. Computerbased models of evolutionary processes provide a “sandbox” for students to experiment with mechanisms and analyze the outcomes that lead to population change over many generations. Our unfamiliarity with “deep time” (Gee, 2000) is one important component of what makes evolution difficult to comprehend. Ever since the late 1700s when Scottish geologist James Hutton described the seemingly infinite stretches of geologic time (see Taylor, 2006), there has been widespread incomprehension of this vastness. In 1805, Hutton’s colleague John Playfair said: “the mind seemed to grow giddy by looking so far into the abyss of time.” Deep time is certainly one important barrier to comprehension of evolution. But there is another important factor that we believe is an even greater impediment. Evolution is a process that works on populations. Gene frequencies in a population change as a result of the variation in competitive advantage of individual traits. Processes where changes occur at one level, but subsequently lead to aggregate outcomes and changes at a higher level (e.g., phenotype results from interaction of genes, population levels result from interactions of individual organisms, and speciation results from interaction of populations), are known as emergent phenomena (Penner, 2000; Wilensky, 2001; Wilensky & Resnick, 1999). In previous work (Resnick & Wilensky, 1993; Wilensky, 1997b, 1999b; Wilensky & Resnick, 1999) we have shown that emergent phenomena are particularly hard for people to reason about. Commonly people “slip between levels” (Levy & Wilensky, 2008; Sengupta & Wilensky, 2009; Wilensky, 2001; Wilensky & Resnick, 1999), attributing properties of the individual to the population and vice versa. For example, if a colony of ants exhibits intelligent foraging behavior, we commonly attribute that intelligence to the individual ants. But this is a misattribution-science has shown that in fact while ant colonies are efficient at gathering food, individual ants are not. It’s through the accumulation of the actions and interactions of many ants, each with simple behavior, that we get the emergent intelligence of the colony (Holldobler & Wilson, 1991; Robson & Traniello, 1995; Sudd, 1957; Wilson, 1971). This slippage between the level of the ant colony and the level of the individual ant is a prototypical example of how people so easily slip between different levels of an emergent phenomenon or complex system. Evolution, itself an emergent process, engenders these same cognitive difficulties. Like other emergent phenomena we have studied, we would expect students of evolution to encounter the same cognitive difficulties reported with these other emergent phenomena. Indeed, we have seen the levels slippage described above when students reason about emergent phenomena. For example, if students are told that a population of dinosaurs evolves into a population of birds, by the levels slippage, they envision that this means that an individual dinosaur must morph into a bird. But such a morphing is
clearly absurd. By this implicit reductio ad absurdum, they conclude that evolution of species cannot be true.
