icons of evolution

Summary In his 2000 book Icons of Evolution, Jonathan Wells reviewed ten then-current biology textbooks for their treatment of what Dr. Wells calls the “icons” of evolution, well-known lines of evidence commonly used to support evolution. (Wells’s 2000 textbook review can be found online, here.) Now, in 2011, we present an updated 2011 textbook review that applies Wells’s evaluation criteria Read More ›

In Icons of Evolution, biologist Jonathan Wells compared icons of evolution –such as homology in vertebrate limbs– with published scientific evidence, and revealed that much of what we teach about evolution is wrong. Published in 2000, the book raised troubling questions about the status of Darwinian evolution that are still plaguing scientists today.

A friend of mine tells me that the only things he remembers about evolution from his high school biology course are photos of black and white peppered moths resting on light and dark tree trunks. They were presented as the classic case of Darwinian evolution in action, explaining how a trait that enhances survival could be acquired through an unguided Read More ›

On this episode of ID The Future we’re featuring the audio of a short video segment from the Icons of Evolution curriculum modules DVD. Antibiotic resistance is an example of natural selection acting on random mutation and is often referred to as one of the hallmark pieces of evidence for Darwin’s theory of evolution. Is it truly strong evidence supporting Read More ›

When students study Darwin’s theory of evolution, should they learn only about its strengths, or should they also hear about its weaknesses? And should they learn about the best current evidence for evolution, or should they study outdated examples that have been discredited by the scientific community? Those are the real issues Discovery Institute has raised with the Texas State Read More ›

British statesman Benjamin Disraeli is reputed to have said that there are “lies, damn lies, and statistics.” Statistics based on unbiased samples and rigorous analyses can point us in the direction of the truth; but statistics can also be unscrupulously manipulated to “prove” things that are patently untrue. Brown University biology professor Kenneth R. Miller demonstrates the latter in his Read More ›