|False truths will fall like autumn leaves?|
In his book, The Believing Brain, Michael Shermer presents quite a different view.
According to Shermer, beliefs come from a variety of "...subjective, personal, emotional, and psychological reasons in the context of environments created by family, friends, colleagues, culture, and society at large."
Many beliefs formed in this way—for example, beliefs about evolution or global warming—may be severely at odds with widely accepted scientific theory and observations.
The recently publicized speech by Paul Broun, a physician and member of the U.S. House of Representatives' Committee on Science, Space and Technology, is a good example of this type of belief. In his speech to Liberty Baptist Church in Hartwell, Georgia, Rep. Broun said that he believes the Earth is 9,000 years old and the Big Bang theory, evolution, and embryology are lies planted by the Devil to challenge faith in God.
Discovery-based lessons on Earth science, cosmology, natural selection, and development of organisms are not likely to change Mr. Broun's beliefs.
The problem, according to Shermer, is that believers—in particular, bright believers—"...after forming [their] beliefs...then defend, justify, and rationalize them with a host of intellectual reasons, cogent arguments, and rational explanations. Beliefs come first, explanations for beliefs follow."
In The Believing Brain, Shermer presents a wealth of neuroscience and evolutionary evidence that supports his view. Central to his thesis is evidence that natural selection has imbued humans with the propensity to see patterns in just about everything they encounter. Stars in the sky look like mythical beings. Clouds look like locomotives and cartoon characters. Patterns of light and color in a thicket look like a cougar ready to pounce.
Thus, according to Shermer, humans were "over-designed" in the wild to see patterns so that they can avoid discounting mortal threats that are really there.
However, pattern recognition alone is insufficient to protect humans from threats. Patterns must also be imbued with meaning, intention, and agency (recognized patterns have the ability to do something). The cougar-like pattern in the thicket may be a real cat eyeing its next meal.
This is where humans get into trouble. When patterns have been recognized and rational explanations are not readily available, humans fill the void with what is available. When young, in times of distress, or when revelatory experiences occur, religious explanations may suffice. If predisposed to fear, evilness and conspiracies become attached to the patterns. Likewise, liberals, conservatives, greens, and libertarians seek predictable explanations for the patterns they see.
Technological progress, itself, fuels how humans explain patterns. Where humans saw devils, ghosts, and sprites inflicting maladies a few centuries ago, they now see aliens in sophisticated spacecraft causing the same problems.
|Roosting explanations get too big to kick out of the nest.|
Shermer posits that science is the best tool humans have to confront our beliefs and separate fact from fantasy, reality from illusion, and emotionally preferred confirmatory evidence from data that challenges treasured beliefs.
The challenge for educators is to teach habits of scientific thinking while being sensitive to the emotionally charged beliefs of learners. This sensitivity may involve helping learners deal with the emotional resistance that comes from critically weighing the evidence that forms the foundations of one's beliefs.
Hypothesis development, data gathering, analysis, and submitting articles for peer review are not the only skills of thoughtful scientists. Submitting oneself to critical analysis and integrating the implications of scientific findings into one's concept of self and the world are central to the instruction of scientific habits of mind. Educators need to pay attention to creating the whole scientist rather than just teaching disembodied skills and concepts.
About the AuthorsScience Approach and principal investigator on its VoxelDiscovery 5-8 project.
Mary Moore is an instructional developer on Science Approach's VoxelDiscovery 5-8 project.