Connecting Genetics and Evolution with 3D Learning
Allele, gene, heterozygous, phenotype, polygenic trait, recessive, dominant . . . The list of terms—and facts that go with them—goes on and on. Much of traditional biology has been taught and learned as a giant vocabulary lesson along with a history of discoveries to be memorized. And as scientific research progresses, more discoveries and vocabulary are added. Is it any wonder that biology textbooks have expanded to over 1,000 pages? In this formulation, biology lessons come to resemble a lifeless catalog more than a science brimming with scenarios for investigation.
The Connected Biology project, a collaboration funded by the National Science Foundation between Michigan State University (MSU) and the Concord Consortium, is developing a technology-enhanced curriculum aligned to Next Generation Science Standards (NGSS) designed to teach high school biology as a coherent set of interlinked and powerful reasoning scenarios. Our goal is to help students explore biological mechanisms, as opposed to memorizing facts and terms coined from past discoveries.
An understanding of biological mechanisms is fundamental to being able to reason about biological phenomena. For example, consider the mechanism underlying the influence of genes on traits. Genes are molecular-level instructions for building large, complex molecules (proteins and RNA) that play an important role in cells. Cells carry out specific functions based on the proteins produced by a subset of the organism’s genome. Depending on the information encoded in the genetic instructions, those complex molecules may function well, poorly, not at all, or simply differently. Over eons of time, these ongoing, varied results produce the myriad life forms on our planet. The underlying mechanisms are key in being able to reason about important topics—from the diversity of life to addressing genetic diseases to meeting ecological challenges.
Such mechanisms play out in and across every level of biology from molecules to populations. In fact, many subfields of biology were originally defined by different levels of scale: microbiology, genetics, molecular biology, behavioral biology, ecology, population biology, phylogenetics, and more. The cause and effect relationships throughout these levels have great explanatory power and form a framework for thinking and reasoning about biology that has led to a blending of these subfields. This same framework can be used in the classroom so that students, too, can experience biology as a coherent field rather than a set of topics investigated in isolation.
A series of “Evo-Ed” cases, developed originally at MSU for undergraduate-level teaching, provide compelling real-world examples of how genetic and evolutionary processes are interlinked. Six different phenomena—from lactose metabolism in humans to toxin resistance in clams, to variations in mouse fur color, and more— were chosen based on the research that has illuminated the phenomena across levels. We understand the mechanism at each level of these cases, which trace the emergence of new phenotypes from their origination in a DNA mutation to the production of different proteins to the effects on cells and finally to the development of stable, alternate macroscopic traits in reproductively isolated populations.
Using these cases, the Connected Biology project is currently developing a Multi-level Model (MLM) to help high school students connect both visible and invisible events into a causative chain across levels—with the ability to “zoom” in and out of the population, organism, cell, and molecular levels. Students start with an observable phenomenon such as an organism’s trait at the visible level and view the trait alongside the “next level down,” a representative cell that produces the trait or a central aspect of the trait. They can also view one level up to see how different versions of the trait affect a population of individuals, or how a changing environment can influence the expression of a trait. In the case of the beach mouse, for instance, students explore the multiple, linked levels underlying the phenomenon of differing fur colors (Figure 1), and are challenged to deduce the events that produce variation in fur color.
Fur colors of several beach mouse subspecies in the southeastern United States range from light to very dark and are correlated with the color of each subspecies’ environs. At the cell level, students discover that the fur-producing cells make two different shades of the pigment melanin and that various substances can affect the balance between them. Looking at the molecular level, they find that in the mice with light fur, the signal to make dark melanin is not received by the fur-making cells, due to a non-functional protein receptor. Comparing the gene for the receptor in the two types of mice, they find a mutation that changes the protein so that it no longer transmits the signal in the light-colored mice. As we follow the fur color differences into the population level of the MLM, students explore the dependence of fur color variation on genetic inheritance of the mutation, and examine how over long periods of time, predation leads to the separation of subspecies via natural selection.
The integrative approach of this case enables students and teachers to focus on one phenomenon via the mechanisms that produce it across multiple, linked levels. In addition to the NGSS disciplinary core ideas and performance expectations outlined in Table 1, students engage in the practices of analyzing and interpreting data and constructing scientific explanations in the context of the crosscutting concepts of patterns and cause and effect. The MLM’s computer-based simulations make invisible events accessible and explorable, and allow students to view or control a phenomenon at one level and observe the outcome on another level, in order to integrate understanding across levels.
We are exploring how materials designed to support three-dimensional learning can promote growing complexity in student understanding of the linked ideas of evolution, traits, and their underlying molecular mechanisms. Our research hypothesis is that multiple representations of phenomena will help students connect observable phenomena to both causative and resulting events occurring on widely varying scales—from sub-microscopic to population level—and help them develop an understanding of the scientific concepts underlying each phenomenon.
We hope that delving into the chains of causation across multiple real-world phenomena explored through interesting cases will increase students’ familiarity with each level of the chain of events, and that as they reason their way through these mechanisms, they will learn to recognize the interlinked levels at work in all of biology.
Frieda Reichsman (email@example.com) is a senior research scientist.
This material is based upon work supported by the National Science Foundation under grants DRL-1620910 and DRL-1620746. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.