Addressing such problems is not for the faint of heart and depends critically on the culture of the department and institution in which one finds oneself (as well as one’s position in the hierarchy). Perhaps counterintuitively, a rigorous learning-goal analysis can lead to what appears to be a simplification of the materials presented, with the goal of producing a deeper, more rigorous and more confident understanding of key ideas. Consider, for example, gene expression. A thorough understanding of this process includes the thermodynamic factors involved in protein-protein and protein-nucleic acid interactions, the general effects of post-transcriptional and post-translational modifications, the stochastic and cooperative nature of the interactions that regulate transcription, RNA processing, transport, translation, the localization of gene products, the assembly of macromolecular complexes, the turn-over of RNAs, polypeptides and proteins, the repair of DNA and the geometric factors that regulate DNA’s accessibility (epigenetics). From this perspective, for example, what is important about miRNA activity is not the details of miRNA processing but the fact that miRNAs (primarily) regulate mRNA stability and translation, a role (and in fact a mechanism) not conceptually distinct from that played by various proteins (a similarity rarely appreciated by students). A rigorous and confident understanding of the molecular underpinnings of gene expression prepares the student to approach more complex issues, such as making informed predictions about the effects of mutations and the behavior of the regulatory networks involved in adaptation, homeostasis and a wide range of processes from embryonic development to immune and nervous system function. But how many programs prepare students to even consider the noise inherent in gene expression and molecular behavior? And how many students howl in disbelief (or even recognize the error) when biological processes are displayed as deterministic, as is often the case, for example, in video presentations of various polymerization processes?
So how do we take science education seriously? I suggest that, just as in a scientific experiment, we must establish objective and informative assays and use the results of those assessments to provide feedback that serves to develop, constrain and redirect our learning goals. This is a contagious behavior, since it tends to infect other courses both within and beyond a particular department. If the learning goals in the biological sciences demand and depend upon an understanding of molecular-level phenomena, then we are within our rights to demand that the mathematics, physics and chemistry courses we require our students to take address these concepts. Within a departmental context, it is critical to present this type of analysis not as a critique of current teaching but as an opportunity to think seriously about the educational system in a scientific (that is, skeptical) manner. Effective change is likely to be evolutionary, not revolutionary; it will take a number of cycles of reflection based on informative assessment to achieve and continuing assessment to maintain a rigorous, welcoming and effective science education system. To paraphrase Socrates, perhaps we can come to appreciate that the unexamined course is not worth sitting through.
1. Committee on Science, Engineering, and Public Policy (2010) Rising above the gathering storm, revisited: rapidly approaching category 5. National Academies Press.
2. Alberts, B. (2010) Prioritizing science education. Science 328, 405.
3. Editorial. 48th Is Not a Good Place. The New York Times. Oct. 26, 2010.
4. Editorial. Why we’re failing math and science: a panel of experts talks about what’s wrong with our education system – and how to fix it. The Wall Street Journal. Oct. 26, 2010.
5. Powell, K. (2003) Science education: spare me the lecture. Nature 425, 234 – 236.
6. McClymer, J. F., and Knowles, L. Z. (1992) Ersatz learning, inauthentic testing. J. Excell. Coll. Teaching 3, 33 – 50.
7. Klymkowsky, M. W., Taylor, L. B., Spindler, S. R., Garvin-Doxas, R. K. (2006) Two-dimensional, implicit confidence tests as a tool for recognizing student misconceptions. J. Coll. Sci.Teach. 36, 44 – 48.
Mike Klymkowsky (firstname.lastname@example.org) is a professor of molecular, cellular and developmental biology and co-director of CU Teach at the University of Colorado, Boulder.