Genetics Computer Teaching Simulation Programs: Promise and Problems/Response for GENETICS

By Sved, J. A.; Ruedi, Elizabeth A. et al. | Genetics, August 2010 | Go to article overview

Genetics Computer Teaching Simulation Programs: Promise and Problems/Response for GENETICS


Sved, J. A., Ruedi, Elizabeth A., Hawley, R. Scott, Genetics


COMPUTER programs that simulate genetics results can play a useful role in teaching the principles of genetics, but some people have argued that such programs have generally not fulfilled their initial promise to engage students. I discuss some of the reasons for this shortfall on the basis of my experience in writing and distributing the "Hands On Genetics" programs (http://www.handsongenetics.com).

It is well accepted that the principles of genetics cannot easily be learned only from lectures, even with excellent descriptive textbooks. Although the evidence for this conclusion is largely anecdotal, there are some objective studies that support this view (e.g., Stewart et al. 1992; Hickey et al. 2003; Pukkila 2004). The question thus becomes: What additional activities are required to transmit the basic concepts of genetics in an introductory course?

Two activities can be invaluable supplements to lectures: direct experience from practical classes and problem solving. Computer simulation should assist implementation of both activities. Some experiments, particularly those involving Mendelian genetics, are amenable to simulation. Complete crossing programs that are impossible in live organisms can be carried out rapidly at almost no cost. Problems can also be posed in connection with such simulations in such a fashion that that each student can receive a different set of questions. Although there has been some acceptance of instructional software for genetics, it is not clear that it has transformed learning. Here I reviewmy experiences with computer-based genetics education.

Simulation programs can be of many types. Here I describe two different types of simulation from the "Hands On Genetics" programs (http://www.handson genetics.com). These programs run under Windows and Macintosh (Classic OS only). Further technical details about the programs are included in the supporting information, File S1.

My vision for these programs was to achieve interactivity between the user and the software. Having learned genetics in the precomputer age, my hope was that the old-fashioned way of learning and thinking- with a pencil in hand-might be replaced by creativity with a mouse in hand, moving objects (concepts?) around the screen.

Mendelism: The program allows the instructor to implement genetic exercises that require students to solve a range of problems. It does this by providing the student a genetic setup, generally a pair of individuals that differ in one or more phenotypes, together with a posed question.

Figure 1 shows how a problem is presented to the student, in this case using Drosophila crosses. In the exercise, there are two segregating loci, one of which controls the presence or absence of the aristae and the other the conversion of the haltere into a second wing pair. The rest of the exercise is left up to the student, who must determine the crosses needed to work out the pattern of inheritance for each trait. To solve the problem, the student drags flies into the "crossing box," which leads to the production of offspring whenever the "offspring box" is empty. Bottles are available for storage to simplify the counting.

Genotypes are shown in the example of Figure 1 because the student has chosen to run a "trial" exercise. Repeated running of trials allows a student to begin to understand the relationship between genotype and phenotype in preparation for the awkward moment when only phenotypes are shown and genotypes must be deduced.

In its standard mode, the software checks the genotypes entered by the student and assigns a grade. This mode has utility in allowing the student to carry out multiple experiments with self-monitoring and in grading large classes where student-teacher interaction is limited. However, the process is not continuously monitored by the instructor and thus does not provide ongoing feedback on student progress. A more satisfactory way of checking student answers is one in which the instructor knows the correct answer, which is not available to the student. …

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