The Future of Secondary Education CLOUDS AND SUN

Linking Models to Data: Hypermodels for Science Education

Paul Horwitz
Bolt, Beranek and Newman, Inc.

Students today--particularly students in the sciences--are awash in data. Information floods them from every side. Textbooks outweigh dictionaries, computers combine with CD-ROM and networking technology to make Hubble photographs, acid rain figures, and DNA sequences available on every desk top. But data is useless without structure, facts are meaningless without conceptual frameworks--information, in short, is not the same as knowledge. This article introduces a new paradigm for educational technology--the hypermodel--that seeks to use the computer to bridge the gap between a model and the physical world the model represents, between the "facts and figures" offered us by the natural world and the mental associations we construct to explain them. In the traditional textbook approach to teaching science the goal is primarily to give students information. The hypermodel uses a computer to help them turn that information into knowledge.

An important goal of science education is to influence students to think like scientists. There is considerable evidence (Chi, Feltovich and Glaser, 1981) that when professional scientists think about their discipline they organize experimental data using mental models to link otherwise disjoint facts, suggest causal relations, expose patterns, and provide explanations for processes and phenomena. It behooves the science educator, then, when presenting scientific "facts," to do so in the context of an appropriately detailed model, and to ensure as far as possible that students acquire both facts and models in the course of their learning.

These twin goals-teaching facts and teaching models-are characteristic of two of the ways in which computers are commonly used in the science classroom: either as information retrieval devices (treating the Internet, for instance, as though it were the world's largest CD-ROM) or else to present models of real-world phenomena in the form of simulations (Simmons and Lunetta, 1993). But neither of these modes captures the complex interaction of model and data that characterizes a biologist's concept of a gene, or a physicist's view of a black hole.

Supported by a grant from the National Science Foundation, my colleagues and I at Bolt Beranek and Newman, have been implementing and exploring the use of a new technology we call a "hypermodel" that links the act of data retrieval to that of model building by coupling representative real-world data to an underlying model of process. At present this new technology exists only in the form of a prototype program called GenScope that is intended to help students learn genetics. Over the next few years, we plan to enhance this software in significant ways, integrate it with curricular modules and student activities, and evaluate its effects both on pedagogy and learning outcomes. Our long term goal is to demonstrate the educational effectiveness of the hypermodel paradigm as a complement to the traditional textbook, and to implement the tools, protocols, and standards necessary to enable other researchers, teachers, curriculum developers, and students to develop a wide variety of hypermodels of their own design.

Description of GenScope

Many of the barriers students face when they learn genetics are consequences of the fact that the phenomena under study take place at many different levels of description. This multi-layered aspect has made genetics a rich domain within which to study student problem solving (Stewart & Van Kirk, 1990). In devising software to help students with this difficulty, we have considered six such levels: the molecular, chromosome, cellular, organism, pedigree, and population levels. At each of these we have devised representations of the information available, as well as tools for manipulating that information. The information is shared between the levels, linking them in such a way that the effects of manipulations made at any one of them may immediately be observed at each of the others. The levels thus combine to form a seamless environment for genetic exploration.

Enter the dragons!

To illustrate genetic phenomena the GenScope program starts with a fictitious species-dragons. These creatures have been given a simple structure that is useful for teaching purposes and will not prematurely raise such sensitive issues as the pros and cons of genetic engineering or the appropriate use of genetic screening tests. Our pedagogical approach has been to present students with a carefully sequenced set of problems to solve and then to set them up, two or three to a computer, and let them work on them. For example, using a model of Mendelian genetics we may challenge students to create dragons with specific traits, or to trace a family tree in order to determine the location of a gene that is responsible for an inherited disease.

Students are generally introduced to GenScope at the organism level (see figure 1), which displays the organisms' phenotypes (physical traits), but gives no information at all concerning their genetic makeup. Using a specific tool, the students may observe a single cell of an organism, as represented in figure 2. The cell contains chromosomes, made up largely of DNA molecules that contain all the genetic information carried by the organism.

Figure 1. GenScope's organism level. Two organisms are shown-in this case dragons. Their appearances are determined by their genes, which can be viewed and altered by the students.
The cells represented on the computer can be made to undergo either mitosis, simple replication, or meiosis, in which process they produce a new kind of cell, called a gamete, which possesses only a randomly selected half of the chromosomes of the parent cell. Once formed, the gametes can be combined in the central panel of the cell window, to produce a fertilized cell, or zygote, containing the usual complement of chromosomes. The zygote, in turn, will grow into a dragon possessing genetic material inherited from each of its parents. Meiosis is particularly difficult for students to understand, in part because although it is a cellular process, it involves processes that take place at the chromosomal and molecular levels, and its effects are felt at the pedigree and population levels.

Figure 2. The cellular level of GenScope. Shown are one cell each from Eve and Adam, the two dragons depicted in figure 1. The spaghetti-looking things in the centers of the cells are chromosomes, the carriers of the genetic information within the cell. These cells can be made to undergo meiosis (division into four gametes, each of which contains only half the genetic material of the parent cell) or mitosis (ordinary cell division into two identical cells. When meiosis is evoked, the computer runs a randomized simulation of gamete formation, as shown below in figure 3.
Thus, it is central to the field of genetics and a good deal of attention has been paid to it in the science education research literature (Kindfield, 1994; Liberatore Cavallo, A & Schafer, L, 1994).

Meiosis is represented graphically in the form of a computer animation, as shown in figures 2 and 3. The animation does not, however, attempt to represent the full complexity of the process, nor does it look exactly like meiosis as it appears under a microscope.

The role of the hypermodel

It is good for students to learn about meiosis by looking at a computer animation, but it is also important for them to know what a real cell looks like under a microscope, and how it divides. It is vital for them to realize that the real world is not as simple as a computer representation, that the information one seeks is often obscured by confusing and extraneous evidence, that interpretation of data is generally not as straightforward as it may appear in textbooks or in carefully arranged classroom experiments.

Figure 3. Meiosis is in process in this snapshot of the cell window. Adam's cell, on the right, has already produced the four gametes; Eve's cell, on the left, has completed the first division and is halfway through the second.
Most high school biology laboratories have at least one microscope, and it is possible-and advisable-for students to use this to view cells. But it is nearly impossible to set things up in a classroom so that one can watch an actual meiosis-for one thing, the process takes too long, for another it is very difficult to observe under any but optimal conditions. So it is educationally valuable to store a short movie sequence of this process on a CD-ROM and let students view it on a computer. Indeed, this kind of thing is becoming so common in educational software that a new name has been coined to describe it: multimedia.

What a hypermodel can do, however, that is not attempted by the conventional multimedia packages is to link a movie of cell division to a computer model of the same process, as depicted in figure 4. On the left-hand side of the window is a QuickTime movie of a cell undergoing meiosis. The process is at the stage known technically as "anaphase I." In the righthand pane of the window is the computer model's version of the same thing. As the student manipulates the scroll bar underneath the movie, both the movie and the model move through the various phases of the process.

The model is not just a "cartoon" version of the movie; it still retains all its former functionality. For one thing, it is a random process-the chromosomes migrate to different gametes each time it is run and their genetic material may be shared in another random process called "crossover." Furthermore, each model chromosome can be examined in greater detail, its genes and its DNA can be observed and altered as described below. The computer model, in other words, is a live, manipulable object, whereas the movie is stored data-static and immutable. The one represents the mental model we want the student to construct, the latter is the bedrock data that the model must explain.

Figure 4. Linking of computer model of meiosis to a stop-action movie of the process as observed under a microscope. The QuickTime movie actually controls the computer model by sending it commands that cause it to go into different states. The full functionality of the model is retained, however, including the randomness of the inherent in the process.

Biological structure and information content

At the cellular level, GenScope represents chromosomes as they appear in nature-as squiggly "spaghetti strands" in the nuclei of cells. But the importance to genetics of these biological structures stems from their role as carriers of information, and for this reason they are often depicted in textbooks as stylized rectangles with positions marked on them representing the locations of various genes. GenScope incorporates this representation as well, but with two important differences: the genes so marked may be altered by the student, producing corresponding alterations in the organism itself, and the chromosomes may be "opened up" to reveal the underlying structure of genes as sequences of DNA.

In figure 5, for example, we see GenScope's version of the textbook depiction of a pair of chromosomes as rectangular objects, schematically representing the linear DNA molecule, with the genes marked at their respective locations. However, anyone familiar with the Macintosh interface will notice that the labels marking the genes are actually pulldown menus. Activating these enables the student to change the gene from one variant, or "allele," to another. Such changes are accompanied by changes in the appearance of the organism to which the genes belong, as appropriate. Thus, an alteration of the wings gene in chromosome 2b, below, from the "W+" form to the "w" form will cause the wings on the dragon to disappear. We have observed students to figure out for themselves the classical Mendelian rules governing the behavior of dominant, recessive, and co-dominant alleles simply by playing around in this way with the various genes. In fact, the dragon genome as we have constructed it includes such relatively advanced topics as sex-linked traits, polygenicity (wherein a trait is affected by more than one gene), and pleiotropy (the opposite condition, in which more than one trait is affected by the same gene).

Figure 5. The "informational" representation of a pair of chromosomes. Note that the labels on the genes are pulldown menus, which allows students to change them and view the alterations, if any, in the affected organism.
Seen at the chromosome level, as above, genes are simply "markers" of some kind-their exact nature remains as mysterious to students as it was to Mendel and his colleagues. The true nature of the genetic mechanism resides, as we now know, at the molecular level, and GenScope enables students to drop down to this level to explore the DNA molecule that is contained within each chromosome. Figure 5 shows Eve's two genes for wings, for instance, showing what the "W+" and "w" alleles look like at the DNA level. They differ, but only very slightly. See if you can discover the difference between them1.
Figure 6. The DNA level representation of the two forms of the gene for wings. The left window shows the dominant and wild type (normally found in the population)W+ allele, the right window the recessive w allele. They differ by a point mutation-a single base pair substitution.
The DNA level has two complementary representations: a physical representation that shows the molecule as strings of colored rectangles representing the base pairs strung out in a linear array, and an informational representation in which the bases are displayed as a linear sequence of the letters ATGC, the initial letters of their names: adenine, thymine, guanine, and cytosine. The tension between representing biological reality and emphasizing information content is reminiscent of the contrast between "chromosome as spaghetti" and "chromosome as rectangle" presented above, and indeed it permeates the GenScope program throughout.

Just as the informational representation of a gene can be manipulated, via pulldown menus, so the equivalent representation of a DNA molecule can also be altered, simply be deleting or inserting the appropriate letters, typing them in as one would with a word processor. In this way, alleles can be altered at the DNA level and the changes will be reflected in the organism just as though the gene had been altered directly on the chromosome. using the pulldown menu. Mutations created at the DNA level are treated as new alleles. They can be named and used just as the pre-defined ones can. (Their default effect is to mimic the recessive allele, but GenScope includes pre-programmed mutations that cause, among other things, albinism.)

Dragon DNA is purposely designed to be as simple as possible, while still illustrating certain central points. GenScope, however, can also represent other species, and when it does so the DNA can be derived from actual sequencing data. We have done this in a few cases, most notably the representing the normal and sickle cell alleles of the human hemoglobin beta gene. This is another example of the close connection between GenScope's internal model of genetics and real-world data. Eventually, we plan to replace all fictitious DNA by the real thing wherever the sequence information is known.

Pedigrees and populations
As we have seen, organisms can be mated by combining gametes at the cellular level to produce a fertilized zygote. The resulting offspring will exhibit the traits appropriate to the particular mix of alleles it has inherited from the parents. This process is somewhat laborious (though instructive) and produces only one offspring at a time. For statistically oriented studies of inheritance patterns GenScope's pedigree level is considerably more useful (see figure 6). This is also the logical level for the introduction of genetics puzzles involving probability theory.

At this level female organisms are represented by circles, males by squares. A single phenotype, selectable by the user, can be represented schematically by full or partial filling of the icon representing the organism. Any two organisms of opposite sex may be mated, or "crossed," to produce a preset number of offspring. The genotypes (the set of alleles), and therefore the phenotypes (physical traits), of these offspring are randomly inherited from the parents.

The organisms represented on a pedigree are as "real" as those created at the organism level or "grown" through fertilization. Their chromosomes and DNA can be examined in just the same way, and they can even be dragged with the mouse onto the organism level, where they are displayed in the same way as any other organism.

Figure 7. The pedigree level. Note that one of Adam and Eve's daughters is stillborn, due to a sex-linked lethal gene.
At the population level, GenScope represents organisms by smaller circles and squares, which once again can be made to show a particular phenotype. This level introduces time and space, however-the organisms can be made to move about on the screen, randomly mating with each other. Moreover, different portions of the screen can be assigned different "environments," which selectively favor one or another phenotype. Thus, for example, we can create a "mountainous" area that favors the survival of winged dragons (presumably because they don't fall off cliffs so easily) and a "swamp" that favors dragons with no legs (because they swim better). When we run a population of animals with randomly chosen genes through many generations we find evidence of "genetic drift" which causes wings to predominate in the mountains, while "snakes" flourish in the swamp.

Organisms at the population level are treated in the same way as at any other. In particular, the cell and chromosome tools work at this level just as they do at the organism and pedigree levels. The organisms themselves can be dragged onto the other two levels, as well, where they are represented in the same way as organisms that were "grown" there. This is particularly useful in the case of the pedigree window, because it enables one to see how a particular trait "arises" in a population. By dragging an organism that possesses the characteristic of interest onto the pedigree window, the user can examine all of its ancestors and can easily trace any allele from one generation to the next.

Figure 8. The population level. Filled squares and circles represent dragons with no legs, partially filled have two legs, and the unfilled ones have four. The graph depicts the growth of these three subpopulations over 6 generations under conditions of random mating. The mountain range down the center of the window has no effect on fitness in this simulation.

III. Other Uses of Hypermodels

GenScope is still "under construction" and does not yet make full use of its ability to link its model to stored information. At this writing we have applied our model to three species: in addition to the fictitious dragons we have created files for humans and fruitflies (drosophila Melanogaster). Clearly, these real species, as well as the many others that we plan to add in the near future, offer excellent opportunities for linking visual data to GenScope in the form either of stills or of short movies that illustrate the various phenotypes. The molecular level, too, cries out for connections to real-world phenomena. In addition to electron microscope pictures of molecular phenomena, video clips of laboratory procedures for isolating, purifying, and sequencing DNA could be linked to the GenScope model, offering students an introduction to biotechnology while at the same time emphasizing the indirect nature of experimental data and the complex chain of inference underlying most scientific models.

It is all too easy, in studying the science of genetics, to lose sight of its human dimension. As the Human Genome Project vividly demonstrates, advances in locating and identifying human genes can have unexpected and sometimes soul wrenching consequences for individuals who are at risk of acquiring or transmitting genetically inherited diseases. Decisions with respect to genetic screening-for oneself, one's parents, one's mate, one's unborn offspring-are portentous and fraught with uncertainty and fear. Informed judgments often differ markedly as to what tests should be performed and who should be privy to the results. The ethical, social, and moral dilemmas brought about by advances in human genetics cannot be "solved" by science alone, but they arise in a scientific context and are affected by scientific judgment and fact.

A hypermodel can help to illuminate and guide discussion of social and ethical issues by embedding model-based exploratory activities within a real-world context. For example, to illustrate the dilemmas caused by advances in identifying the gene responsible for, say, Huntington's disease, we might link GenScope's internal model to a set of video clips of real people (or actors) who suffer from the disease, or are at risk of developing it or handing it down to their offspring. Connecting such a video to a realistic and manipulable model can serve not only to demonstrate the power of the science, but to aid young people to grapple with difficult moral decisions in a safe and informative context. In this way we may perhaps approach a "holy grail" of science education-placing complex scientific subject matter in a broader societal context without trivializing either.


Chi, M., Feltovich, P., & Glaser, R. (1981), Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152.

Liberatore Cavallo, A. & Schafer, L. (1994), Relationships between students' meaningful learning orientation and their understanding of genetics topics. Journal of Research in Science Teaching, 31(4), 393-418.

Kindfield, A. (1994) Understanding a basic biological process: expert and novice models of meiosis, Science Education 78(3), 255-283.

Simmons, P. & Lunetta, V. (1993), Problem-solving behaviors during a genetics computer simulation: beyond the expert/novice dichotomy. Journal of Research in Science Teaching, 10, 153-173.

Stewart, J. & Van Kirk, J., Understanding and problem-solving in classical genetics. Journal of Science Education, 12 (5), 575-588.

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