Recently I get the sense that when people talk about "educational technology" they are thinking only of blogs, social media, and other "web 2.0" applications that take advantage of the recent increased in internet bandwidth and computing power. I think we need to take a broader view. I have been using technology to teach science since the late 1990s. I would divide the sorts of technology I use into two categories: (1) probeware - electronic sensors that can be used to take measurements during experiments; (2) computer-based simulations used to teach science concepts, or as alternatives to "wet" experiments in science.
Probeware is useful for gathering data in ways that would otherwise be impossible. For example, I used carbon dioxide sensors to measure the rate of respiration in yeast, and I use oxygen sensors to measure enzyme activity. I also have dissolved oxygen, nitrate, and other sensors for measuring water quality. Sensors can interface with a computer and can easily programmed to collect data at a specific rate - so for example I can get a data point every second for three minutes, or every 30 minutes for 12 hours. Other Gonzaga teachers use probes to measure light refraction through liquids, pH, and a variety of physics phenomena. Biology and chemistry teachers use probes from Vernier, while the physics department uses a different system. Here is the lab protocol that I use for the respiration experiment.
Computer-based simulations allow students to conduct some lab work that would otherwise be impossible within the time frame of a high school biology class. For example, follow genetic traits through multiple generations of fruit flies, or watch traits evolve through dozens of generations of Galopagos finches. We also use image-analysis software to do some investigations.
One example is the "Biology Labs Online" system from Pearson. My students use the "Fly Lab" module to investigate how traits are inherited in fruit flies, based on basic Mendelian genetics principles. The lab is designed to mimic real systems, such that numerical results are variable, but still fall around a predicted result based on experimental models. In other words, if experimental data would predict 75% of the offspring from a particular cross would have red eyes, one student might get 72% and other student would get 76%. It's a very robust simulation in the way it models the real world, which allows students to grapple with the concepts and not get bogged down in the mundane details. We also use the "Evolution Lab" to model how natural selection drives changes in the size of finch beaks on the Galopagos islands. The simulation is based on field work done in recent decades by scientists from Princeton University. Pictured above is a screen shot from the program.
One other program I use is an image-analysis tool called "Scion Image" This software is designed to analyze images such as satellite photos, DNA electrophoresis gels, or microscope images. We use the software to investigate cell structure as well as the stages of cell division (which is what we were doing when Mark Howell happened upon my class earlier this month).



