applications. Error analysis, uncertainty, fluctuations, and noise are probably best treated as part of laboratory experience rather than as topics in physics. Examples from biology should be used when available, and can already start in the section on Newtonian and macroscopic mechanics. Properties of materials (bone, tendon, hair) and biological fluid flows or motions of bacteria or bioparticles in water provide excellent opportunities.
The laboratory should begin with sessions based on step-by-step instruction, data sheets, equations given, and minimal writing. In a later phase, there should be guidelines—laboratories based on examples of how to do things, concepts, and a memo report (~1 page). Over the year they should evolve to open-ended questions with minimal reporting (~2 pages). This is a “Crawl, Walk, Run” approach. Students should work as a team consisting of two or three students for all labs. While the work done in lab should be done as a team, all writing assignments should be done by each student to develop writing skills. Whenever possible, students should learn by doing. If students are required to think through the process, they will have a much better understanding of the concepts. It may not be feasible to have a physical lab for all the desired laboratory experiences. Physical laboratories are preferred whenever possible, but both physical and virtual labs should be utilized. LabVIEW and Matlab both offer excellent environments for students to learn laboratory concepts. Web-based learning should also be utilized when particular experiments are not available or may be hard to reproduce locally. Details on the content for such a lab can be found in Chapter 4.
It is important to bring some ideas from engineering into the education of biology students. The word function is used in a similar context in engineering and biology, and this context does not exist in pure science or mathematics. Biology, with the impetus to dissect systems to understand their components (top-down), has evolved in the past decade into a molecular science. Now that the human genome is known, and the molecular players of many cell-signaling pathways are identified, biology is turning increasingly to the understanding of complex systems. Understanding function at the systems level requires a way of thinking that is common to many engineers. An engineer takes building blocks to build a system with desired features (bottom-up). Creating (or re-creating) function by building a complex system, and getting it to work, is the ultimate proof that all essential