Activities

Checks Lab
This is a fun activity to do with small groups. The Checks Lab will help develop the skills needed for successful science students. It allows students to practice data analysis, hypothesis making, hypothesis evaluation in the light of new data, good cooperative group skills, and good communication skills. This activity is designed to encourage students to test these skills as they try to reach a solution. This exercise points out that the data one has to work with can bias the conclusions made.
MATERIALS: 1 set of 16 checks for each group of students.

PROCEDURE: (1) Each one of the groups is given 5 of the 16 checks. These 5 are randomly selected so that no two groups receive the same combination of checks. You may want to randomly select the checks for each group before you begin and paper clip them together to guarantee each group has a different combinations of the same 16 checks. The groups are then asked to evaluate their data and develop a hypothesis that would account for the information learned from the checks and to develop supporting evidence for that hypothesis. They examine the checks and develop a story using the information on the checks. (2) When their hypothesis is complete the group is then given 4 more randomly selected checks and asked to re-evaluate their hypothesis using the new data and to either restate their hypothesis or add data to their supporting list. (3) When the second hypothesis is complete the students are given 4 more randomly selected checks and repeat the process. (4) Each group will have 13 of the 16 checks when they have completed the task. Each group then presents their hypothesis to the class and describes their supporting evidence. (5) The class after hearing all of the hypotheses arrives at a final hypothesis based upon all available evidence.
DISCUSSION: As a class discuss how the following affected their hypotheses: (1) the order that the checks were received, (2) the importance of evidence not received, (3) the importance of bias within each group.

* For more information about any of these activities on this page
e-mail Ernie Simoneaux at esimoneaux@selu.edu .

Cool Beans Activity
This activity develops skills in classification, sampling, graphing data, formula invention, and population estimation. The class should be placed into groups of four or five. The questions being asked in this activity are: "How big is big enough?" and "How many of them are there?". This activity can be followed up with an activity in the field.
MATERIALS: Hangers bent into square shapes of one inch, two inches, four inches, and eight inches on a side (quadrats); permanent marker, whole peanuts and bags of bean soup.
PREPARATION: Quadrats of each size are needed for each group of students. These miniature quadrats can be used to approximate one square meter, four square meters, sixteen square meters, and sixty-four square meters sampling area. The mixture of beans should be spread out over a desk that seats at least four. Each group gets one whole peanut thrown into the bean mix. Once the beans are distributed, they should not be re-shuffled.

How big is big enough?: The objective for this part of the activity is to demonstrate quadrat sampling methods (i.e., what sample size yields an accurate, representative , field sample while minimizing work effort?). Before the exercise begins, ask the students to make a graph with the number of species on the y-axis and the size of each quadrat on the x-axis. After the beans are spread, the students are allowed to determine exactly how the quadrats must be deployed in order to obtain an unbiased, random sampling (e.g., with eyes closed, over the shoulder toss, by taking turns, etc.) Once the quadrat has been tossed out, the total number of species (not individuals) in the sample is counted and recorded. Several replications with each quadrat size should be performed. After the number of species in each quadrat is recorded, have the students take the mean (average) number of species "captured" and write it on the board. When the sampling for each quadrat is completed the instructor should plot, on a line graph, the individual averages from each group for each quadrat size and the overall average for each quadrat size. As the data are added, the resultant curve will show an increasing number of species "captured" as the quadrat size increases, but at a certain point the curve will level off. This clearly indicates that at some quadrat size (usually the second largest), the number of species does not significantly differ from the next largest size but results in much less work. It is more efficient to use that quadrat size. Also, ask how many groups "caught" the peanut. Usually, most will have caught it even though the probability of catching this single item is very low. This demonstrates sample bias; was the peanut sampled preferentially because it was rare or because it was big?

How many of them are there?: The objective for this part of the activity is to illustrate the principles involved in basic ecological research. Specifically, to estimate the population density of a target species of elusive or mobile animals using the "mark-recapture" technique. Pick a target species. Use the quadrat size that provides the most efficient and reliable estimate. Toss out the quadrat and count the number of the target species caught. Place them in another quadrat that will serve as a corral. After a predetermined number of samples, count and mark all of the corralled items with a marker and release them and allow them to disperse by spreading them out randomly across the desk. Assuming that (1) the marked individuals disperse randomly into the wild population, and (2) subsequent trapping is also random, then any new sample should contain a representative proportion of marked to unmarked individuals. From this the size of the population may be estimated. You can have each group invent the mark-recapture formula or you can provide the formula. To invent the formula, your students need four symbols and the statement "this is to this as that is to that."


Either using logic or trial and error your students will find that, when the formula is solved for N, only certain answers make sense (i.e., N must be bigger than M, C, and R). It should be noted that many formulas in science and mathematics are determined in this manner. It turns out that the population size (N) is estimated by multiplying the number of marked individuals from the first sample (M) by the number of individuals of that species caught in the second sample (C), and dividing that product by the number of marked individuals recaptured in the second sample (R). N = ( M x C ) / R Why do the estimates differ? Each estimate is merely a guess at the truth, just as it is when scientists attempt to estimate the abundance of organisms in nature. We must keep in mind that this technique works only if the populations relatively static, or where changes due to such factors as immigration, births or deaths, are known. Also such factors as marked individuals being more noticeable to predators or even loosing their marks can greatly affect the results of such a method.

This web page was designed by Shannon Martin.
If you have comments or suggestions, email me at sbm@selu.edu