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The Warm Little Pond and the Warm Little Planet: Research Inquiry for the Second Tier
Jan C. Weaver , Honors College and Environmental Studies Program
Francis J. Schmidt, Honors College and Department of Biochemistry
University of Missouri-Columbia
Columbia, MO 65211
Second-tier students (Tobias, 1990) are academically able to study Science, Technology, Engineering and Mathematics (STEM) fields in college but not interested in doing so. Often their lack of interest stems from a science curriculum that they see as rich in facts but poor in creativity. This attitude is an anomaly, because scientists themselves regard creativity as an important part of “the pleasure of finding things out (Feynman,1999).” For a professional scientist, the factual material of a discipline exists primarily to support further investigation - the mere regurgitator of facts does not a scientist make. Traditionally, however, undergraduate science education concentrates on factual material and investigation commences only later (even as late as graduate school). The purpose of an undergraduate science laboratory exercise thus becomes twofold: to illustrate some known principle by reference to a classic result, or (for those who will go on to further education) to develop the practical skills necessary for research work. It is in undergraduate research programs that science majors get a taste of the excitement of science and these programs are very successful in training and retaining science majors throughout their undergraduate career.
While undergraduate research opportunities are important to the training of STEM students, they do not really address the needs of non-majors. Non-STEM majors, whose exposure to the subject matter is necessarily limited, never get to the investigations that make science fascinating. Seldom are these students asked to pose questions and design ways to address these questions. Yet, this is a working definition of inquiry, and especially since Shaping the Future (1996), we are enjoined to teach all students through inquiry. Can we bring the pleasure (and frustration) of research to non-STEM majors in the large university? In an effort to do so, we have built a sequence of courses for a general undergraduate population that explicitly models the behavior of professional scientists in their vocation of finding things out. This interdisciplinary, inquiry-based, general science sequence for undergraduate non-STEM majors was first offered in 1997 through the undergraduate Honors College. The small size of the Honors College and its informal governance has allowed us to experiment with the format and content of the course. The Honors College also has a strong interdisciplinary tradition extending through nearly 50 years of the humanities sequence; our new courses quite naturally were interdisciplinary. We wanted to integrate physical, biological, earth and mathematical disciplines to show how common themes apply across the disciplines.
Student Population and Faculty Motivation
The students enrolled in our course sequence are a classic example of Tobias’ (1990) second tier. The Honors College enrolls the top 10-15% of entering students, based on high school grades and ACT scores. These students, like the entire undergraduate population, have met the University’s requirement that they have three units of high school science and four of mathematics. While they have been academically successful at it, they have no interest in science as a career choice. Commonly, Honors students express their frustration at having learned the material in their pre-college science courses without mastering it. About half of the students in our courses are in pre-journalism, with the remainder in humanities, social science, education and business concentrations
We wanted to use the general science sequence to fit these students for roles as consumers of science. As professional research scientists, the course faculty believe that the investment of time and resources in education of non-STEM majors will pay off for the future of U.S. science as a whole. The participation of second-tier students in civic and political life can have profound influences on professional science. For example, how many local school boards have professional scientists serving on them? Even in Columbia, Missouri, a college-dominated town, the local school board has had a single physician and a psychologist as the lone science-trained representatives over the last decade. Yet these bodies have enormous influence on the growth and health of science education.
The Courses
The fall semester class averages 44 students while the winter semester class averages 26 students. The higher enrollment in the fall is due to the fall course being heavily promoted to incoming freshman. We designed the courses to model science as it is actually practiced by researchers (White and
Fredriksen, 1998) and consequently teach science as process rather than a collection of data. The factual material of the course sequence serves to support model research activities by the students. The course operates with a small annual budget for supplies and materials, less than or equal to that of a traditional laboratory-based introductory course. Tenured faculty teach the course as an overload and receive a small supplement that can be used for books, meetings, etc. Enrollment is limited to fifty students per semester, due to two factors: first, the Honors College emphasizes close student-faculty interaction, and, secondly, laboratory space is rather limited, since it is donated by academic departments.
The first semester offering, informally titled The Warm Little Pond, uses a decorative pond on the campus as a focus. The overall theme of the course relates to biological and chemical transformations and cycles. Key concepts from chemistry, biology and environmental science include trophic relationships and their foundation in chemical thermodynamics, population dynamics, biogeochemical cycles, oxidation-reduction reactions in physical and biological systems, evolution and ecosystems. The second semester offering, titled The Warm Little Planet, focuses on physical modeling of the evolution of Earth, including topics from physics, astronomy, chemistry, biology and geology. A third offering with a molecular physiology focus, tentatively titled The Warm Little Cell, is under development.
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Photo 1:
Students measure the area of the "Warm Little Pond." |
Given that the courses are introductory and interdisciplinary, most material that we teach is outside our immediate academic specialty. For example, a biochemist teaches the material about thermodynamics, and a chemist teaches most of the physics material. While this intellectual stretch is fairly common in undergraduate institutions, most research-extensive university faculty teach more focused material. However, the intellectual stretch turns out to be an advantage over the default mechanism of having faculty teach material closely related to their research specialization. Teaching outside their discipline requires that faculty distill the most essential points for their presentations. We find that we often unnecessarily complicate material that is closely related to our research expertise. Conversely, it’s often useful to examine the underlying assumptions of one’s discipline, and one of us
(F.J.S.) has altered his research program as a result of being forced to rethink a basic concept while teaching this course.
Modeling Research from the Start
The highest form of inquiry for a professional scientist is research that provides new knowledge. Research by undergraduate science majors is an important motivator in leading them to choose and succeed in scientific careers. Can this rubric be adapted to the goal of teaching undergraduate science for enrichment rather than for professional preparation? We decided to model research in our course by leaving the instructional laboratories much less determined than are traditional exercises. We explicitly tell the students that for most experiments there will be a lot of trial and error involved in devising the right procedure to answer the question that is being asked. Because this is usually very time-consuming, traditional student science labs have had most of the trial and error worked out in advance and the only real unknown is whether the students will be able to follow the directions carefully enough to get the expected results. We have put some of the trial and error back into the process.
In our course students carry out the same activities as professional scientists, albeit within a defined context: brainstorming, hypothesis development, proposal submission, peer review, experiment, appropriate record keeping (i.e., in a professional notebook format). They present their results in formal papers and at a poster session.
Each course begins with an open-ended, concrete exercise. In the Pond course, student collaborative groups are charged with measuring the area of the pond, using only string, a tape measure, and graph paper. The results are illuminating: the estimates of the area vary from less than 800 to more than 2000 square feet but almost always are reported to >4 significant figures, i.e., to a precision on the order of a few square inches. The set of wildly varying estimates furnishes the starting point for class discussion about random and systematic error, which leads naturally to the concept of significant figures. Given the varying estimates of the pond area, we can make sense of these estimates only by assuming that the errors are randomly distributed around the mean. Using the students’ experience and pre-existing knowledge (for example, that more measurements are better than fewer), we develop the equations for standard deviation and show how the mean cannot be more accurate than the least accurate single measurement.
This exercise reinforces several themes of the course:
The development of models. The students’ drawings and measurements are smaller and simpler than the actual area of the pond. The mean and standard deviation of their measurements are a model of their actual data. Models, however, are always underdetermined - anything we say about a system is less complex than is the system itself.
Data as inexact representations of a real situation. There is a moment of truth when students ask what the real area of the pond is and we tell them that we don’t know - our knowledge of the pond’s area is based solely on their own measurements. This is used to exemplify the fact that measurement depends implicitly on the means of measurement, as illustrated by Mandelbrot’s (1983) classic question “How long is the coastline of Britain?” and its answer “It depends on the length of your ruler.”
Mathematics from the bottom up rather than the top down. We develop the idea of standard deviation as a way to describe (model) the uncertainty in their data instead of providing a formula and ask students to compute the answer. The idea of significant figures flows naturally from the study of errors. This is an advantage of the bottom-up approach; all of our students have heard of significant figures and some can apply the rules, but none can state what the concept means or what it is good for. In this respect they don’t differ from first-year science majors we have taught.
The need for concrete experience. Data that students have argued over, identified the weaknesses in, and presented to their peers is more meaningful than any supposedly better measurement, such as a map of the pond taken from aerial photographs.
A similar exercise starts the second semester. Students alter a standard paper airplane design in systematic ways, and then measure the distance the planes fly to see if the alterations affect the plane's performance.
The Lecture/Laboratory Format
With this foundation, we move into a set of integrated lecture/lab modules to build students’ investigative skills. Each module consists of a classroom introduction of the topic, a laboratory or field exercise and a follow-up session. The classroom introduction is as concrete as possible. Thus, for example, in the introductory discussion of evolution and adaptation, the students are given a bag of leaves picked from local trees and asked to place them into morphologically similar groups and decide which are from the same type of plant (species). Then they go out into the field to measure the distribution of a single species and the variation of that distribution with different habitat types.
The laboratory and field exercises are derived from common, well-tested exercises, but they are not presented in the standard cookbook format. Instead, students are given a mini-journal consisting of short papers written in research format (abstract, introduction, methods, results, discussion and references) on each topic. Each paper presents the results of an experiment actually carried out by the faculty or teaching assistants. It is important that the data be imperfect; we found that this encourages the students to respect their data and not look for perfect results in their own work. The student groups then adapt the approach and information given in the paper to a related but independent investigation. For example, given a paper about the distribution of one plant type in various habitats within a local natural park, they must determine the distribution of a different plant or plants in the same or another area. In laboratory exercises, students often determine the relationship between two physical quantities (e.g., the heat of solution and the amount of solute added) for a chemical that is different from the one discussed in the mini-journal paper.
The lecture sections are coordinated with the labs in order to provide content in enough depth for students to formulate hypotheses and evaluate data. Lecture sections also provided opportunities for us to review any tricky procedures or mathematical analyses before the lab.
We usually start each unit with a recapitulation about the previous lab experiment, leading to a question “Why did you observe [the result of the laboratory]? For example, the trophic relationships they observe among insects in the field are an obvious lead-in to the conservation of energy (First Law of Thermodynamics) and the fact that energy conversions never work with 100% efficiency (Second Law of Thermodynamics). After we introduce the overall concept, we introduce the laboratory experiment, usually by discussing the results presented in the short paper describing a similar experiment. The class sessions encourage student feedback and “thinking out loud.” Our own experience in research had told us that ideas are often worked out in discussion.
After the experiments are completed, we use the second lecture session in each unit for a quiz on the unit, for a “post-mortem” of the students’ experimental results, and to extend the concepts of the unit. We believe it is very important that the discussions relate directly to the students’ experience with lab activities.
Model Research Projects
Once the students are familiar with the conventions of the scientific literature and methodology, we move on to a more complicated research project, carried out over several weeks. Initially, we gave the students free rein in selecting their projects. This was a disaster. Hypotheses varied bimodally between the trivial and the impossible, while the need for a variety of materials and instruments burdened the course staff considerably. For the last several years, all the student groups work with the same system but pose different hypotheses. The Warm Little Pond project uses a Winogradsky column (a column of water and mud which naturally stratifies into trophic layers) constructed in a 2L soda bottle. Students propose hypotheses relating physical and chemical variables to the distribution of microorganisms in the column. In the Warm Little Planet course, we have adapted the greenhouse model of Dunnivant et al. (2000) for the class. This model uses a 2L soda bottle as a mini-greenhouse; upon illumination the temperature of the bottle increases to an equilibrium value. The final temperature is greater in a bottle enriched in an infrared-absorbing (i.e., greenhouse) gas than in a bottle containing only a non-greenhouse gas
N2. Students identified physical or chemical processes that could affect the warming in the bottle. They then wrote a proposal that hypothesized ways to determine these effects.
Students present their hypotheses and proposed experiments in class and their peers comment on them. The hypotheses have to be justified by a plausible mechanism or analogy rather than being just “We’ll try this and see if something happens.” They carry out their experiments over two class periods, incorporating trouble-shooting and replication to validate their results. Finally, they write a paper in scientific format and present their results in a poster session. In grading the projects, we evaluate the students’ ability to perform activities such as formulating a hypothesis, isolating variables, keeping careful records, and presenting their results in a clear and logically consistent manner, rather than reproducing some predetermined result. We tell them from the start that plausible but wrong hypotheses are valuable as long as they are rigorously tested. The scoring rubric is designed to encourage students to respect their data and, at the same time, to give careful consideration to what is necessary to obtain good data.
Assessing student learning
Our three main objectives were that students would understand and be able to use key science facts, theories and concepts, that they would be able to think scientifically about new problems and novel situations and they would have a positive view of their ability to understand and use science. The continuing challenge is finding and/or creating assessment tools that will allow us to evaluate our progress in achieving these objectives.
During the semester, student progress was evaluated by standard criteria such as quizzes, research reports, participation in discussion and performance—as a team—on an end of semester research project. In addition, we gave students Lawson's (2000) Classroom Test of Scientific Reasoning at the beginning and end of the semester, and asked them to self assess their ability to understand and use scientific concepts and scientific processes.
Individually Graded Quizzes as Collaborative Learning: Quiz questions required students to recall science concepts and then use them to evaluate data or to make predictions. A key feature of the quiz was the opportunity for students to discuss the questions with their lab partners for 10-15 minutes and then to finish the answers on their own. We believe the collaborative quiz helped accomplish several goals. It got the students to work as a team, which was critical to later success on the semester project, and it usually got students started on the right track in answering the question and reduced the amount of misinterpretation of the questions. The quiz provided more opportunities for peer-led learning and increasing the understanding of students who had to explain and defend what they thought was the right answer to other team members.
Interestingly, there were still students who failed to answer questions even when given the opportunity to get answers from other students. It appears that if students failed to study the required material, no amount of coaching could save them. On the other hand, students who understood at least a little of the material probably achieved a greater understanding of the concepts when working with peers.
Below are samples of the quiz questions used in each of the courses.
Warm Little Pond: Using lateral gene transfer, agricultural scientists have been able to insert genes for herbicide resistance into grain crops like corn and wheat. These genetically modified (or GM) crops are able to survive applications of the commercial herbicide Round Up. When a farmer sprays herbicide resistant crops with Round Up, the weeds are killed but the crop plant is unaffected.
- Using what you know about variation, the different mechanisms of evolutionary change, and adaptation, speculate about what is likely to happen to the usefulness of Round Up in killing weeds in the next 10 years.
- Would it make a difference if 90% of grain farmers used Round Up instead of only 20% of farmers? If so, what difference would it make?
- From this example, could you make a generalization or rule of thumb about the long term effectiveness of any widely used pesticide?
Warm Little Planet:
- List the planets in the solar system along with as many characteristics of each as you can think of. Construct a table to answer this question.
- In one or two sentences, describe the Dynamic Encounter (DE) and Nebular Hypotheses (NH) for the origin of the solar system.
- Which model, DE or NH, appears to be better supported by the characteristics of the solar system and the planets? Use at least two characteristics of the solar system and/or planets to support your arguments.
Research Reports and Laboratory Experiments: Each experimental lab was presented in the format of a scientific paper. The paper provided background on a concept, proposed an hypothesis based on that background information, outlined materials and methods for investigating the hypothesis, presented actual data, analyzed the data, and discussed whether the data agreed with the hypothesis or not. Finally, the discussion section raised one or more questions that followed from the results. Students could investigate these questions using essentially the same methods and materials described in the paper. In carrying out their investigation, a student was required to engage in a parallel process. They would decide on a question, work out an experimental protocol for answering it, perform the experiment, collect the data, analyze it, decide whether the data agreed with the hypothesis and then discuss the results within a larger context. While the students worked in lab as a team, each student wrote his or her own paper. The introductory research paper provides a model of how students should write their own research reports and we have observed an improvement in the quality of the student papers as we have adopted this format.
Reports were graded based on the quality of individual sections and on overall quality. We looked for ability to use a concept to propose a hypothesis, use of outside sources, the amount of quantitative analysis of data performed, whether the conclusions fit the data, and the integration of the results into a larger context. Over the course of the semester, students showed the greatest improvement in their ability to analyze the data, including using quantitative and graphical methods, and in drawing the correct conclusions about what the data showed - even if it was not consistent with their original hypothesis. However, they continued to show limitations in their ability to link concepts learned in class to specific hypotheses and to experimental outcomes.
Class Discussion: While we encouraged questions during lecture and provided open ended exercises for students to work and comment on, we formally evaluated participation only during discussion of two popular science books assigned to the students. For Warm Little Pond these books were Silent Spring, by Rachel Carson, and A Sand County Almanac by Aldo Leopold; T. rex and the Crater of Doom by Walter Alvarez and Microcosmos by Lynn Margulis and Dorion Sagan were used for the Warm Little Planet. We chose these books because they all contain several examples of the concepts we covered in each class.
Students were instructed to read the books with the goal of identifying passages that in some way used a concept discussed in class. This allowed us to evaluate their ability to recognize concepts in a novel situation and even to apply them to analysis of the events covered in the text
(i. e. development of insecticide resistance in mosquitoes as a result of natural selection). Students were organized into small groups that were different from their lab groups and asked to take turns reading the passages and explaining how they related to a class concept. Other students were expected to expand on, disagree with, or respond in some other way to the first student’s interpretation of the passage. Instructors merely noted how many times a student offered a comment and indicated something about the quality of the contribution.
Here are some of the comments students made about the books for Warm Planet. (comments for the pond class books were similar).
Would you recommend the readings (Microcosmos and T. rex) again?
“Yes, for science they were actually cool.”
“Microcosmos I loved! It was very thorough and really brought the process/concepts of evolution together in a comprehensive manner.”
“T. rex was really interesting. I usually don't enjoy science readings but I loved this book.”
“No - They are time consuming and don't completely relate to class.”
‘No, these took too much time for such a small aspect of the class. Choose smaller readings or put a greater emphasis on the books.’
“Yes, because they are thought-provoking and necessary to a well-rounded knowledge base.’
‘Yes - they related to things we were learning in class.’
Semester Project: While we suggested possible modifications to the Winogradsky columns or the greenhouse in a bottle, the students decided for themselves what they were going to test. Some of the variables investigated using Winogradsky columns were pH, additional nitrogen, the role of plastic litter on the formation of bacterial colonies and the effect of different colors of light. For the atmosphere in a bottle, students looked at different gases or the heat absorbency of different substrates, or modeled the relationships between the albedo or atmospheric dust and the atmospheric temperature.
After the groups picked a variable to investigate, each student was expected to find and summarize two sources on the subject, with at least one being a peer-reviewed article. For a team of four students, this provided eight background sources for their proposal and final research report. The students were evaluated on their paper summaries (which were individual), their research proposal, an oral presentation of their proposal, a poster showing their results and a final research report, which were all group projects.
The scoring for all of these assignments emphasized understanding of the underlying concepts, ability to construct an hypothesis, quantitative analysis of data, and explanation of the results within the context of what was already known about the system.
Did the students feel that the format encouraged learning?
We asked the students to comment on the class’ approach to the laboratory activities:
Do you think the method of having you read science papers to prepare for labs was useful in helping you to understand the process of science as scientists do it?
For fall 2002, there were 36 positive responses, 5 negative, 2 don't know or yes and no, and 3 who did not answer. Some of the more descriptive responses follow.
“Yes - very effective. Have students pay more attention to what’s happening in the process - make sure they realize that this is how it actually works.”
“Yes, it made us think more critically instead of just following instructions, it helped me understand the purposes/processes much better.”
“It was great. Helped me know where to start. Often felt like I was a pro.”
“Not really, find database of real scientific papers for us to search.”
“No, I think the examples in the lab manual were infinitely more helpful than the papers.”
“Yes because you actually understand the context of the lab before you do it.”
“The science papers were good because you actually have to think for yourself.”
“Yes, it forces students to see how scientists present their findings.”
‘It was a good model more for writing the labs than performing the labs.”
“I thought it was useful, but I would make them more accessible to non-science people.”
“No, it confused our group on what to do and when we tried to be open-minded and creative, points were deducted.”
“Yes - but the lab should be discussed and explored before we are actually in the lab room.”
“Yes, but it was difficult to do the labs with little guidance.”
“Yes and no - it gave me a good idea, but not a real complete idea of what we were doing. Also I felt I based my lab report too much on the book, but it was nice to have a guide.”
Did the students think they learned anything from the course?
Students were given a list of concepts covered in class and asked to assess improvement in their understanding and use of those concepts. The concepts for the Warm Little Pond were:
1. evolution
2. natural selection
3. adaptation
4. alternative modes of evolution (mutation, drift, etc.)
5. exponential growth
6. logistic growth
7. carrying capacity
8. r and K selected species
9. niche concept
10. species interactions (predation, competition, mutualism)
11. food webs/trophic levels
12. trophic pyramids
13. 1st law of thermodynamics
14. 2nd law of thermodynamics
15. entropy
16. free energy
17. oxidation reduction reactions
18. respiration/photosynthesis
19. electron transport chain
20. biogeochemical cycles (N, S)
21. acid-base reactions
22. pH
23. buffering capacity.
For understanding, on a scale of 0 (the same) to 2 (much better), students' average score was 1.15 +/- 0.07. For ability to use concepts, the scale was: 1 (now I know there is such a concept), 2 (can recognize when it would be relevant to a news story or policy issue), and 3 (can apply it to decisions in my own life). Students' average score was 1.93 +/- 0.08.
Students were also asked to score their understanding and use of the processes of science:
24. how to develop questions,
25. how to develop experiments,
26. how to interpret data,
27. how to fit research results into a larger context,
28. how to deal with unexpected results,
29. how important is observation,
30. how interconnected biology, chemistry and physics are in the real world.
Using the same scoring as for science concepts, students rated their ability to understand scientific processes as 1.38 +/- 0.21 and to use processes as 2.56 +/- 0.25.
Did the students improve their reasoning ability?
In Fall 2002, we administered the Classroom Test of Scientific Reasoning developed by Lawson (2000) at the beginning and end of the semester. The test consists of 24 multiple choice questions covering relationships of mass, volume, and shape, data interpretation, probability estimates and experimental design. None of the topics or examples used in the test were covered in the course itself. Lawson’s instrument is designed to be content-independent and able to assess scientific reasoning by all varieties of students. We compared individual scores on the pre- and post-test to see if there was any change in their reasoning ability over the semester. The 46 students tested increased their scores on the test by 1.02 +/- 0.42 points, a small but statistically significant (P < 0.05) result. Although promising, the data don’t yet establish cause and effect. Such a slight change in scientific reasoning ability could be due to other factors, including a general increase in reasoning ability just from surviving another semester at college. In the future we plan to administer the test to a control group of students and compare the changes between students in our class and in more conventional science classes.
Did the course affect students’ further academic or research interests?
This is difficult to evaluate since our aim is to educate students to be consumers rather than practitioners of science. Our evidence at this point is only anecdotal. A few (on the average of 1-2 per year) of the students have changed their courses of study to include more science-oriented disciplines (e.g., one student moved from journalism to science journalism and eventually to environmental law and another took a joint major in meteorology). One student, while remaining a journalism major, did an undergraduate research preceptorship in molecular biology in one of our laboratories
(F.J.S.). However, these students are still a decided minority.
We also have very little data about the ability of our students to translate their newly learned research skills into non-STEM fields. Clearly the ability to place facts in context and evaluate the reproducibility of evidence would be important skills for any citizen, but these skills are difficult to measure since our students don’t stay enrolled in STEM fields once they fulfill their general education requirements and we cannot easily track them.
Advice to others
Foster Group Work: We found that a positive group experience was key to student satisfaction. If they had a good group, students had positive feelings about the class. If the group failed to come together, or if there were one or more bad actors, then the students expressed negative feelings about the whole class experience. A good group experience (measured by scores on peer evaluations) was also correlated with higher grades (r = 0.435, p = 0.003), though it is impossible to tell whether good group dynamics led to better grades or better grades left students more satisfied with their group experience. We also know, through trial and error, that a good group experience does not just happen. Here are things that worked for us.
Do not let students self-select groups or the social outliers will end up in a group by themselves, even in a class of complete strangers. Instead, select groups randomly. We have students count off by the number of lab groups we are going to set up while they are still sitting.
Make expectations for group behavior clear. Students receive a hand out describing appropriate behavior - coming to meetings, being prepared, staying in touch, not dominating meetings - and an evaluation form for scoring each of their team members on their adherence to these standards. This evaluation counts for part of the grade.
Have the students exchange contact information immediately - phone, email, address.
Have the students decide on a standard meeting time, and plan a first meeting with them so you can explain how the group project works and so you can answer any questions they have about the class. We split up this responsibility among the TAs and faculty so no one person had to go to a dozen meetings.
Have the students sit together as a group. We reinforced this by having small group exercises that break up the lecture and by allowing the lab groups to work together on the quizzes.
Less is More: We organized the course material around only six main concepts we wanted to teach the students. For the Warm Little Pond they were evolution, population growth, ecological communities, heat and energy, oxidation reduction reactions and acid base reactions. For the Warm Little Planet the concepts were the 4 forces, the solar system, plate tectonics, the rock cycle, the origin of life, and the fossil record. These are significantly fewer concepts than are found in a semester-long survey course in, for example, chemistry or biology. We explicitly traded breadth for depth, reasoning that students would be able to apply reasoning skills to new factual material if they had learned scientific reasoning.
Once students mastered these main concepts, they acted as anchors to which we could attach additional concepts. For example, elementary particles and radioactive decay could be grouped with the 4 forces, or r and K selection could be grouped with population growth. Then these secondary concepts would provide linkages among the main concepts; radioactive decay evidence supports the rock cycle and the fossil record, and K selected species have different evolutionary adaptations than r selected species.
Build Math from the bottom up: Mathematics is essential in science, yet second-tier students are often intimidated by it. We try to overcome this difficulty by starting with results and data, usually from experiments that the students carry out. First, it’s necessary to identify the problem e.g., these points aren’t on a straight line. How do we find the best line for the points we got? With the problem identified, the students brainstorm various possibilities for solving the problem. For example, they might decide to minimize the sum of the differences between the line and the experimental points. However, this leads to a possibly false result if the differences are negative. They then might try to take the absolute values of the differences, and, finally, for computational simplicity, the squares of the distances of the experimental points and the constructed line. This contrasts with the more common approach of deriving a formula and then applying it to data. Such an approach often causes the students to give up on the approach entirely, since they believe that they are not good at math.
Make Connections Between Lab and Lecture Explicit: Although this continues to be a challenge, we are making progress. There are six conceptual units, and each has a lab with it that depends on an understanding of the key concept of the unit. Initially we thought simply associating the unit and the lab in time would be enough for students to see the connections. However, we have gradually had to increase the amount of lecture time used to explain the lab and how it fits into the landscape of scientific knowledge. Because we are introducing more uncertainty into the lab experience and seeking a higher level of conceptual understanding than is typically expected of students in non-majors classes, we think that helping them see connections is a fair tradeoff.
Make the Lab Experience Simple, Direct and Concrete: In their initial phases, the labs relied heavily on electronic probes interfaced with computers. Students set up their experimental systems, plugged in their probes, and fed their data into computers that recorded their data and then graphed it. It soon became clear that while the students were becoming proficient at trouble shooting poor connections between the probe and the computer, they didn’t have a clue about what to do with the data they were getting. Some of them didn’t even know how to read the graphs generated by the computer, let alone interpret what they meant in terms of the hypotheses they were testing. In addition, we consumed a lot of class time explaining the operation of equipment students were unlikely to use ever again since they were not science majors. Students were quite hard on the expensive probes and the computer linked equipment did not allow us to do experiments in the field.
So we rethought our approach. We decided we wanted the students to experience the phenomenon we were talking about as directly as possible, using the simplest and most familiar tools necessary for the job. Then, the lab would be about the phenomenon and not about the equipment. Instead of a temperature probe, we used a thermometer. Instead of an electromagnetic field detector we use a compass and measured deflection of the needle from north. Instead of using a motion detector to measure acceleration, we rolled marbles down inclined planes and timed their motion with stopwatches. Because students were already familiar with the equipment, they could focus on the data instead of fiddling with the apparatus. For example, many data were collected at set time intervals in order to see when a maximum level was reached. The computers automatically used time as the independent variable when graphing the data, even though the variable of interest might be amount of solute or pH. Even though students tended to make the same mistake as the computers, by having them graph their data by hand, we had an opportunity to intervene and get them to rethink their approach.
Thermometers and inclined planes are admittedly crude and as a result, the data suffer from a certain level of imprecision. On the other hand, because of the average student’s lack of experience with more sophisticated equipment, there was also a lot of experimental error even when using probes and computers. Because the experience was mediated by electronic equipment, students did not have as good a feel for when they were getting problematic data. So, better equipment does not necessarily translate into better data.
Another positive aspect was that we thought more creatively about field research, especially in systems biology and geology. Students consistently rated the field trips (especially those taken on nice days) as one of the best experiences in the class.
Future Directions and Opportunities
We have concluded that we have developed an educationally- and cost-effective way to meet the STEM needs for the second tier by emphasizing science as a process and leading the students through the same intellectual steps that professional scientists use in their work. In support of this, we converted existing laboratories into a mini-journal format that is explicitly modeled on the scientific literature. In the future, we want to expand this course to include the larger undergraduate population, not just Honors students. However, there are several challenges involved in making the usual introductory and/or non-majors courses in science more inquiry based.
Making the labs more open-ended and re-writing the standard biology, chemistry and physics labs so they fit the scientific paper format we used would be time-consuming, and would depend on finding individuals who are familiar with both the science content and the principles of inquiry. However, if this task is distributed among faculty in a department who have the appropriate background, it is not insurmountable. A second issue is integrating lecture and lab so students are receiving the background material they need to understand and modify the lab exercise. At
MU, the introductory/non-majors lecture courses are not necessarily closely integrated with the lab schedule. Faculty usually decide for themselves the order and pacing of material and what specific content will be included, as long as major theories and concepts are covered. Our approach of focusing on a smaller number of significant topics and covering them in more depth might or might not be acceptable to the faculty teaching these courses.
A third concern is the need to revise the assessment tools so they are more appropriate for a non-honors population. While the non-honors student at MU is brighter than average, she or he may not have the facility with writing, math and critical reasoning that a typical honors student may have. Asking students to do background research on a topic, analyze data they have collected and write it up in research paper format may prove too challenging for the average freshman. On the other hand, the creative opportunities presented by inquiry science may stimulate students much more than the usual fact based approach.
Finally, the group experience was extremely important to the student's perception of the course and possibly to their grade in the course. Teaching assistants would need to have some training in facilitating positive group dynamics because students would be able interact in groups only in the lab, not in the large lectures.
However difficult it might seem, our success with these inquiry-rich interdisciplinary laboratory courses encourages us. An institutional change in this direction would help meet the imperative of
Shaping the Future, that “all students learn these subjects by direct experience with the methods and processes of inquiry.”
The Institution
Founded in 1839, the University of Missouri-Columbia was the first state university in Thomas Jefferson's Louisiana Purchase territory and the first public university west of the Mississippi River. In Fall 2002, the total enrollment was 26,124 students, 19,698 undergraduates and 6,426 graduate and professional students. Of these, 1,409 were international students (representing more than 100 countries) and 2,502 were minority. The average ACT score was 25.5. The freshman retention rate is 83.6%, and the student to faculty ratio is 18.2 to 1.
MU offers over 250 degree programs in six colleges - Agriculture Food and Natural Resources, Arts and Science, Business, Education, Engineering and Human Environmental Sciences. In addition there are schools or programs in Music, Journalism, Health Related Professions, Nursing, Information Science, Accounting, Natural Resources and Fine Arts. In addition to the Graduate school, there are professional programs in Law, Medicine, Veterinary Medicine, and Public Affairs.
MU has been designated a Research-Extensive University by the Carnegie Foundation for Advancement of Teaching. Only a handful of U.S. universities offer the same breadth of professional and undergraduate degree programs as does
MU. To ensure commonality, the faculty adopted a general education requirement, under which all undergraduates, regardless of major, must complete three courses each in the humanities, social sciences and natural sciences. Natural science courses must include both physical/mathematical and biological sciences, and one must have a laboratory. A typical student might meet the general education requirement by taking a series of traditionally organized series courses such as General Biology, Mathematics, and a lecture course relating to Science and Society. A major mission of the MU Honors College is to meet general education needs for students in their first and second years.
Acknowledgements
We are grateful to our faculty colleagues who have been involved in the course, especially John Adams, Jim Carrel, Carol
Deakyne, Ray Ethington, Mel George, Jack Jones and Stuart Palonsky, Honors College Director. We are also grateful to a number of dedicated Teaching Assistants, John
Burkhardt, Suzy Otto, Angela Sell and Tony Thorpe, and, especially, to the MU Honors students who helped us plan the course and were willing subjects for this ongoing educational experiment. This work was supported by an NSF RAIRE grant to MU and by the MU Honors College.
References
Dunnivant FM. Moore A. Alfano MJ. Brzenk R. Buckley PT. Newman ME. 2000. Understanding the greenhouse effect: Is global warming real? An integrated lab-lecture case study for non-science majors. J. Chem. Ed.. 77(12):1602-1603.
Feynman, R.P. 1999. The pleasure of finding things out : the best short works of Richard P.
Feynman. J. Robbins, ed. Cambridge, Mass. : Perseus Books
Lawson, A. E. 2000. Classroom Test of Scientific Reasoning (Multiple Choice Version), based on Lawson, A. E. 1978. Development and validation of the classroom test of formal reasoning. Journal of Research in Science Teaching, 15(1):11-24.
Mandelbrot, B.B. 1983. The Fractal Geometry of Nature. New York: Freeman and Company
National Science Foundation. 1996. NSF Report 96-139. Shaping the Future: New Expectations for Undergraduate Education in Science, Mathematics, Engineering, and Technology. Washington: National Science Foundation.
Tobias, S. 1990 They're Not Dumb, They're Different: Stalking the Second
Tier. Tucson, Ariz.: Res. Corp.
White BY; Frederiksen JR. 1998. Inquiry, Modeling and Metacognition: Making Science Accessible to All Students. Cognition and Instruction 16:3-118
Copyright
© 2003 Council on Undergraduate Research. All rights reserved.
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