Revealing Student Thinking about Experimental Design and the Roles of Control Experiments
International Journal for the Scholarship of
Teaching and Learning
Revealing Student Think ing about Experimental Design and the Roles of Control Experiments
Joy M. Power 0
Michael W. Klymkowsky 0
0 University of Colorado , USA
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Revealing Student Thinking about Experimental Design and the Roles of Control Experiments
Jia Shi University of Colorado Boulder, Colorado, USA
Joy M. Power University of Colorado Boulder, Colorado, USA
Michael W. Klymkowsky Boulder,
Well-designed “controls” distinguish experimental from non-experimental studies.
Surprisingly, we found that a high percentage of students had difficulty identifying control
experiments even after completing three university-level laboratory courses. To address
this issue, we designed and ran a revised cell biology lab course in which students
participated in weekly “experimental control exercises.” To measure student understanding
of control experiments, we developed a set of assessment questions; these were given to
students prior to and following completion of either a standard cell biology lab course or the
revised cell biology lab course. Not unexpectedly, the results indicate that the revised
course led to greater improvements in students’ ability to identify and explain the purpose
of control experiments. Based on these observations, we recommend that explicit and
detailed discussions designed to identify the design and purpose behind control experiments
become a standard component of all laboratory courses.
A major effort in current science curricular reform involves helping students learn how to
make informed decisions regarding the significance of scientific observations and
hypotheses throughout their lives. It is often assumed that “scientific literacy” will be useful
in this regard and that the acquisition of science process skills, such as those presumed to
be provided by laboratory courses, is essential to getting students to achieve this goal
(American Association for the Advancement of Science, 1993; Council of Ministers of
Education, 1997; Miller, Osborne, & Nott, 1998)
. A key, and perhaps defining feature of the
scientific strategy, particularly within the biological sciences, is the role of control
experiments in both the design and interpretation of experimental observations. Control
experiments, both positive and negative, are served to explicitly test the experimenter’s
assumptions, so as to validate the conclusions that can be drawn from experimental results.
Much published science education research has been focused on improving high school
student science process skills, that is, the development of testable hypotheses, robust
experimental design, the critical interpretation of data and subsequent the revision and
extension of studies (Germann, 1998; Tamir, & Amir, 1987). As part of this work, there has
been an effort to develop assessments to evaluate such skills at both high school
Okey, & Wise, 1985)
and college levels
(Brickman, Gormally, Armstrong, & Hallar, 2009)
Some studies have suggested that the inquiry approach produces greater achievement in
science process skills than the traditional approach
(e.g., Gabel, Rubba, & Franz, 1977;
Tobin & Capie, 1982; Brickman, Gormally, Armstrong, & Hallar, 2009)
. Based on these
studies the authors conclude that basic science process skills can be taught, and that when
learned, such skills could be readily transferred to new situations. However, there continues
to be an active debate concerning just what the ability to design, carry out and interpret
authentic scientific inquiry encompasses, as well as, how to differentiate it from the simple
inquiry commonly found in high school science classrooms (Chinn & Malhotra, 2002). In
addition, it is difficult to determine if inquiry-based learning has had a lasting effect
(Abrams, Southerland, & Silver, 2008; Chinn & Malhotra, 2002)
. It is arguable that the
entire peer-review system is based on the fact that rigorous experimental design and data
interpretation are by no means trivial skills; they must be constantly reinforced. Therefore
more studies are needed to improve and evaluate students’ science process skills at the
Since experimental design and controls are an essential and difficult part of scientific
process, we hoped to reveal student thinking about control experiments through Ed’s tools –
a web-based program to facilitate the collection, coding, and analysis of text-based student
(Klymkowsky & Garvin-Doxas, 2008)
. In response to the question “It is common to
hear talk about ‘controls‘ in scientific experiments, what are ‘controls’ and why are they
essential part of rigorous experiments?”, we find that the use the terms of “positive” or
“negative” control are rare in student language. The responses below are representative of
most student responses:
“Controls are variables that you can make changes to them. They are very
important to the experiments because they allow you to form a conclusion that could either
support or reject your hypothesis”.
“Controls are what set the boundaries and allow for the results to be accurate and to
reduce the change of giving false information or inaccurate results”.
“Controls are ways of double-checking your method. You can check to see if there
might be another explanation for anything in your test. Each control is one opportunity to
It was in this light that we undertook the present study to learn what students majoring in
Molecular, Cellular, and Developmental Biology (MCDB) at the University of Colorado know
about experimental design and controls, and to determine the effect of introducing
collaborative learning projects on this topic into a one-semester Cell Biology Lab Course
(CBLC). Collaborative learning has been shown to promote students’ conceptual gains,
(Mazur, 1997; Johnson & Johnson, 1999; Springer, Donovan, & Stanne, 1999 and many
, enhance problem solving skills (Cooper, Cox, Nammouz, Case, & Stevens, 2008)
and boost performance on a wide variety of tasks
(Woolley, Chabris, Pentland, , Hashmi, &
In this study, we found that students (predominantly sophomores) had difficulty identifying
and explaining experimental controls after a standard one-semester CBLC, a course
commonly preceded by two other laboratory courses. These students served as the control
cohort. Students in this group often confused positive control experiments with
experiments or negative control experiments. Positive control experiments were often not
recognized as necessary. To address these issues, we designed and incorporated a set of
control exercises into the spring 2010 CBLC; students taking this course served as the
experimental cohort. For most control exercises, students first worked independently and
then in collaborative groups to explicitly identify experimental, positive and negative control
experiments necessary within experiment scenarios, and to explain the purpose of each
control experiment. As another type of control exercise, students designed experimental
scenarios based on proposed questions. We present a comparison between these two
cohorts with regard to assessment gains measured by pre- and post-responses, student
reasoning on experimental controls and student attitudes.
The CBLC is a required 2-credit course taken by MCDB majors. It is also the last lab course
required of majors; typically these students have already taken two one-credit laboratory
courses (associated with the Introduction to Cell and Molecular Biology and the Introductory
Genetics lecture courses). Each section contains between 16 -20 students working in
groups of 2-4 for 4 hours weekly (one section in spring 2010 contained only 9 students).
The first half of the semester emphasizes techniques (e.g., microscopy and electrophoretic
analyses), while the second half focuses on groups of students designing, conducting,
analyzing, and reporting on their self-designed experiments. Teaching Assistants (TAs)
work in pairs and each TA is responsible for two sections per week. The instructor meets
with the TAs weekly to prepare them for the upcoming labs. In spring 2010, the instructor
(J.P.) and J.S. both met with the TAs to go over the course materials including the control
Sophomore or junior students who have completed at least 3 of the 4 MCDB core courses
and 2 previous lab courses participated in this study. Students (n = 101) who completed
the standard CBLC without the control intervention at the end of fall semester in 2009
served as the control cohort. Students (n = 40) who took the spring 2010 CBLC with the
control intervention served as the experimental cohort. Sixty-five percent and 63% of
study participants in the control and experimental cohorts respectively took the Molecular
Biology course concurrently or prior to the CBLC.
We developed two sets of questions to probe student thinking on experimental design and
controls (see Appendix 1: Pre/Post Assessment). The first set of questions evaluates
student understanding of a “negatively controlled experiment” and basic mathematical
reasoning skills within the context of experimental data
(adapted from Stanovich, 2009)
The second question set represents a typical experimental scenario and evaluates student
understanding of both the positive and negative control experiments. Within the second
question set, students took the first four questions (2.1 – 2.4) in the pre-assessment and
four additional questions (2.5 – 2.8) in the post-assessment. Students were given 15 and
30 minutes to complete the pre- and post-assessment respectively. Since students were
not aware that these were assessment questions, some students discussed the questions
with neighbors in both the pre- and post-assessments. Students first identified the
experimental conditions in the format of multiple-choice responses [e.g. positive control (P),
negative control (N), experiment (E) or unnecessary (U)] and then explained the purpose
for each identified control.
Our intervention included one online control tutorial, which students completed outside of
class, and seven in-class control exercises. Six of these seven exercises involved
identification of positive and negative control experiments and experimental groups within
an experimental scenario and the generation of conclusions based on these controls (see
Appendix 2: Example of a Control Exercise). For the seventh exercise, students designed
an experimental scenario based on provided questions and results. For each in-class control
exercise, students first worked individually and then in collaborative groups made of 3-4
students. It took about 20 minutes to complete each exercise. Each exercise was worth 5
or 10 points upon completion. TAs read through student responses, shared the discovered
incorrect explanations with one another at the next TA meeting and discussed a set of
common incorrect explanations with students in the next lab period.
Data Collection and Analyses
We collected post-assessment data in the fall 2009 standard CBLC (no intervention), and
both pre- and post-intervention results in the spring 2010 CBLC. We compared student
performance in the spring 2010 CBLC by the measure of pre- and post-multiple choice
selections and pre- and post-written responses to explain the controls. We used ANOVA to
analyze results for the multiple-choice assessment when three groups were compared.
When two groups were compared, data were analyzed using both the effect size and
independent samples t-tests. Effect size was used as a measure of standardized
differences between two means (M1 and M2) and was calculated as d = (M1 – M2)/s, where
s is standard deviation. An effect size of < 0.4 is generally considered to indicate a small
effect, 0.4 – 0.8 a medium effect, and > 0.8, a large effect
. Two biologists
who were not involved in the study coded the student written responses for cohesiveness.
Two attitude survey questions (see Results below) were given to students during the last
week of the 2010 CBLC. Permission to use student survey data and the pre- and
postintervention results (exempt status: Protocol no. 0108.9) was obtained from the University
of Colorado Institutional Review Board.
Response to the First Set of Assessment Questions
The first set of questions presents a common drug trial scenario followed by a series of
questions (see Question 1 in Appendix 1). The first question (A) provided four categories
with either a drug treatment or a placebo; students were asked to indicate whether each
represented an experimental or a control group. The second question (B) asked, “If there
is a control, what did it control for?” Virtually all students answered these two questions
correctly on both the pre- and post-assessments. The third question (C) asked: “Is there
a positive control in this experiment?” Twenty-three percent of students thought that the
placebo was the positive control on the pre-assessment. However, all students thought
the placebo was a negative control on the post-assessment, indicating that students had
learned to recognize a negative control and distinguish it from a positive control. In
response to the fourth question (D) about whether the drug was effective, 35% of students
thought the drug was effective on both the pre- and post-intervention assessments. Since
it requires a mathematical calculation to answer this question and we did not address the
math issue in this class, we did not expect any change in answering this question between
the pre- and post-intervention results. Nevertheless, the result indicates that a significant
proportion of students relied on impressions rather than calculations to draw conclusions
about experimental results.
Response to the Second Set of Assessment Questions
The second set of questions presents a hypothesis and an experimental scenario (see
Question 2 in Appendix 1). Figure 1 shows that most students failed to identify the positive
control experiment on the spring 2010 CBLC pre-assessment. Students also had difficulty in
identifying the two negative controls, and to a lesser degree, the experimental group on the
pre-assessment. Students who did not do the control exercises in fall 2009 (i.e., control
cohort: without intervention) had a mean post-assessment score similar to the mean
preassessment score of spring 2010 CBLC students (t-test; p > 0.05 and effect size; d = 0.4
medium). However, the mean post-assessment score for students who completed the
control exercises (experiment cohort) was significantly higher than the mean
preassessment score for the experimental cohorts and the mean post-assessment score for the
control cohort [(ANOVA; p < 0.001; effect size d = 0.2 – small (i.e., measures the effect
size between the mean post-assessment scores for the control and experimental cohorts)].
One significant caveat to this conclusion (as well as all multiple-choice type instruments) is
that an analysis of students’ written responses revealed that not all students who correctly
identified the controls via multiple-choice response had coherent or correct explanations in
the short response section. Figure 2A shows the distribution of student pre-assessment
choice and explanation for the positive control (Question 2.1). Forty students took both the
pre- and post-assessments. Seventeen percent of students identified the positive control.
Of these 17% of students, only 5% provided a correct and coherent explanation, while 10%
did not provide any explanation and 2% provided non-coherent explanation. The remaining
83% of students misidentified the positive control as either unnecessary (P = U; 40%), an
experimental condition (P = E; 35%), or as a negative control (P = N; 8%). The
postresponse for this question (Figure 2B) revealed that not only more students (40%)
identified the positive control, but all these students also provided correct coherent
explanations. Moreover, no student mistook the positive control for a negative control
(P = N; 0%). A higher percentage of students mistook the positive control for an
experimental group (P = E; 45%). Interestingly, of these 45% of students, 13% of them
provided an explanation implying that they understood the concept of a positive control but
were just confusing the terms, not the concept. For example, many students stated that
the purpose of including this condition in this experiment is the “need to verify the NK cells
are actually expressing the protein after the viral infection”. Fewer students thought that
the positive control was unnecessary (P = U; 15%); of these 15% of students, 5% of them
provided an incorrect rationale. An example of these incorrect explanations is: “if a gene is
placed inside of cells, the protein of interest should be present inside of the cells”. This
suggests that some students failed to answer this question correctly based on a lack of
Figure 3A shows the distribution of student pre-responses to the first negative control
question (Question 2.2). Twenty two percent of students correctly identified the negative
control (there were a total of 40 students). Of these 22% of students, 7.5% provided
correct coherent explanations, 12.5% did not provide any explanations, and one student
(2.5%) provided non-coherent explanation. The remaining 77.5% students mistook the
negative control for either a positive control (N = P; 47.5%), unnecessary (N = U; 17.5%)
or experiment (N = E; 12.5%). The post-response for this question revealed that more
students (52.5%) were able to identify the negative control, and most of them (81%) also
provided correct coherent explanations (Figure 3B). While encouraging, we note that this
represents barely a majority of the students who can actually provide a coherent
explanation of a negative control. Figure 4 shows the distribution of pre- and
postresponses for the second negative control question (Question 2.3). Although a similar
number of students identified this as a negative control on both the pre- and
postassessments (57.5% and 62.5%), more students provided post explanations (42.5%
versus 18% for the post- and pre-responses respectively). A significantly higher
percentage of students (40% versus 7.5%) provided correct coherent explanations on the
post-assessment. In summary, analysis of student thinking through their written responses
revealed that the most prominent confusion centered on the difference between a positive
control and an experiment. Some students also confused a negative with a positive control
for this experimental scenario.
In addition to the four questions that students answered before and after the control
exercises, four additional questions were given only as a post-assessment in order to
further probe student thinking (Figure 5). Many students had trouble indentifying the two
unnecessary experiment conditions, although most students did recognize the third one as
unnecessary condition. For the first unnecessary condition, a majority of students mistook
it as a positive control (U = P; >90%). For the second unnecessary condition, a majority of
students mistook it as a negative control (U = N; >90%). The reason that these two
conditions were unnecessary is because they refer to a different cell type, and students
simply ignored this fact (see Question 2 in Appendix 1 for detail). Of the 60% students who
recognized the additional negative control for this experiment, all of them provided correct
coherent explanations. This result is consistent with the finding that about 60% students at
the end of the 2010 spring CBLC course indentified the negative controls (Figure 1).
We asked if students who took the Molecular Biology lecture course were more prepared to
correctly answer the control assessment questions than students who had not taken the
course. We found that there was no statistical difference in student pre-test performance
between the students who had and had not taken the Molecular Biology course for both the
fall 2009 control (66 vs. 35 students; t-test; p > 0.05) and the spring 2010 experimental
cohorts (24 vs.16 students; t-test; p > 0.05).
We asked whether students thought that the various control exercises helped their own
research projects. Seventy percent of students thought they helped in designing their
research projects (Figure 6). Sample student quotes are listed below.
Quotes from “moderate help”:
“The controls are an essential part of biology experiment. Without the control
exercises, I had no experience identifying these types of things, and I think experience is
absolutely necessary in order to improve”.
“Control exercises provide practice for planning our experiment”.
Quotes from “little help”:
“The controls for our research project were simple whereas the ones given
throughout the semester were complex, and at times, difficult to understand”.
Students had a mixed response to the second survey question, e.g., “rate the difficulty level
for the various control exercises”. They seemed to indicate that it depended on the
individual control exercise; some were easy, others were difficult.
Our control exercises were designed to help make students aware that both positive and
negative controls are necessary when designing an interpretable biological experiment.
Here we run into some real world complexities; in particular, it is not always possible to
have both types of controls; positive control experiments can often be quite difficult to
construct. For example, consider the situation in testing a new drug for a disease. If the
drug is a small molecule, we can determine the purity and homogeneity of the sample to
be used in the study, but if the molecule exists in multiple forms (like a protein might) and
has no easily assayable activity, it can be more difficult to devise a way to standardized
experiments (for example, to test the efficacy of a vaccine in a particular group). In this
light, herbal extracts can be difficult to test if we do not know the concentration of the
“active ingredient” (assuming that such an active ingredient has been identified). Different
batches of the “same” substance make a dramatic difference in “potency”. Often we are left
to conclude only that the substance tested and no significantly different effect than the
negative control. It becomes a skill to even recognize when a positive control is not
possible. Alternatively, sometimes multiple positive and or negative controls are needed to
produce meaningful results or to judge the reproducibility of the observed behavior (a topic
not explicitly considered in this study). How many controls and what types are needed
within a particular experimental scenario depends on what questions are to be asked and
what we already know about the particular biological system to be used.
Based on the poor ability of students to explain positive and negative control experiments,
even after two introductory level laboratory courses (as well as multiple science courses,
which one would presume would address these issues explicitly), we developed an
intervention to help students better analyze experimental design. Our results indicate that,
after completing eight control exercises in a one-semester cell biology lab course, many
students improved their the ability to both correctly identify control experiments and to
offer coherent and correct explanations of the purpose for these controls. In addition, more
students were able to differentiate a positive control from an experiment or a negative
control. That said, we are under no illusions that this particular intervention cannot be
dramatically improved; we only point to the fact that explicitly and repeatedly raising the
issue of positive and negative control experiments does seem to help. Better interventions
and more intense and rewarding experiences for students are likely to produce even more
robust scientific “habits of mind.” In this light, it is worth remembering that the
improvements observed were specific to the context of our intervention. While students
showed overall improvement on the post-assessment, they failed to show improvement on
the drug effectiveness for Question 1, which requires mathematical and analytical
reasoning. Notably, the post-performance of the control cohort (fall 2009 CBLC students)
was similar to the pre-performance of the spring 2010 CBLC students, and the
postperformance of the spring 2010 students was significantly better than either of these groups
Our data show that more students recognized the second negative control than the first
negative control on the pre-assessment. There are two possible explanations. First, we
investigated whether students who had taken a molecular biology course concurrently or
prior to the CBLC (65% and 62% of the 2009 fall and 2010 spring CBLC students
respectively) had an advantage answering the assessment questions though we intended
to make the assessment questions content-independent. We found no statistical difference
between the two groups. Second, during the one-semester interaction with students and
specifically from student pre-assessment written response, we discovered that many
students thought a negative control was simply adding “nothing” to an experimental
system. This thinking explains why more students (58%) recognized that infecting cells
with an “empty” vector was a negative control (the second negative control) than the first
negative control (22%) on the pre-assessment.
Student written responses provided insight into student thinking. While some students
provided coherent explanations when choosing the correct answers this was by no means
universal; a number of students choose the correct response and provided an incorrect
justification. This was demonstrated in the response to the second negative control
condition where a similar number of students identified the negative control on both the
pre- and post-assessments, but a significantly higher number of students provided coherent
explanations on the post-assessment than the pre-assessment. We conclude that we need
to look at both the multiple choice and especially the written responses to reveal true
student understanding [an insight we are not the first to have – see
(Nehm & Reilly, 2007)
However, not all students provided written responses. There are two possible reasons for
this. First, since both the pre- and post-assessments were not graded, some students may
not have made the effort to provide what they thought were unnecessary written responses.
Second, it is possible that students were more confident and therefore more enthusiastic
about providing written responses on the post-assessment than on the pre-assessment.
(e.g., for Question 2.1, 7% and 40% of students provided pre- and post-written responses
respectively; for Question 2.2, 10% and 45% of students provided pre- and post-written
responses respectively, and for Question 2.3, 20% and 42.5% of students provided
preand post-written responses respectively).
It would be informative to measure students’ ability to transfer what they learned about
experimental design through the control exercises to their final research projects. Since
each student group research project was evaluated based on the overall oral presentations
by the group members, it was difficult to make correlation of the experimental design and
the post-control performance for each student. Nevertheless, all research groups except
one (a group composed of a single student requested to work on his own) included and
discussed controls in their experimental design. We will evaluate these students as they
progress to senior year using a capstone or exit assessment that includes questions
targeting experimental design (in development).
Teaching students to think experimentally is both important and non-trivial; it is necessary
for them to objectively and skeptically evaluate the various claims made by many experts.
Thinking like a scientist should allow them to understand the reach and limitations of
scientific conclusions. In this study we provided students the opportunity to think explicitly
about experimental design and why various types of controls are essential in order that
rigorous conclusions can be drawn. It is clear from our data that knowing how to design
an experiment, and being familiar with the different roles of controls requires continued
practice. Our results show a first, albeit modest, successful step towards achieving this
How do we use the results from studies of student thinking to improve our courses and
curricula? Clearly, the first step is to disseminate our observations as widely as possible,
starting with our own department. We found that our faculty believe designing control
experiments is an essential skill, similar to those in other science departments
Wenderoth, Cunningham, & Dirks, 2010)
. However, these same instructors do not, by their
own admission, explicitly teach or reinforce such a skill in their courses. Because even
advanced students struggle with these ideas, we suggest that instruction about controlled
experiments be explicitly incorporated into every science course. We recommend that for
every experiment mentioned in lecture, instructors take time to promote student discussion
of the way measurements were carried out and which experimental controls were required
to produce rigorous conclusions. This would provide students the opportunities to learn
about both the various types of controls and their significance in the context of critical past
studies. Students can then practice such a skill of designing control experiments in every
lab course. As students learn more about the design, implications, and limitations of
biological experiments during their undergraduate education we can, at the very least,
expect to train them in the dispassionate analysis of research results. In this same light, a
more rigorous introduction into the application of statistical analyses, including effect size,
is likely to be helpful in interpreting experimental results.
We are grateful to Carl Wieman, Bill Wood and Jennifer Knight for helpful discussions in
preparation for this manuscript. We thank the teaching assistants for their advice on ways
to improve the control exercises and the control assessment questions. This study was
supported by the Science Education Initiative at University of Colorado.
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Appendix 1: Pre/Post Assessment
1. 340 patients with Alzheimer' s disease are enrolled in a study of a new drug. The results
from the study are:
❏200 were given the drug and their symptoms improved
❏75 were given the drug and their symptoms did not improve
❏50 were given a placebo and their symptoms improved
❏15 were given a placebo and their symptoms did not improve
(A) For each of the four categories above indicate whether it represents an experimental or
a control group.
(B) If it is a control group, what did it control for?
(C) Is there a positive control group in this experiment? If so, what does it control for.
(D) Based on these data, was the drug effective? (justify your answer).
2. To test the hypothesis that high levels of a viral protein (LMP-1) inhibit cell division in NK
cells, the researchers have:
1. constructed viral vectors that express either LMP-1 and Green Fluorescent Protein
(GFP) together or GFP alone in NK cells.
2. developed an antibody that recognizes LMP-1 protein.
3. devised a method to efficiently infect NK cells.
4. devised a method to identify those NK cells that have divided during the
For each experimental choice, indicate whether this is a positive control (P), a negative
control (N), experimental (E), or unnecessary (U).
For control experiments, explain what they control for.
2.1 P ❏ N ❏ E ❏ U ❏
2.2 P ❏
N ❏ E ❏ U ❏
2.3 P ❏ N ❏ E ❏ U ❏
2.4 P ❏ N ❏ E ❏ U ❏
Determine whether the LMP-1 protein is present in LMP-1/GFP infected NK cells.
Infect NK cells with the GFP vector and count the number of GFP-expressing cells that divided during the experimental period.
Infect NK cells with an “empty” vector (e.g., expresses neither LMP-1 nor GFP), and count the number of virally infected cells that divided during the experimental period.
Infect NK cells with the LMP-1/GFP vector and count the number
of infected cells that divided during the experimental period.
2.5 P ❏ N ❏ E ❏ U ❏
Examine a cell type known to express LMP-1.
2.6 P ❏ N ❏ E ❏ U ❏
Examine a cell type known not to express LMP-1.
2.7 P ❏ N ❏ E ❏ U ❏
2.8 P ❏ N ❏ E ❏ U ❏
Determine where LMP-1 protein is located in LMP-1/GFP infected NK cells
Examine NK cells for the expression of LMP-1 before viral infection.
If the NK cells divided, what are the possible explanations?
If the NK cells did not divide, what are the possible explanations?
Appendix 2: Example of a Control Exercise
The DeDecker lab in MCDB studies the function of a previously undescribed Drosophila
gene, unglued glia (ugg). Ugg mutants are embryonic lethal. Ugg is thought to be a seven
transmembrane receptor protein. In order to determine what is wrong in homozygous ugg
mutant embryos, stage 16 embryos were fixed and stained for HRP (which is expressed
specifically in neurons at this stage) and Repo (which is expressed specifically in glial cells).
This was the result:
A) Positive control experiments are designed to ensure that reagents work and procedures
were carried out correctly.
B) Negative control experiments are designed to check whether experimental outcomes are
due only to the specific variable being tested.
C) We have access to a previously characterized mutant, glial cell missing (gcm), which
does not develop detectable glial cells and death with nerves (dwn), in which homozygous
embryos die during development at the same time as homozygous ugg embryos.
1. Were positive control(s) included in this experiment?
❏ Yes. The following were positive control(s) and they controlled for
❏ No. What should the experimenters have done?
❏ No. What could be used as a negative control?
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2. Were negative control(s) included in this experiment? ❏ Yes. What is it and what is it controlled for? 3. Given the control(s) that were included, what can you conclude from this experiment?