Pay Dirt: Multiple Approaches to Cooperative Learning in Physical
Geography
Richard Knox and Gavin Schwan
This paper was completed and submitted in partial fulfillment of the Master Teacher Program, a 2-year faculty
professional development program conducted by the Center for Faculty Excellence, United States Military
Academy, West Point, NY, 2016.
Abstract
This paper compares three approaches to cooperative learning in a large introductory
physical geography class. Student performance in cooperative learning laboratory exercises was
correlated with exam performance. Roughly 500 lower-division students experienced varying
levels of in-class, cooperative learning with instructor supervision and out-of-class work. We
found a very low correlation between lab work and exam performance, with R-squared values
varying from 0.02 to 0.21. Terms experiencing the highest correlation between lab and exam
performance involved the greatest amount of in-class work and instructor contact. While
inconclusive, this paper encourages the consideration of cooperative learning, assessment
structures, and instructor contact in delivery of physical geography courses.
Introduction and Research Context
According to V.L. Clegg (1979), effective teaching should capitalize on students’ natural
curiosity in order to promote motivation and thereby increase learning. Presentation of a
problem and provision of a modicum of direction and structure in a supervised classroom
environment should encourage student initiative and analysis that makes learning fun and
improves understanding. This philosophy nests well with cooperative learning, generally
typified as students working together in small groups to accomplish a task that furthers their
individual learning (Watson, 1992; McKeachie and Svinicki, 2006). Indeed, research into
cooperative learning techniques have shown increased student participation and satisfaction,
strongly suggesting that students prefer cooperative methods as compared to traditional lecturebased classroom instruction (Kraft, 1985; Lyman and Foyle, 1991; Lindquist, 1995; Stelt, 1995;
Miller and Groccia, 1997; Karim, Rutledge, and Titard 2000; Brown and Klein, 2003; Gupta,
2004; Saunders, 2008). Cooperative learning techniques are thus generally considered effective
in harnessing student curiosity and encouraging motivation, and have likewise been shown to
improve learning performance (Ravenscroft, et al., 1995; Hampton and Grudnitski, 1996; Hite,
1996; Nowak and Miller, 1996; Whicker, Bol and Nunnery, 1997; McKeachie et al., 2006).
Still, research does exist evidencing a negative or weak relationship between cooperative
methods and improved learning as assessed by test and course scores (Herzog and Lieble, 1996;
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Kunkel and Shafer, 1997; Brown et al., 2003; Smith, 2007). Cooperative learning techniques are
many and varied (Watson, 1992), and mixed results may therefore indicate that some methods
are better than others, potentially dependent on environment and student composition, or that
there are better ways of implementation in the classroom.
With these factors in mind, the Introduction to Physical Geography course (EV203), a 40
lesson compulsory course at the United States Military Academy known locally as “Dirt”, is
structured with several lab periods during which students are assigned to work in pairs to
complete various exercises provided in a course-required lab manual. Each term, roughly 500
students were enrolled in the course with class sizes of 15 to 18 students per instructor. Watson
(1992) calls this method of cooperative learning, “learning together,” which is little addressed by
existing literature as concerns college-level geography and physical science courses, although
this appearance may be due to differences in terminology. In Herzog et al (1996), this technique
(described though not so named) is examined with inconclusive results, although the researchers
do find, in concert with numerous other studies identified above, that students evidently
preferred cooperative learning activities as opposed to lecture-based classes. Smith (2007),
however, reported a weak correlation between grades and similar group lab work in a geography
classroom. Additional studies (Lyman et al., 1991; Gupta, 2004) analyzing the “learning
together” technique in a physical science classroom only assess student preference without
considering any measureable effects on learning.
The purpose of this research was twofold. First, we sought to assess the value of lab
work in EV203 in terms of its impact on overall learning as could be determined by individual
student grades on tests. The data sets available following a restructuring of the course in the Fall
Term of Academic Year 2014 further allowed us to consider three separate terms, over which
time the lab experiences varied in instructor-student contact and student time spent working
individually and cooperatively. Specifically:
Fall Term, Academic Year 2014 (Term 141):
Labs were assigned at the beginning of the lab period and were to be turned in at the beginning
of the following class period. Students worked in groups of two or three and turned in labs
individually.
Spring Term, Academic Year 2014 (Term 142):
Labs were assigned the class period before the lab period and were due at the end of the lab
period. Although permitted to work in groups of two or three, a small number of students would
turn the lab in at the beginning of the lab period, having worked on the lab in their own time and
without any supervision or help from their peers or guidance from their instructors. Students
were still instructed to submit labs individually for a grade.
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Fall Term, Academic Year 2015 (Term 151):
To avoid cadets working individually, labs were assigned at the beginning of the lab period and
were due at the end of that same lab period. In most cases students were still instructed to submit
labs individually for a grade, but a minority of instructors, allowed the latitude, permitted groups
to turn in one lab for a group grade that was applied individually to all students in the group.
This method of delivery continues to the present time.
With these differences in lab delivery, the second goal of this research was to assess these
separate methods to determine if one benefitted students more than the others. Additionally, it
afforded the opportunity to measure not only the value of cooperative learning but also studentinstructor contact. Instructors provide valuable context and framing to student groups working
on lab assignments in class, and thus the method of lab delivery should ideally maximize
student-instructor contact while still promoting cooperative group work. As such, we
hypothesized that the method of lab delivery practiced in Term 151 would show the best results.
During that term, students were required to complete all work in class, ensuring that all work was
cooperatively executed. This method further permitted instructors to monitor student progress,
check work, and provide guidance as necessary to shape student understanding. We therefore
expected to find that lab scores and test scores were higher in Term 151.
Methodology and Data
This research made use of lab, exam 1 and 2, and the final exam scores from students
enrolled in EV203, during the 141, 142, and 151 terms. Falling around lesson 20, exam 1
evaluated material explored in the weather and climate block and labs 1, 2, 3, and 4. Exam 2,
near lesson 32, evaluated material covered during the geomorphology block and labs 5 and 6.
The final exam, after lesson 40, evaluated material from all labs, both exams, and 6 or 7 other
lessons.
Analysis was conducted in three general categories: exam 1 and corresponding labs,
exam 2 and corresponding labs, and the final exam and all labs. Labs and exams differed
slightly between terms. To evaluate how these differences could impact this research, a mean
analysis of scores in each term was conducted. To determine how lab performance correlated
with overall course performance, a linear regression was conducted between corresponding labs
and exams. A coefficient of determination (R squared) was determined.
Results
The mean analysis of scores and R squared values are illustrated in figure 1 below. The
linear regression and R squared for the final exam and all labs is illustrated in figures 2, 3, and 4,
below.
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Labs 1-4
Exam 1
R squared
Mean
All terms
89.2
80.1
141
-0.8
1.1
(0.18)
Term +/142
0.5
-1.0
(0.15)
151
0.2
-0.2
(0.19)
Labs 5-6
Exam 2
R squared
91.2
81.1
0.1
-0.4
(0.09)
0.7
-0.2
(0.03)
-0.9
0.6
(0.02)
All labs
Final Exam
R squared
90.0
79.9
-0.4
-0.1
(0.21)
0.6
-1.0
(0.17)
-0.3
1.2
(0.21)
Figure 1: Means and R squared values of labs, exam 1 and 2, and the final exam
This chart illustrates mean values for labs, exams 1 and 2, and the final exam. The left column is
the three-term mean value and the subsequent 3 columns illustrate that terms difference from the
mean, either positive or negative (in gray). The R squared values between labs and
corresponding exam were all positive and are found in parentheses. Term 141 n = 536, term 142
n = 428, term 151 n = 583.
Figure 2: final exam and all lab scores, term 141
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Figure 3: final exam and all lab scores, term 142
Figure 4: final exam and all lab scores, term 151
Discussion
With R squared values between 0.02 and 0.21 for labs and exams our analysis is
consistent with many researchers (e.g. Herzog and Lieble, 1996, etc.) that found a weak
correlation between cooperative learning events and assessments. Generally, correlations
compared closely across similar events for all terms with slight decreases in term 142. While all
R squared values were very low, values for exam 1 and labs and the final exam and labs were
higher between 0.15 and 0.21 while values for exam 2 and labs was near zero from 0.02 to 0.09.
This project doesn’t disentangle the impacts of cooperative learning and exam assessment
issues. However, our experience in the course allows us to offer some explanation for the
extremely low correlations. Still low, exam 1 and labs correlated much higher than exam 2 and
labs. It is thought that exam 1 questions more closely match the type of questions posed in labs
compared to exam 2 and labs. Instructors frequently tells students to use labs to study for exam
1 but rarely offers that advice for exam 2. This project certainly raises the question of matching
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assessment topics and styles between labs and exams. Is the low correlation between labs and
exams due solely to assessment differences? We don’t think so.
Term 142 is unique in that mean lab scores were high, about a ½ percent above the threeterm mean, but correlations of labs and exams were lower than correlations in terms 141 and 151
in five of six cases. It is likely these observations are not just a statistical artifact and may shed
some light on this project’s second aim, namely to determine which of the lab delivery methods
benefited students the most. Students in 142 spent more time working on labs independently,
since they were able to submit the lab and leave. Students in 141 would conduct most of the
work in class and then “brush up” the lab afterwards. Students in 151 started and completed the
lab in class. At first glance, this is counterintuitive: shouldn’t less instructor supervision result in
lower overall grades? Maybe not. Generally, the students that would work on the labs
unsupervised, were driven, talented students who normally scored very well. They were “selfstarters” in other words. All else being equal, students like this were able to work in a timeunconstrained environment and perhaps score better than they normally would, leading to a ½
percent increase in overall lab scores. Or, possibly, the ½ percent difference in lab scores is an
artifact. So, then, why does this term have the lowest correlation between labs and exams in five
of six comparisons? Simply, it is likely that the instructor’s diminished impact, with this term
seeing the greatest amount of lab work completed unsupervised, outside of class, is responsible
for the low correlation between labs and grades. While students scored as well or better than
normal on labs, the instructor was unable to do a number of important things such as help
students see the big picture, make connections between the lab work and previous lessons or
blocks, and help students focus on concepts that are normally tested on. The first two items,
seeing the big picture and making connections, results in meaningful, long term learning by
allowing students to build a framework of learning, as opposed to memorizing and dumping
tidbits of information, that likely results in better outcomes. Additionally, term 142 saw less
cooperation between students, supporting cooperative learning.
Regarding term 151, our hypothesis that lab and exam scores would be higher was
partially borne out. While lab scores were slightly lower (discussed above), correlation between
labs and exam 1 and the final exam were higher. Greater cooperation and instructor contact
during laboratory exercises could certainly have resulted in more meaningful learning as shown
by the higher lab – exam correlation. The higher correlation for labs and the final exam possibly
illustrate a greater degree of long-term learning. Linkages to performance on the final exam are
of great interest given its integrative, comprehensive nature. This project bears out the
hypothesis that greater focus on cooperative learning and instructor contact at least partially
influences better outcomes in the course.
We find that term means for labs and exams vary by no more than 1.2% from the threeterm mean. Accordingly, we are comfortable assuming that differences in labs and exams
between each term is not the cause of any of the trends noted above.
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Conclusion and Recommendations
Not unlike previous studies of “learning together” styled cooperative activities in a
geography classroom environment (Herzog et al, 1996; Smith, 2007), our research finds a very
weak correlation between cooperative learning techniques and improved student assessments.
The possibility cannot be overlooked that this design of cooperative learning is ineffective in
improving student understanding of geographic patterns and processes.
Existing literature seems to suggest the popularity of problem-based learning (PBL) in
college-level geography classrooms vice cooperative learning techniques as a whole. PBL is a
collaborative learning style that differs from cooperative learning in that students are assigned to
work on different aspects of a problem and required to combine individual skills and research to
address a larger issue. Despite the apparent popularity, available studies, taken as a whole, offer
similarly mixed results as compared to literature on cooperative learning techniques. While
Spronken-Smith (2005) offers a positive view of PBL, identifying improved evaluation scores,
several others (Fournier, 2002; Chappell, 2006; Pawson, Fournier, Muniz et al., 2006) could
identify no such benefits and were cautious in recommending the learning style. In sum, these
studies into the use of both cooperative and collaborative learning styles in college-level
geography classrooms leaves little room for recommending peer learning (the umbrella category
related to group classroom work) for geography students on the basis of provable causative
relationships between peer learning and consequent improved learning.
Still, we should assume the coalescing of multiple variables when considering individual
classroom performance, regardless of the chosen learning technique. Examining variations in the
delivery of lab work, as this paper does, returns little data of consequence in terms of valuation
differences between structures, but may highlight the importance of student-instructor contact
and the relationship between peer learning and assessment structure. Future research should
weigh these variables in order to more fully understand the value of cooperative learning
techniques in the college-level geography classroom.
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