Manajemen | Fakultas Ekonomi Universitas Maritim Raja Ali Haji joeb.81.1.21-28
Journal of Education for Business
ISSN: 0883-2323 (Print) (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
"Teach Us to Learn": Multivariate Analysis of
Perception of Success in Team Learning
Ali Rassuli & John P. Manzer
To cite this article: Ali Rassuli & John P. Manzer (2005) "Teach Us to Learn": Multivariate
Analysis of Perception of Success in Team Learning, Journal of Education for Business, 81:1,
21-27, DOI: 10.3200/JOEB.81.1.21-28
To link to this article: http://dx.doi.org/10.3200/JOEB.81.1.21-28
Published online: 07 Aug 2010.
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“Teach Us to Learn”: Multivariate Analysis
of Perception of Success in Team Learning
ALI RASSULI
JOHN P. MANZER
INDIANA UNIVERSITY–PURDUE UNIVERSITY FORT WAYNE (IPFW)
FORT WAYNE, INDIANA
ABSTRACT. Considerable attention
has been given to the efficacy of teamlearning pedagogy, yet the methodology remains underused among educators
in institutions of higher education. We
suggest that the perception of success
is antecedent to greater acceptance and
use of this teaching style. Educators
and students alike must experience the
value creation potential of team learning before they will endorse it. In this
article, the authors investigated perceptions of success within the theoretical
realms of cognition elaboration, effective collaboration, and motivation perspectives. In addition to rank-ordering
the importance of these realms, the
authors make recommendations and
suggest policies to raise the likelihood
of success in team-learning practice.
T
he superiority of the cooperative
learning method over the traditional
lecture style of teaching is well established in the literature. The basic tenets
of cooperative learning are inter-group
positive interdependence and individual
accountability (Cottell & Millis, 1993;
Slavin, 1992). Most scholars support the
proposition that group-based instructional methods can be used to promote the
achievement of desirable learning outcomes in institutions of higher education.
To be specific, researchers advocated
team-learning pedagogy as the main
delivery scheme. Maier and Keenan
(1994) described team learning as “a
large number of structured, systematic
in-class techniques that engage students
in group work toward a common goal”
(p. 358).
Despite decades of research on team
learning and an overwhelming consensus
on team-learning efficacy, its use in colleges and universities is limited.
Research by Becker (1997) showed an
absence of team-learning techniques “in
all economics courses at research universities” (p. 1354). Hernandez (2002)
reported that students resisted participating in team-learning activities. Ravenscroft, Buckless, McCombs, and Zuckerman (1995) and Imel (1999) similarly
discussed teachers’ reluctance to employ
team-learning methods in their classes.
In search of a successful formula for
team learning, researchers have concen-
trated on a variety of structures and
techniques. For example, Karp and
Yoels (1987) concentrated on students’
group participation optimization, Johnson, Johnson, and Smith (1991) stressed
skill heterogeneity in the group, Fiechtner and Davis (1992) suggested a minimum allocation of grades to teamwork,
Li Wan Po (1994) emphasized inclusion
of an employer practicum in team
activities, and Bartlett (1995) discussed
free-rider problems. Also, Tanner and
Lindquist (1998) researched the relationship between attitude formation and
performance. Many authors have even
suggested detailed processes for administration of team learning. Examples
include Cottell and Millis (1993), Hernandez (2002), Michaelsen and Black
(1994), Michaelsen, Fink, and Knight
(1997), and Persons (1998).
We suggest raising the likelihood of
success is antecedent to promoting the
use of team-learning pedagogy in institutions of higher education. In this article, we redefine “success” in terms of
student perceptions. Perceptions were
measured using the academic achievement theoretical perspectives proposed
by Springer, Stanne, and Donovan
(1999): (a) motivational, (b) affective,
and (c) cognitive. These perspectives
are based on the proposition that what
students learn is influenced by how and
why they learn. Once they experience
its value creation potential, both stuSeptember/October 2005
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dents and faculty will be more amenable
to team learning.
Review of the Literature
Traditional Teaching Versus
Cooperative Learning
The shift from a teacher-focused
method to a learner-focused approach
came about as a result of a major paradigm shift from teaching to learning in
the past few decades (Saunders, 1997).
Now, most educators involved in higher
education agree that the traditional pedagogy of teaching does not lend itself to
the creativity and problem-solving ability that are expected of learners. Under
the traditional method of teaching, the
instructor is considered the source of
“ultimate truth,” whose skill in disseminating knowledge is derived from the
ability to perform well on the classroom
stage. Students are expected to learn
more only if the professor does a better
job of delivering materials through professing with “style” to a captive audience (Michaelsen & Black, 1998). In
the traditional setting, students are passive listeners; yet, they are expected to
possess extraordinarily long attention
spans, retention skills, powerful imaginations, and, most important, excellent
memories, to regurgitate that knowledge
and prove their success by passing an
examination. A number of scholars in
various business as well as nonbusiness
disciplines have abandoned the preoccupation of educators in favor of
improving their own performance, alone
in the classroom. The bias toward
improving information delivery methods rather than spending time developing students’ learning has been documented, for example, by Becker (1997),
Brown (1997), Chonko (1993), Guskin
(1994), and Johnson et al. (1991).
The main thrust of the new paradigm is
a shift of focus on student and learner
development. To effectively enhance
learning skills, Slavin (1980) argues that
students must be closely involved in the
learning process. Johnson et al. (1991)
emphasize the greater need for direct and
active student involvement in the classroom. The new concept of involving students in the learning process calls for a
major change in the traditional role of the
22
Journal of Education for Business
instructor. In the new paradigm, the
teacher becomes a facilitator for learning.
According to Bobbitt, Inks, Kemp, and
Mayo (2000), instructors “should be the
designers of a learning environment in
which students are active participants in
the learning process” (p. 15).
Active participation in learning is not
confined to taking notes or raising a
hand and responding to questions, and
neither is paper presentation. It is
accomplished through cooperative
learning with group activities. The
effective pedagogy in cooperative learning is teamwork. Becker (1997, p. 1360)
describes the team-learning process as
“think, pair, and share.” In this process,
students discuss, refine, and articulate
issues posed in class and provide a team
response in collaboration with each
other. The main idea is that within the
psychological safety of the team
(Edmondson, Bohmer, & Pisano, 2001)
of cooperative and responsible peers, a
deeper level of thinking takes place
(Knabb, 2000). In the process of sharing
and communicating their thoughts, students develop a kind of collective learning synergy that surpasses the sum of
their individual efforts (Mutch, 1998).
Team-Learning Pedagogy
The primary focus of team learning
is to fashion a learning environment
and process where students are actively involved in learning. There is a common understanding among scholars of
the required elements of team teaching. Cottell and Millis (1993) argue for
five features as requisites for a successful team-learning experience: (a)
student interdependence, (b) individual
accountability, (c) appropriate grouping, (d) social skills interaction, and
(e) group monitoring.
The debate is on how extensively to
apply these elements in the classroom.
The purpose is to foster a learning environment conducive to group interaction.
Stringency of team rules, and the extent
to which they are implemented, is the
core difference between cooperative and
collaborative styles of team learning.
The main tenet of collaborative learning
is achievement of higher levels of learning through the intellectual efforts of
students, or students and instructors
together (Smith & MacGregor, 1992).
This is accomplished primarily through
positive interdependence and individual
accountability (Slavin, 1989). Collaborative learning methods are unstructured, and students usually establish
rules. For example, students determine
group membership, rules of engagement, and procedures for contributions
and accountability.
If we envisage collaborative learning
as the initial position of a stringency
scale continuum, cooperative style
would appear on the opposing pole.
Cooperative style is defined as “a large
number of structured, systematic inclass techniques that engage students in
group work toward a common goal”
(Maier & Keenan, 1994, p. 358). In
such a setting, the instructor generally
controls the teams’ functions through a
set of predetermined policies and activities. As such, team goals are well
defined, the instructor selects team
members and assigns them to interrelated roles, length of debates and problemsolving activities is monitored, and each
team member is held accountable for his
or her contribution to team and individual learning.
As Springer et al. (1999) point out,
“the many forms of cooperative and collaborative small-group learning do not
follow from a single theoretical perspective” (p. 24). Divergent methods
and variable results from empirical
studies reflect this fact. Lancaster and
Strand (2001) summarize the results of
10 team-learning studies in the area of
accounting and report diametrically different outcomes. These mixed results
are symptomatic of the preponderance
of discipline-specific studies. In their
quest for a successful formula, scholars
experiment with a variety of strategies.
For example, Johnstone and Percival
(1976) suggest limiting classroom lectures to a maximum of 18 min in chemistry classes. Bobbitt et al. (2000) favor
combining lectures with real-world
events to improve learning in marketing
theory classes. Ravenscroft et al. (1995)
contend that, in addition to group
grades, individual test scores must be
assigned in accounting classes to further
motivate team efforts for a more positive outcome. Although proclaiming the
usefulness of team-learning pedagogy,
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Johnson, Johnson, and Stanne (2000)
correctly point out the impossibility of
devising a unique, effective method
across educational disciplines.
Research
According to Lancaster and Strand
(2001), learning models are not transferable across educational disciplines;
they asserted that “what works for one
teacher in a particular situation may not
work for another in a similar or different
situation” (p. 554). Team-learning activities can take a number of forms, limited only by the creativity of the instructor. In this study, we are searching for a
common ground for team-learning success, beyond the pedagogical differences. We posit that although there is no
guarantee of consistently desirable outcomes, a better understanding of the
determinants of team-learning effectiveness will improve the likelihood of
achieving preferred outcomes.
Springer et al. (1999) articulated
three interrelated theoretical perspectives to describe the “efficacy of smallgroup learning” (p. 24). The first is Cognitive Elaboration. They contended that
new information is best retained when
linked to information already present in
memory. By describing and elaborating
on classroom issues, team members
establish this necessary association.
The second perspective is Affective
Collaboration. Here, the objective is to
increase interaction among peers. This
can be accomplished not just by affording students an opportunity to communicate, but also by stimulating a desire
to participate and discuss and exchange
ideas. Conversing about issues simultaneously enhances learning for both the
listener and the communicator. This
facilitates the learning process, as long
as students remain focused and are less
restricted with rules of engagement.
Finally, the third perspective is Motivation. If students value the success of the
group, they will support each other individually and collectively to succeed. This
requires that students view the process as
cooperative instead of seeing it as competitive. The emphasis is on the necessity
of individual accountability for learning,
to motivate students to share ideas well
beyond merely sharing correct answers.
For students to effectively participate in team learning, they must feel
rewarded by success. They must
understand that success is a complex
process, with high test scores composing only a fraction of their expected
performance. Equally important to students should be that their peers do
well. This can be accomplished if each
student makes a connection with the
material prior to team activities, and
then effectively communicates and
helps peers to relate and comprehend
it. After all, everyone can share knowledge and perform better together.
Instrument Development and
Data Collection
The data for this study were collected
from economic principles classes in a
medium-sized, state-sponsored, regional university in the Midwest. The
Department of Economics is part of the
School of Business, which is accredited
by the Association to Advance Collegiate Schools of Business (AACSB).
The university promotes the individual
attention given to students because of its
small classes. Economics classes are
generally capped at 35 students and are
taught by experienced and academically
qualified faculty.
The questionnaire was developed in
three stages. First, students in a pilot
group were asked to evaluate a grouplearning experience. These results provided a preliminary basis for a pilot
instrument, which we field tested on
three groups of four students each.
Based on the field test results, we developed and administered another instrument to an economic principles class for
further refinements prior to using it with
the classes actually involved in the
study. We administered the finalized
survey questionnaire to six economic
principles classes within a three-semester period.
Two instructors were involved in this
study. Prior to the start of each semester,
instructors coordinated their coverage,
class activities, and procedures.
Although a team cooperative learning
approach was emphasized, the implementation process included collaborative elements. The instructors handled
the groups’ goals by defining assign-
ments, timing for lecture and team
activities, grading, monitoring group
activities, and assuring appropriate
grouping (Cottell & Millis, 1993). The
students determined group size, member roles, peer assessments, and modes
of interaction. Moreover, the instructors
acted as designers and observers by
responding to questions, mediating
problems, and providing immediate
feedback to the teams.
The survey instrument was composed
of three interrelated segments. The first
contained twelve 5-point Likert-scale
questions (from 5 = strongly agree to
1 = strongly disagree) asking about students’ perceptions of success in team
learning. The students’ responses constituted the latent roots for the three constructs of Cognitive Elaboration, Affective Collaboration, and Motivation, as
suggested by Springer et al. (1999).
The second segment contained questions regarding the optimal size of the
team. Also included was a question
intended to investigate the impact of
group conflict resolution on perception of
success. Finally, questions with regard to
demographics appeared in the third segment. In addition to demographics such
as age, grade point average (GPA), gender, work status, and school status, as
suggested by Hite, McIntyre, and Lynch
(2001), other variables related to perception of success: (a) prior exposure to
teamwork, (b) expected course grade,
and (c) opportunity costs of time commitment to team activities. For example,
it is reasonable to assume that students
exposed to team learning in prior courses
appreciate the relationship between team
activities and success. However, students
with family responsibilities or full-time
jobs may resent the time spent preparing
for teamwork. A complete list of these
variables appears in Table 1.
METHOD
The sample comprised 180 students
from six economic principles classes. We
asked students to rate, on a 5-point scale,
the degree to which they agreed or disagreed with the statement that teamlearning contributed highly to their mastery of the course material. Three
subgroups emerged: (a) Group 1 included students who either agreed or highly
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TABLE 1. Selected Descriptive Statistics on Team Learning (TL)
Characteristic
Perception of success
Better attitude toward
course
Better attitude toward
instructor
Teamwork helped improve
problem solving
Pre- and posttest
reviews helped
Team presentations helped
Team tests improved
learning
Teammate achievement
important
Achievement of higher
test score
Communicate economic
concepts
Solve complex economic
problems
Understand economic
concepts
Preferred more lecture
Team
Size*
Size change preferred
Prevalent problems
% free rider
% lack of interest
% nonparticipation
% team problems solved*
Demographics
Sex (% male)
Marital status (% married)
Age
Semester hours completed
Years worked full time
GPA
Hours enrolled
Driving time to campus
(min)*
TL experience (classes)*
Expected grade*
Group 1: Cases for TL (n = 116)
Agree
Disagree
or highly
or highly
SD
%
agree (%) disagree (%)
M
3.9
0.2
0.8
0.7
M
Group 2: Cases against TL (n = 32)
Agree
Disagree
or highly
or highly
SD
%
agree (%) disagree (%)
87.2
0.0
0.0
78.2
69.2
10.2
6.3
87.5
91.1
0.0
3.1
81.2
75.6
62.3
1.4
8.6
3.1
3.2
75.0
45.1
30.9
3.0
6.4
42.0
78.9
3.9
0.0
93.8
64.1
9.0
0.0
96.9
79.5
1.3
3.1
56.3
60.3
7.7
6.3
71.9
87.2
20.5
2.6
61.5
3.1
87.5
78.2
6.2
4.8
–0.3
0.7
1.1
84.6
92.3
87.2
87.8
61.5
67.3
82.6
67.8
0.4
40.3
0.5
43.8
25.9
66.8
5.1
3.1
9.8
5.6
47.7
3.3
0.5
4.4
26.7
77.4
5.5
2.9
10.2
6.3
30.7
4.6
0.6
3.6
23.1
3.8
3.2
15.9
4.9
0.6
35.9
1.4
2.8
18.7
2.8
0.8
*p ≤ .05 significant differences between group means.
agreed with that statement, (b) Group 2
was composed of students who either disagreed or highly disagreed, and (c)
Group 3 encompassed students who gave
neutral responses. Table 1 shows descriptive statistics for Groups 1 and 2.
Because our objective was to assess the
success of team learning, we accentuated
the variance between groups by omitting
the third group from Table 1.
24
Journal of Education for Business
Further, to capture the team-learning
perspectives proposed by Springer et al.
(1999), we employed factor analysis.
The multi-item constructs that satisfied
two conditions—having eigenvalues of
one or greater and explaining at least
5% of total variance—are included in
Table 2. In addition, we computed
Cronbach’s alpha reliability coefficients
for multi-item constructs used in this
study. They ranged from .79 to .92 and
were found to be acceptable. Items that
produced factor loadings of 50% or
more constituted latent roots and were
used to interpret each construct.
Finally, we used stepwise discriminant analysis on team learning. Discriminant analysis is a statistical technique that predicts group membership.
We employed this technique for two
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reasons: first, to ascertain the predictive
power of the constructs and variables
used in this study; and second, to rank
order their contribution to perceptions
of team-learning success. The criterion
variable was based on the student’s
response to whether or not team learning activities were extremely beneficial
for mastery of the course. If they agreed
or strongly agreed (Group 1), the criterion variable was assigned a value of
one. We assigned values of zero to
respondents who either disagreed or
strongly disagreed with the statement
(Group 2). We kept only significant discriminant predictors in the model by the
stepwise procedure. We dropped
insignificant predictors from the analysis, as they did not contribute to group
membership predictability.
RESULTS AND DISCUSSION
Selected results of descriptive statistics appear in Table 1. An overwhelming
majority of students in Group 1 (87.2%)
indicated they had a better attitude
toward the course as a result of teamlearning activities. In fact, none of them
reported a worse attitude. A large majority of Group 1 also agreed that teamlearning activities improved their performance. To be specific, they reported
that teamwork had improved their problem-solving abilities, as well as their
ability to understand and communicate
complex economic concepts. Most of
them reported developing a positive attitude toward the instructor, and only
20.5% preferred more lecture.
By contrast, an overwhelming majority of Group 2 (78.2%) revealed a negative attitude, with none reporting any
attitude improvement toward the course
as a result of team-learning activities.
An insignificant percentage of cases in
this group reported improvement in
learning, problem solving, understanding, or communicating economic concepts as a result of team learning. Finally, 87.5% of students from this group
preferred more lecture as opposed to the
team-learning method of instruction.
Analysis of team size and problems
associated with working in a team were
also revealing. Group 1, the group that
favored team-learning, reported a team
size of 4 (average = 3.9). They also
noted the presence of major problems
among team members, but they suggested virtually no change in the size of the
team. One may infer that the team functioned well, given the fact that the members were successful in solving 87.8%
of team problems.
By contrast, Group 2 had a significantly
larger team size of almost 5 (average = 4.8). They preferred to reduce the
group size, as appears in Table 1. The
percentage of group problems reported
by Group 2 was, in general, smaller than
that reported by Group 1. However, the
TABLE 2. Factor Matrix for Team-Learning Perspectives
Construct
Cognition elaboration
Better understand economic concepts
Solve complex economic problems
Better communicate economic concepts
Affective collaboration
Better attitude toward instructor
Better attitude toward course
Prefer more lecture than team work
Achievement of higher test score
Motivation
Team test taking improves learning
Teamwork helps improve problem solving
Pre- and posttest review improves learning
Teammate achievement is important
Team presentation improves learning
Factor
loading
Eigenvalue
% variance
explained
6.10
60.6
2.46
10.3
1.04
6.0
.76
.75
.73
.75
.68
–.55
.53
.73
.62
.56
.53
.51
Note. N = 180. Items with factor loadings ≥ .50 appear here.
members of Group 2 solved a significantly smaller percentage (67.8%) of team
problems as compared with Group 1.
Moreover, the percentage of nonparticipant (i.e., team problems) in Group 1 as
compared with Group 2 was significantly
higher. To determine if this problem was
a result of a larger team size, we calculated the correlation between the presence
of nonparticipation problems with teams
having more than four members. The biserial correlation coefficient produced a
statistically significant value of .92.
Analysis of the demographics in Table
1 indicated that prior team-learning
experience, driving time to campus, and
expected grade were the only variables
that differed significantly between
groups. The group that found team learning beneficial reported having experienced the team-learning method in more
classes and expected to receive a higher
grade in the course. It appears that the
longer and greater involvement with
team activities, the higher the chances for
the realization of its positive contribution
to students’ learning.
Results of factor analysis appear in
Table 2. Cognition Elaboration is the
first construct, with three items that
relate to student perceptions concerning their mastery of course content and
tools. Their understanding of basic
economics concepts is an important
aspect. If students believe they are
mastering the underlying economic
principles, they tend to feel more positive toward the team learning method.
Using this understanding of basic economics concepts to solve complex economics problems reinforces a positive
view of team learning. A related issue,
and the third cognitive item, is the ability to communicate economics concepts and issues. This reinforces perceptions of economics understanding
and problem-solving skills. In a group
learning setting, students must be able
to communicate with each other to
benefit from each other’s contributions. Students with poor communication skills, or those simply unwilling to
communicate with fellow team members, frequently dislike the team-learning method.
The second construct captures the
Affective Collaboration perspective
toward the team-learning method. Items
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that loaded on this construct involve student views of the teacher, course,
instructional methodology, and their
own test performance as assisting them
to reach course objectives. Overall,
these perceptions reveal student views
of how effective team collaboration was
in their advancement in the course. A
positive view of the instructor might
also enhance their outlook on team
learning because they see instructor
input as supportive. Insofar as students
are concerned, attitudes in the classroom are an important consideration in
shaping perceptions of the effectiveness
of the team-learning method.
Motivation is the third construct. This
construct grasps the essence of learning
interdependence, interaction, and
accountability among the team members as suggested by Cottell and Millis
(1993). In a group setting, students not
only learn from each other, they also
reinforce each other’s learning processes. Enhanced achievements through
team test taking, problem solving, and
presentation create strong motivation
for camaraderie and responsibility for
each other’s learning.
The results of stepwise discriminant
analysis on team learning appear in
Table 3. The discriminant function was
statistically significant, χ2 (92, N = 148)
= 97.96, and discriminating power (hit
ratio) = 96.2%.
Table 3 also contains the standardized
canonical coefficients (discriminant
weights) of the stepwise discriminant
analysis on team learning. Generally, the
size of these coefficients is indicative of
the relative importance of the predictive
variables. However, ranking of their relative importance is closely dependent on
the intercorrelation between predictor
variables. This problem (similar to the
multicollinearity problem in regression)
may cause interdependence among variables, thus producing a blurred and unreliable ranking of their relative importance.
Such problems are generally avoided if
the discriminant loadings (pooled within
group correlations) are calculated and
interpreted (Hair, Anderson, Tatham, &
Black, 1998). Discriminant loadings represent correlations between each predictor
and the discriminant function and are
most useful for interpretation of the
results. They reveal that, among the variables in the analysis, the three constructs
have the strongest predictive power. If students feel that team learning in fact helps
them perform better in the team and in the
classroom, then they will vote in the affirmative for the success of team learning.
Other interesting results are apparent
from Table 3. A negative sign on team
size indicates that students prefer a
smaller team. Along with the positive
sign on percentage of problems solved,
these results corroborate the findings in
TABLE 3. Results of Stepwise Discriminant Analysis on Preference for
Team Learning (n = 148)
Discriminant predictor
Cognition elaboration
Affective collaboration
Motivation
Team size
Percent of problems solved
Team-learning experience
Driving time to campus
Expected grade
% variance
Model χ2
Λ
F(2, 139)
53.97*
69.43*
13.17*
4.81*
12.26*
7.53*
12.27
9.83*
99.90
97.96*
.45
Standardized
canonical
coefficients
Discriminant
loading
.88
.78
.40
–.10
.21
.02
–.06
.25
.49
.55
.24
–.15
.23
.18
–.23
.21
Note. Insignificant discriminant predictors dropped from the analysis were sex, work experience,
age, instructor, hours enrolled, semester hours completed, grade point average, and marital status.
Hit ratio = 96.2% of observations where correctly classified.
*p ≤ .05.
26
Journal of Education for Business
Table 1 and indicate that larger team
size may render team problems unsolvable, rendering teamwork dysfunctional. Finally, the negative sign on driving
time to campus is as expected for an
urban commuter campus.
Conclusions and Implications
The literature on team learning gravitates unambiguously toward two conclusions: (a) It is an effective pedagogy and
(b) despite its proven benefits, team
learning remains underused in institutions of higher education. We suggest
that raising the likelihood of success is
antecedent to promoting the team-learning pedagogy. Given the proposition that
what students learn is influenced by how
and why they learn, we redefine success
in terms of student perceptions. Students
must experience higher learning in forms
other than the traditional, straight lecture
approach, in which success is measured
by examination scores. With the team
learning method of instruction, students
must perform well as team members in
addition to passing exams.
Our study confirms that team activities must be closely connected to promote an environment in which motivated students collaborate to learn. Based
on our findings, we emphasize the
importance of rigor in teamwork issues
and make specific recommendations for
implementing this strategy.
Student input, discussions, presentations, and the give-and-take of complex
issues may carry parallel weight in the
determination of a final grade. A positive perception is further reinforced
once students are convinced that they
will achieve a higher level of comprehension of course material by participating in team activities.
First, instructors should realize that
success comes in small increments
through the interaction of students within the team. Instructors should develop
as many techniques as possible for
increasing student involvement. However, it is imperative that students do not
feel they are engaging in “busy work.”
Rather, assignments should be viewed
as supportive of interdependence and
geared to recognition of the students’
collective input toward mastery of
course material. If students find the
Downloaded by [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 17:49 12 January 2016
methodology beneficial to their learning
needs, they will develop a better attitude
toward the discipline as a whole.
Second, instructors should monitor
and assess teams and provide them with
immediate feedback. The idea here,
however, is not to police team activities.
Perception of success is strengthened if
the feedback reinforces cognitive elaboration, such as becoming more proficient with basic concepts, problemsolving abilities, and communicating
economics concepts. Moreover, supplying feedback also presents an opportunity for instructors to stress the benefits
of listening and learning from one
another, resulting in accountability for
student efforts to achieve success.
Third, team size should be limited to
three or four students and carefully
monitored for potential problems. Here
again, aside from solving team personality or cultural conflicts, the instructor
must also facilitate team operations to
achieve cognitive and collaborative success. For example, students with prior
team-learning experience tend to reinforce positive views of team-learning
outcomes, as well as their view of mastering the material. For optimal results,
these students should be appointed initially as team leaders with responsibilities to team reporting tasks.
In addition, students with poor communication skills and a negative attitude
toward team learning will need assistance in improving deficiencies. A
secure team environment can foster a
favorable outcome by providing students with opportunities to practice
these skills with economics concepts in
a comfortable setting. The most compelling reason for wide-scale use of the
team-learning method is the success of
the model in promoting positive attitudes toward mastery of the economic
way of thinking.
NOTES
John P. Manzer passed away on August 8, 2005,
as the result of an automobile accident.
Professor Ali Rassuli dedicates this article in
memory of his friend and colleague, Professor
John P. Manzer, a professional and highly regarded teacher of teachers.
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September/October 2005
27
ISSN: 0883-2323 (Print) (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
"Teach Us to Learn": Multivariate Analysis of
Perception of Success in Team Learning
Ali Rassuli & John P. Manzer
To cite this article: Ali Rassuli & John P. Manzer (2005) "Teach Us to Learn": Multivariate
Analysis of Perception of Success in Team Learning, Journal of Education for Business, 81:1,
21-27, DOI: 10.3200/JOEB.81.1.21-28
To link to this article: http://dx.doi.org/10.3200/JOEB.81.1.21-28
Published online: 07 Aug 2010.
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“Teach Us to Learn”: Multivariate Analysis
of Perception of Success in Team Learning
ALI RASSULI
JOHN P. MANZER
INDIANA UNIVERSITY–PURDUE UNIVERSITY FORT WAYNE (IPFW)
FORT WAYNE, INDIANA
ABSTRACT. Considerable attention
has been given to the efficacy of teamlearning pedagogy, yet the methodology remains underused among educators
in institutions of higher education. We
suggest that the perception of success
is antecedent to greater acceptance and
use of this teaching style. Educators
and students alike must experience the
value creation potential of team learning before they will endorse it. In this
article, the authors investigated perceptions of success within the theoretical
realms of cognition elaboration, effective collaboration, and motivation perspectives. In addition to rank-ordering
the importance of these realms, the
authors make recommendations and
suggest policies to raise the likelihood
of success in team-learning practice.
T
he superiority of the cooperative
learning method over the traditional
lecture style of teaching is well established in the literature. The basic tenets
of cooperative learning are inter-group
positive interdependence and individual
accountability (Cottell & Millis, 1993;
Slavin, 1992). Most scholars support the
proposition that group-based instructional methods can be used to promote the
achievement of desirable learning outcomes in institutions of higher education.
To be specific, researchers advocated
team-learning pedagogy as the main
delivery scheme. Maier and Keenan
(1994) described team learning as “a
large number of structured, systematic
in-class techniques that engage students
in group work toward a common goal”
(p. 358).
Despite decades of research on team
learning and an overwhelming consensus
on team-learning efficacy, its use in colleges and universities is limited.
Research by Becker (1997) showed an
absence of team-learning techniques “in
all economics courses at research universities” (p. 1354). Hernandez (2002)
reported that students resisted participating in team-learning activities. Ravenscroft, Buckless, McCombs, and Zuckerman (1995) and Imel (1999) similarly
discussed teachers’ reluctance to employ
team-learning methods in their classes.
In search of a successful formula for
team learning, researchers have concen-
trated on a variety of structures and
techniques. For example, Karp and
Yoels (1987) concentrated on students’
group participation optimization, Johnson, Johnson, and Smith (1991) stressed
skill heterogeneity in the group, Fiechtner and Davis (1992) suggested a minimum allocation of grades to teamwork,
Li Wan Po (1994) emphasized inclusion
of an employer practicum in team
activities, and Bartlett (1995) discussed
free-rider problems. Also, Tanner and
Lindquist (1998) researched the relationship between attitude formation and
performance. Many authors have even
suggested detailed processes for administration of team learning. Examples
include Cottell and Millis (1993), Hernandez (2002), Michaelsen and Black
(1994), Michaelsen, Fink, and Knight
(1997), and Persons (1998).
We suggest raising the likelihood of
success is antecedent to promoting the
use of team-learning pedagogy in institutions of higher education. In this article, we redefine “success” in terms of
student perceptions. Perceptions were
measured using the academic achievement theoretical perspectives proposed
by Springer, Stanne, and Donovan
(1999): (a) motivational, (b) affective,
and (c) cognitive. These perspectives
are based on the proposition that what
students learn is influenced by how and
why they learn. Once they experience
its value creation potential, both stuSeptember/October 2005
21
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dents and faculty will be more amenable
to team learning.
Review of the Literature
Traditional Teaching Versus
Cooperative Learning
The shift from a teacher-focused
method to a learner-focused approach
came about as a result of a major paradigm shift from teaching to learning in
the past few decades (Saunders, 1997).
Now, most educators involved in higher
education agree that the traditional pedagogy of teaching does not lend itself to
the creativity and problem-solving ability that are expected of learners. Under
the traditional method of teaching, the
instructor is considered the source of
“ultimate truth,” whose skill in disseminating knowledge is derived from the
ability to perform well on the classroom
stage. Students are expected to learn
more only if the professor does a better
job of delivering materials through professing with “style” to a captive audience (Michaelsen & Black, 1998). In
the traditional setting, students are passive listeners; yet, they are expected to
possess extraordinarily long attention
spans, retention skills, powerful imaginations, and, most important, excellent
memories, to regurgitate that knowledge
and prove their success by passing an
examination. A number of scholars in
various business as well as nonbusiness
disciplines have abandoned the preoccupation of educators in favor of
improving their own performance, alone
in the classroom. The bias toward
improving information delivery methods rather than spending time developing students’ learning has been documented, for example, by Becker (1997),
Brown (1997), Chonko (1993), Guskin
(1994), and Johnson et al. (1991).
The main thrust of the new paradigm is
a shift of focus on student and learner
development. To effectively enhance
learning skills, Slavin (1980) argues that
students must be closely involved in the
learning process. Johnson et al. (1991)
emphasize the greater need for direct and
active student involvement in the classroom. The new concept of involving students in the learning process calls for a
major change in the traditional role of the
22
Journal of Education for Business
instructor. In the new paradigm, the
teacher becomes a facilitator for learning.
According to Bobbitt, Inks, Kemp, and
Mayo (2000), instructors “should be the
designers of a learning environment in
which students are active participants in
the learning process” (p. 15).
Active participation in learning is not
confined to taking notes or raising a
hand and responding to questions, and
neither is paper presentation. It is
accomplished through cooperative
learning with group activities. The
effective pedagogy in cooperative learning is teamwork. Becker (1997, p. 1360)
describes the team-learning process as
“think, pair, and share.” In this process,
students discuss, refine, and articulate
issues posed in class and provide a team
response in collaboration with each
other. The main idea is that within the
psychological safety of the team
(Edmondson, Bohmer, & Pisano, 2001)
of cooperative and responsible peers, a
deeper level of thinking takes place
(Knabb, 2000). In the process of sharing
and communicating their thoughts, students develop a kind of collective learning synergy that surpasses the sum of
their individual efforts (Mutch, 1998).
Team-Learning Pedagogy
The primary focus of team learning
is to fashion a learning environment
and process where students are actively involved in learning. There is a common understanding among scholars of
the required elements of team teaching. Cottell and Millis (1993) argue for
five features as requisites for a successful team-learning experience: (a)
student interdependence, (b) individual
accountability, (c) appropriate grouping, (d) social skills interaction, and
(e) group monitoring.
The debate is on how extensively to
apply these elements in the classroom.
The purpose is to foster a learning environment conducive to group interaction.
Stringency of team rules, and the extent
to which they are implemented, is the
core difference between cooperative and
collaborative styles of team learning.
The main tenet of collaborative learning
is achievement of higher levels of learning through the intellectual efforts of
students, or students and instructors
together (Smith & MacGregor, 1992).
This is accomplished primarily through
positive interdependence and individual
accountability (Slavin, 1989). Collaborative learning methods are unstructured, and students usually establish
rules. For example, students determine
group membership, rules of engagement, and procedures for contributions
and accountability.
If we envisage collaborative learning
as the initial position of a stringency
scale continuum, cooperative style
would appear on the opposing pole.
Cooperative style is defined as “a large
number of structured, systematic inclass techniques that engage students in
group work toward a common goal”
(Maier & Keenan, 1994, p. 358). In
such a setting, the instructor generally
controls the teams’ functions through a
set of predetermined policies and activities. As such, team goals are well
defined, the instructor selects team
members and assigns them to interrelated roles, length of debates and problemsolving activities is monitored, and each
team member is held accountable for his
or her contribution to team and individual learning.
As Springer et al. (1999) point out,
“the many forms of cooperative and collaborative small-group learning do not
follow from a single theoretical perspective” (p. 24). Divergent methods
and variable results from empirical
studies reflect this fact. Lancaster and
Strand (2001) summarize the results of
10 team-learning studies in the area of
accounting and report diametrically different outcomes. These mixed results
are symptomatic of the preponderance
of discipline-specific studies. In their
quest for a successful formula, scholars
experiment with a variety of strategies.
For example, Johnstone and Percival
(1976) suggest limiting classroom lectures to a maximum of 18 min in chemistry classes. Bobbitt et al. (2000) favor
combining lectures with real-world
events to improve learning in marketing
theory classes. Ravenscroft et al. (1995)
contend that, in addition to group
grades, individual test scores must be
assigned in accounting classes to further
motivate team efforts for a more positive outcome. Although proclaiming the
usefulness of team-learning pedagogy,
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Johnson, Johnson, and Stanne (2000)
correctly point out the impossibility of
devising a unique, effective method
across educational disciplines.
Research
According to Lancaster and Strand
(2001), learning models are not transferable across educational disciplines;
they asserted that “what works for one
teacher in a particular situation may not
work for another in a similar or different
situation” (p. 554). Team-learning activities can take a number of forms, limited only by the creativity of the instructor. In this study, we are searching for a
common ground for team-learning success, beyond the pedagogical differences. We posit that although there is no
guarantee of consistently desirable outcomes, a better understanding of the
determinants of team-learning effectiveness will improve the likelihood of
achieving preferred outcomes.
Springer et al. (1999) articulated
three interrelated theoretical perspectives to describe the “efficacy of smallgroup learning” (p. 24). The first is Cognitive Elaboration. They contended that
new information is best retained when
linked to information already present in
memory. By describing and elaborating
on classroom issues, team members
establish this necessary association.
The second perspective is Affective
Collaboration. Here, the objective is to
increase interaction among peers. This
can be accomplished not just by affording students an opportunity to communicate, but also by stimulating a desire
to participate and discuss and exchange
ideas. Conversing about issues simultaneously enhances learning for both the
listener and the communicator. This
facilitates the learning process, as long
as students remain focused and are less
restricted with rules of engagement.
Finally, the third perspective is Motivation. If students value the success of the
group, they will support each other individually and collectively to succeed. This
requires that students view the process as
cooperative instead of seeing it as competitive. The emphasis is on the necessity
of individual accountability for learning,
to motivate students to share ideas well
beyond merely sharing correct answers.
For students to effectively participate in team learning, they must feel
rewarded by success. They must
understand that success is a complex
process, with high test scores composing only a fraction of their expected
performance. Equally important to students should be that their peers do
well. This can be accomplished if each
student makes a connection with the
material prior to team activities, and
then effectively communicates and
helps peers to relate and comprehend
it. After all, everyone can share knowledge and perform better together.
Instrument Development and
Data Collection
The data for this study were collected
from economic principles classes in a
medium-sized, state-sponsored, regional university in the Midwest. The
Department of Economics is part of the
School of Business, which is accredited
by the Association to Advance Collegiate Schools of Business (AACSB).
The university promotes the individual
attention given to students because of its
small classes. Economics classes are
generally capped at 35 students and are
taught by experienced and academically
qualified faculty.
The questionnaire was developed in
three stages. First, students in a pilot
group were asked to evaluate a grouplearning experience. These results provided a preliminary basis for a pilot
instrument, which we field tested on
three groups of four students each.
Based on the field test results, we developed and administered another instrument to an economic principles class for
further refinements prior to using it with
the classes actually involved in the
study. We administered the finalized
survey questionnaire to six economic
principles classes within a three-semester period.
Two instructors were involved in this
study. Prior to the start of each semester,
instructors coordinated their coverage,
class activities, and procedures.
Although a team cooperative learning
approach was emphasized, the implementation process included collaborative elements. The instructors handled
the groups’ goals by defining assign-
ments, timing for lecture and team
activities, grading, monitoring group
activities, and assuring appropriate
grouping (Cottell & Millis, 1993). The
students determined group size, member roles, peer assessments, and modes
of interaction. Moreover, the instructors
acted as designers and observers by
responding to questions, mediating
problems, and providing immediate
feedback to the teams.
The survey instrument was composed
of three interrelated segments. The first
contained twelve 5-point Likert-scale
questions (from 5 = strongly agree to
1 = strongly disagree) asking about students’ perceptions of success in team
learning. The students’ responses constituted the latent roots for the three constructs of Cognitive Elaboration, Affective Collaboration, and Motivation, as
suggested by Springer et al. (1999).
The second segment contained questions regarding the optimal size of the
team. Also included was a question
intended to investigate the impact of
group conflict resolution on perception of
success. Finally, questions with regard to
demographics appeared in the third segment. In addition to demographics such
as age, grade point average (GPA), gender, work status, and school status, as
suggested by Hite, McIntyre, and Lynch
(2001), other variables related to perception of success: (a) prior exposure to
teamwork, (b) expected course grade,
and (c) opportunity costs of time commitment to team activities. For example,
it is reasonable to assume that students
exposed to team learning in prior courses
appreciate the relationship between team
activities and success. However, students
with family responsibilities or full-time
jobs may resent the time spent preparing
for teamwork. A complete list of these
variables appears in Table 1.
METHOD
The sample comprised 180 students
from six economic principles classes. We
asked students to rate, on a 5-point scale,
the degree to which they agreed or disagreed with the statement that teamlearning contributed highly to their mastery of the course material. Three
subgroups emerged: (a) Group 1 included students who either agreed or highly
September/October 2005
23
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TABLE 1. Selected Descriptive Statistics on Team Learning (TL)
Characteristic
Perception of success
Better attitude toward
course
Better attitude toward
instructor
Teamwork helped improve
problem solving
Pre- and posttest
reviews helped
Team presentations helped
Team tests improved
learning
Teammate achievement
important
Achievement of higher
test score
Communicate economic
concepts
Solve complex economic
problems
Understand economic
concepts
Preferred more lecture
Team
Size*
Size change preferred
Prevalent problems
% free rider
% lack of interest
% nonparticipation
% team problems solved*
Demographics
Sex (% male)
Marital status (% married)
Age
Semester hours completed
Years worked full time
GPA
Hours enrolled
Driving time to campus
(min)*
TL experience (classes)*
Expected grade*
Group 1: Cases for TL (n = 116)
Agree
Disagree
or highly
or highly
SD
%
agree (%) disagree (%)
M
3.9
0.2
0.8
0.7
M
Group 2: Cases against TL (n = 32)
Agree
Disagree
or highly
or highly
SD
%
agree (%) disagree (%)
87.2
0.0
0.0
78.2
69.2
10.2
6.3
87.5
91.1
0.0
3.1
81.2
75.6
62.3
1.4
8.6
3.1
3.2
75.0
45.1
30.9
3.0
6.4
42.0
78.9
3.9
0.0
93.8
64.1
9.0
0.0
96.9
79.5
1.3
3.1
56.3
60.3
7.7
6.3
71.9
87.2
20.5
2.6
61.5
3.1
87.5
78.2
6.2
4.8
–0.3
0.7
1.1
84.6
92.3
87.2
87.8
61.5
67.3
82.6
67.8
0.4
40.3
0.5
43.8
25.9
66.8
5.1
3.1
9.8
5.6
47.7
3.3
0.5
4.4
26.7
77.4
5.5
2.9
10.2
6.3
30.7
4.6
0.6
3.6
23.1
3.8
3.2
15.9
4.9
0.6
35.9
1.4
2.8
18.7
2.8
0.8
*p ≤ .05 significant differences between group means.
agreed with that statement, (b) Group 2
was composed of students who either disagreed or highly disagreed, and (c)
Group 3 encompassed students who gave
neutral responses. Table 1 shows descriptive statistics for Groups 1 and 2.
Because our objective was to assess the
success of team learning, we accentuated
the variance between groups by omitting
the third group from Table 1.
24
Journal of Education for Business
Further, to capture the team-learning
perspectives proposed by Springer et al.
(1999), we employed factor analysis.
The multi-item constructs that satisfied
two conditions—having eigenvalues of
one or greater and explaining at least
5% of total variance—are included in
Table 2. In addition, we computed
Cronbach’s alpha reliability coefficients
for multi-item constructs used in this
study. They ranged from .79 to .92 and
were found to be acceptable. Items that
produced factor loadings of 50% or
more constituted latent roots and were
used to interpret each construct.
Finally, we used stepwise discriminant analysis on team learning. Discriminant analysis is a statistical technique that predicts group membership.
We employed this technique for two
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reasons: first, to ascertain the predictive
power of the constructs and variables
used in this study; and second, to rank
order their contribution to perceptions
of team-learning success. The criterion
variable was based on the student’s
response to whether or not team learning activities were extremely beneficial
for mastery of the course. If they agreed
or strongly agreed (Group 1), the criterion variable was assigned a value of
one. We assigned values of zero to
respondents who either disagreed or
strongly disagreed with the statement
(Group 2). We kept only significant discriminant predictors in the model by the
stepwise procedure. We dropped
insignificant predictors from the analysis, as they did not contribute to group
membership predictability.
RESULTS AND DISCUSSION
Selected results of descriptive statistics appear in Table 1. An overwhelming
majority of students in Group 1 (87.2%)
indicated they had a better attitude
toward the course as a result of teamlearning activities. In fact, none of them
reported a worse attitude. A large majority of Group 1 also agreed that teamlearning activities improved their performance. To be specific, they reported
that teamwork had improved their problem-solving abilities, as well as their
ability to understand and communicate
complex economic concepts. Most of
them reported developing a positive attitude toward the instructor, and only
20.5% preferred more lecture.
By contrast, an overwhelming majority of Group 2 (78.2%) revealed a negative attitude, with none reporting any
attitude improvement toward the course
as a result of team-learning activities.
An insignificant percentage of cases in
this group reported improvement in
learning, problem solving, understanding, or communicating economic concepts as a result of team learning. Finally, 87.5% of students from this group
preferred more lecture as opposed to the
team-learning method of instruction.
Analysis of team size and problems
associated with working in a team were
also revealing. Group 1, the group that
favored team-learning, reported a team
size of 4 (average = 3.9). They also
noted the presence of major problems
among team members, but they suggested virtually no change in the size of the
team. One may infer that the team functioned well, given the fact that the members were successful in solving 87.8%
of team problems.
By contrast, Group 2 had a significantly
larger team size of almost 5 (average = 4.8). They preferred to reduce the
group size, as appears in Table 1. The
percentage of group problems reported
by Group 2 was, in general, smaller than
that reported by Group 1. However, the
TABLE 2. Factor Matrix for Team-Learning Perspectives
Construct
Cognition elaboration
Better understand economic concepts
Solve complex economic problems
Better communicate economic concepts
Affective collaboration
Better attitude toward instructor
Better attitude toward course
Prefer more lecture than team work
Achievement of higher test score
Motivation
Team test taking improves learning
Teamwork helps improve problem solving
Pre- and posttest review improves learning
Teammate achievement is important
Team presentation improves learning
Factor
loading
Eigenvalue
% variance
explained
6.10
60.6
2.46
10.3
1.04
6.0
.76
.75
.73
.75
.68
–.55
.53
.73
.62
.56
.53
.51
Note. N = 180. Items with factor loadings ≥ .50 appear here.
members of Group 2 solved a significantly smaller percentage (67.8%) of team
problems as compared with Group 1.
Moreover, the percentage of nonparticipant (i.e., team problems) in Group 1 as
compared with Group 2 was significantly
higher. To determine if this problem was
a result of a larger team size, we calculated the correlation between the presence
of nonparticipation problems with teams
having more than four members. The biserial correlation coefficient produced a
statistically significant value of .92.
Analysis of the demographics in Table
1 indicated that prior team-learning
experience, driving time to campus, and
expected grade were the only variables
that differed significantly between
groups. The group that found team learning beneficial reported having experienced the team-learning method in more
classes and expected to receive a higher
grade in the course. It appears that the
longer and greater involvement with
team activities, the higher the chances for
the realization of its positive contribution
to students’ learning.
Results of factor analysis appear in
Table 2. Cognition Elaboration is the
first construct, with three items that
relate to student perceptions concerning their mastery of course content and
tools. Their understanding of basic
economics concepts is an important
aspect. If students believe they are
mastering the underlying economic
principles, they tend to feel more positive toward the team learning method.
Using this understanding of basic economics concepts to solve complex economics problems reinforces a positive
view of team learning. A related issue,
and the third cognitive item, is the ability to communicate economics concepts and issues. This reinforces perceptions of economics understanding
and problem-solving skills. In a group
learning setting, students must be able
to communicate with each other to
benefit from each other’s contributions. Students with poor communication skills, or those simply unwilling to
communicate with fellow team members, frequently dislike the team-learning method.
The second construct captures the
Affective Collaboration perspective
toward the team-learning method. Items
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that loaded on this construct involve student views of the teacher, course,
instructional methodology, and their
own test performance as assisting them
to reach course objectives. Overall,
these perceptions reveal student views
of how effective team collaboration was
in their advancement in the course. A
positive view of the instructor might
also enhance their outlook on team
learning because they see instructor
input as supportive. Insofar as students
are concerned, attitudes in the classroom are an important consideration in
shaping perceptions of the effectiveness
of the team-learning method.
Motivation is the third construct. This
construct grasps the essence of learning
interdependence, interaction, and
accountability among the team members as suggested by Cottell and Millis
(1993). In a group setting, students not
only learn from each other, they also
reinforce each other’s learning processes. Enhanced achievements through
team test taking, problem solving, and
presentation create strong motivation
for camaraderie and responsibility for
each other’s learning.
The results of stepwise discriminant
analysis on team learning appear in
Table 3. The discriminant function was
statistically significant, χ2 (92, N = 148)
= 97.96, and discriminating power (hit
ratio) = 96.2%.
Table 3 also contains the standardized
canonical coefficients (discriminant
weights) of the stepwise discriminant
analysis on team learning. Generally, the
size of these coefficients is indicative of
the relative importance of the predictive
variables. However, ranking of their relative importance is closely dependent on
the intercorrelation between predictor
variables. This problem (similar to the
multicollinearity problem in regression)
may cause interdependence among variables, thus producing a blurred and unreliable ranking of their relative importance.
Such problems are generally avoided if
the discriminant loadings (pooled within
group correlations) are calculated and
interpreted (Hair, Anderson, Tatham, &
Black, 1998). Discriminant loadings represent correlations between each predictor
and the discriminant function and are
most useful for interpretation of the
results. They reveal that, among the variables in the analysis, the three constructs
have the strongest predictive power. If students feel that team learning in fact helps
them perform better in the team and in the
classroom, then they will vote in the affirmative for the success of team learning.
Other interesting results are apparent
from Table 3. A negative sign on team
size indicates that students prefer a
smaller team. Along with the positive
sign on percentage of problems solved,
these results corroborate the findings in
TABLE 3. Results of Stepwise Discriminant Analysis on Preference for
Team Learning (n = 148)
Discriminant predictor
Cognition elaboration
Affective collaboration
Motivation
Team size
Percent of problems solved
Team-learning experience
Driving time to campus
Expected grade
% variance
Model χ2
Λ
F(2, 139)
53.97*
69.43*
13.17*
4.81*
12.26*
7.53*
12.27
9.83*
99.90
97.96*
.45
Standardized
canonical
coefficients
Discriminant
loading
.88
.78
.40
–.10
.21
.02
–.06
.25
.49
.55
.24
–.15
.23
.18
–.23
.21
Note. Insignificant discriminant predictors dropped from the analysis were sex, work experience,
age, instructor, hours enrolled, semester hours completed, grade point average, and marital status.
Hit ratio = 96.2% of observations where correctly classified.
*p ≤ .05.
26
Journal of Education for Business
Table 1 and indicate that larger team
size may render team problems unsolvable, rendering teamwork dysfunctional. Finally, the negative sign on driving
time to campus is as expected for an
urban commuter campus.
Conclusions and Implications
The literature on team learning gravitates unambiguously toward two conclusions: (a) It is an effective pedagogy and
(b) despite its proven benefits, team
learning remains underused in institutions of higher education. We suggest
that raising the likelihood of success is
antecedent to promoting the team-learning pedagogy. Given the proposition that
what students learn is influenced by how
and why they learn, we redefine success
in terms of student perceptions. Students
must experience higher learning in forms
other than the traditional, straight lecture
approach, in which success is measured
by examination scores. With the team
learning method of instruction, students
must perform well as team members in
addition to passing exams.
Our study confirms that team activities must be closely connected to promote an environment in which motivated students collaborate to learn. Based
on our findings, we emphasize the
importance of rigor in teamwork issues
and make specific recommendations for
implementing this strategy.
Student input, discussions, presentations, and the give-and-take of complex
issues may carry parallel weight in the
determination of a final grade. A positive perception is further reinforced
once students are convinced that they
will achieve a higher level of comprehension of course material by participating in team activities.
First, instructors should realize that
success comes in small increments
through the interaction of students within the team. Instructors should develop
as many techniques as possible for
increasing student involvement. However, it is imperative that students do not
feel they are engaging in “busy work.”
Rather, assignments should be viewed
as supportive of interdependence and
geared to recognition of the students’
collective input toward mastery of
course material. If students find the
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methodology beneficial to their learning
needs, they will develop a better attitude
toward the discipline as a whole.
Second, instructors should monitor
and assess teams and provide them with
immediate feedback. The idea here,
however, is not to police team activities.
Perception of success is strengthened if
the feedback reinforces cognitive elaboration, such as becoming more proficient with basic concepts, problemsolving abilities, and communicating
economics concepts. Moreover, supplying feedback also presents an opportunity for instructors to stress the benefits
of listening and learning from one
another, resulting in accountability for
student efforts to achieve success.
Third, team size should be limited to
three or four students and carefully
monitored for potential problems. Here
again, aside from solving team personality or cultural conflicts, the instructor
must also facilitate team operations to
achieve cognitive and collaborative success. For example, students with prior
team-learning experience tend to reinforce positive views of team-learning
outcomes, as well as their view of mastering the material. For optimal results,
these students should be appointed initially as team leaders with responsibilities to team reporting tasks.
In addition, students with poor communication skills and a negative attitude
toward team learning will need assistance in improving deficiencies. A
secure team environment can foster a
favorable outcome by providing students with opportunities to practice
these skills with economics concepts in
a comfortable setting. The most compelling reason for wide-scale use of the
team-learning method is the success of
the model in promoting positive attitudes toward mastery of the economic
way of thinking.
NOTES
John P. Manzer passed away on August 8, 2005,
as the result of an automobile accident.
Professor Ali Rassuli dedicates this article in
memory of his friend and colleague, Professor
John P. Manzer, a professional and highly regarded teacher of teachers.
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