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1. 개인일정

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2. HP-UX 시스템용 gcc 설치하기

/usr/sbin/swinstall -s /src/zeniusd/gnutools/gcc-3.2-11.00_64.depot gcc

3. 버그트래킹시스템

[http]mantis(http://www.mantisbt.org)apache, mysql, php를 사용한 버그트래킹 시스템 한글화 되어 있음

4. emacs 설정파일(~/.emacs.el)

(show-paren-mode t)
(global-font-lock-mode t)
(auto-compression-mode 1)
(keyboard-translate ?\C-h ?\C-?)
(global-set-key [?\C-x?\C-j] 'goto-line)

;; my c mode
(setq-default inhibit-default-init t
              query-replace-highlight t
              transient-mark-mode 't
              font-lock-mode-maximum-decoration t
              font-lock-support-mode 'lazy-lock-mode
              c-basic-offset 4
              tab-width 4
              indent-tabs-mode t)
(c-add-style "my-c-style" '((c-continued-statement-offset 4)))
(defun my-c-mode-hook ()
  (c-set-style "my-c-style")
  (c-set-offset 'substatement-open '0)
  (c-set-offset 'inline-open '+)
  (c-set-offset 'block-open '+)
  (c-set-offset 'brace-list-open '+)
  (c-set-offset 'case-label '+)
  (define-key c-mode-base-map (kbd "RET") 'newline-and-indent))
(add-hook 'c-mode-hook 'my-c-mode-hook)
(add-hook 'c++-mode-hook 'my-c-mode-hook)

;; wheel mouse scroll
;; (setq-default scroll-step 1)
(defun up-slightly () (interactive) (scroll-up 5))
(defun down-slightly () (interactive) (scroll-down 5))
(defun up-one () (interactive) (scroll-up 1))
(defun down-one () (interactive) (scroll-down 1))
(defun up-a-lot () (interactive) (scroll-up))
(defun down-a-lot () (interactive) (scroll-down))
(global-set-key [mouse-4] 'down-slightly)
(global-set-key [mouse-5] 'up-slightly)
(global-set-key [S-mouse-4] 'down-one)
(global-set-key [S-mouse-5] 'up-one)
(global-set-key [C-mouse-4] 'down-a-lot)
(global-set-key [C-mouse-5] 'up-a-lot)

;; leim, locale, fontset
(require 'cl)
(when enable-multibyte-characters
  (set-language-environment "Korean")
  (setq-default file-name-coding-system 'euc-kr)
  (when (string-match "^3" (or (getenv "HANGUL_KEYBOARD_TYPE") ""))
    (setq default-korean-keyboard "3"))
  (setq input-method-verbose-flag nil
        input-method-highlight-flag nil)
  (prefer-coding-system 'euc-kr)
  (set-default-coding-systems 'euc-kr)
   (cond ((eq system-type 'windows-nt) 'euc-kr-dos)
         (t 'euc-kr)))
  (set-keyboard-coding-system 'euc-kr)
  (when (assq 'encoded-kbd-mode minor-mode-alist)
    (setf (second (assq 'encoded-kbd-mode minor-mode-alist)) ""))
  (if (null window-system)
        (set-terminal-coding-system 'euc-kr)
        (define-key encoded-kbd-mode-map [27] nil))))
(progn (create-fontset-from-fontset-spec
        "-*-fixed-medium-r-*-*-14-*-*-*-*-*-fontset-gulimche,korean-ksc5601:-hanyang-gulimche-medium-r-normal-*-12-*-*-*-c-*-ksc5601.1987-0" '(medium))
       (setq default-frame-alist (append '((font . "fontset-gulimche")))))

 ;; custom-set-variables was added by Custom.
 ;; If you edit it by hand, you could mess it up, so be careful.
 ;; Your init file should contain only one such instance.
 ;; If there is more than one, they won't work right.
 '(column-number-mode t)
 '(display-time-mode t nil (time))
 '(fringe-mode (quote (nil . 0)) nil (fringe))
 '(scroll-bar-mode (quote right)))

Team Formation Methods for Increasing Interaction During In-Class Group Work
Katherine Deibel
Computer Science and Engineering
University of Washington
Seattle, WA 98195
In contrast to the student teams used for larger and longer
group projects, in-class groups are often ephemeral, lasting
for only a few minutes or until the end of the period. Because
of this, little effort is put into forming these groups, usually
letting the students self-select their teams. This paper argues
that greater student interaction and learning can take
place by using instructor-selected teams. Two group formation
techniques for in-class group work, the latent jigsaw
method and grouping students by Felder-Silverman learning
styles, are presented. Observations from a classroom deployment
of these techniques are also described.
Categories and Subject Descriptors
K.3.1 [Computers and Education]: Computer Uses in
Education%G—%@Collaborative learning
General Terms
Human Factors, Performance
collaborative learning, active learning, learning styles
In computer science education, two forms of group learning
are practiced rather universally: large group projects
and small, in-class group activities. Modeled from industry,
group projects have teams of students working on a large
project over several days or the length of the entire term.
In-class group work, however, takes place in at most a single
class period and often consists of student-to-student discussion.
These two methods, as well as other variations on
group work, all depend strongly on proper team functioning
for success. Thus, it should come at no surprise that educational
researchers have developed multiple guidelines for
assigning people to groups [8, 10].
Permission to make digital or hard copies of all or part of this work for
personal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. To copy otherwise, to
republish, to post on servers or to redistribute to lists, requires prior specific
permission and/or a fee.
ITiCSE$(C!/(B05, June 27%G–%@29, 2005, Monte de Caparica, Portugal.
Copyright 2005 ACM 1-59593-024-8/05/0006 ...$5.00.
Surprisingly, these team formation methods are often dismissed
and unused for in-class group activities under an argument
of diminishing returns. The educational gains, if any,
of using these methods are perceived to not warrant the time
and expense of forming and assigning teams [11]. However,
successful group work relies on strong, uniform interaction
among the students. Student-selected teams offer no guarantees
of participation [11]. Assigning teams, though, provides
instructors with a direct means of promoting studentto-
student interaction.
This paper aims for computer science instructors to reconsider
their use of in-class group work. Arguments are made
that assigning groups can improve how group members interact.
Two team formation methods for promoting more
interaction for in-class group work are also presented. The
first is the latent jigsaw method, a new method for assigning
groups based on prior student knowledge for the purpose
of peer-teaching. The second method shows how forming
groups by learning styles can promote participation by creating
a comfortable social atmosphere for the members.
This section details the argument for assigning students
to groups during in-class group activities. In order to understand
how team formation methods can improve group
work performance, it is necessary to understand what exactly
makes collaboration successful.
2.1 Successful Group Work
To begin, consider the many educational benefits of collaborative
learning. First, directly engaging the learner with
the subject matter allows for better absorption of the material
[12]. The increased socialization and exposure to different
student ideas can also improve student retention in the
major [5]. Finally, Springer et al. have shown that collaboration
leads to an intense level of information processing
that encourages cognitive growth [12].
All of these benefits point at a single key concept: student
interaction. By analyzing dialogues between students
and tutors, Core et al. [3] found that an individual student$(C!/(Bs
learning gains correlated strongly with the number of words
and utterances made by that student. Students who passively
listened showed significantly weaker learning gains.
These results suggest that encouraging student-to-student
interaction is key to successful group work. In the time allotted
for the group learning experience, each student should
feel both comfortable and motivated enough to engage in
multiple conversational exchanges within their group. These
exchanges can be nearly anything: questions, comments, etc.
Thus, the challenge for us, the instructors, is to find ways of
promoting this vital interaction among our students.
2.2 Reasons to Avoid Student-Selected Teams
One aspect of group work controlled by the instructor is
how the groups are formed. Group membership clearly affects
interaction among the students, thus giving the instructor
a direct means of influencing interaction. Typically, the
instructor chooses between assigning the groups and letting
the students select their own teams.
Focusing just on group projects, Oakley, et al. [11] list
several pitfalls of letting students select their own groups.
First, students of similar abilities tend to congregate together:
strong with strong, weak with weak. This limits
interaction by preventing weaker students from learning
how stronger students approach problems and robbing the
stronger students of the educational values of peer teaching.
A second pitfall is that groups will likely form around
pre-existing friendships. This decreases the exposure to different
ideas, and such groups are more likely to encourage
and cover for inappropriate behaviors like non-participation
and cheating [11].
Self-selection can also pose a problem for under-represented
minorities. When an at-risk student (e.g., a woman in computer
science) is isolated in a group, this isolation can contribute
to a larger sense of feeling alone. This can then lead
to non-participation or purely passive roles such as being the
team$(C!/(Bs secretary [9, 11].
It is a simple observation to see that these arguments
against self-selected groups apply just as much to in-class
group activities. Students are likely to form groups based
on neighbors, which are often friends. At-risk minorities will
still stand the risk of isolation. Assigning groups provides
us, the instructors, with a means to combat these pitfalls
and thereby improve the quality of our in-class collaborative
2.3 Adjusting for In-Class Group Work
The question now arises as to how we go about assigning
teams in order to provide interaction among the students.
The methods suggested for group projects provide a starting
point, but the shorter duration of in-class activities raises
some challenges.
First, consider the educational goals we hope to achieve
by using collaboration in the classroom. Generally, a focus
is put on students learning and mastering a topic. Projects
groups additionally aim to teach students how to collaborate
as a preparation for working in industry [13]. If groups for
in-class activities are formed with the goal of reducing the
time needed for working together, more focus can be put
on the learning goals. Thus, teams that promote immediate
productivity are desirable for in-class group work.
A second effect of the time constraint involves participation
within a group. In project groups, the involvement of
members can vary greatly over the course of the project.
Some team formation methods design groups so that some
members are active at the start while others are more active
towards the end [10]. The shorter in-class activities simply
do not have this luxury. Teams need to create a group atmosphere
that supports and encourages uniform participation
by each and every member.
Thus, any team formation method used for group projects
might require adjustments in order to benefit interaction for
in-class activities. The remainder of this paper describes two
methods for team formation that meet these requirements of
immediate productivity and uniform participation. Positive
experiences and observations from a pilot classroom deployment
of these methods are also presented.
Before delving into the methods, though, this section briefly
describes the classroom context that both motivated and
prototyped the group formation methods.
3.1 Course Description
The work in this paper took place during my two terms as
the graduate teaching assistant (TA) for a Data Structures
(for majors) course at a large, public university. Taken by
every CSma jor, this course introduces students to a variety
of advanced data structures and their computational efficiencies.
A normal offering consists of 35%G–%@50 students attending
three 50-minute lectures and a required 50-minute recitation
section per week (students are assigned to one of two section
times). Support staff usually consists of a graduate and an
undergraduate TA.
To balance out the theory-heavy lectures, I chose to spend
sections focusing on applications of data structures. To give
the students experience in using data structures, I gave the
students open-ended questions involving choosing an appropriate
data structure for a given scenario. Typically, students
would spend 5 to 10 minutes discussing the scenario
in groups. Afterwards, the class would come together and
discuss the various solutions proposed by each group.
3.2 Classroom Logistics
Overall, implementing the group work exercises was fairly
straightforward. The sections that term were fairly small: 22
students in one, 15 in the other. Converting the classroom$(C!/(Bs
layout for group work instead of a more traditional lecture
also did not pose any significant problems. For example,
there were only ten minutes to prepare the room for the
afternoon section, but this was more than sufficient. Using
a map to direct students to sit in specific locations with
their groups at the beginning of class prevented confusion
and saved time.
Additionally, a fellow graduate student was brought in to
act as an independent observer. As I was piloting two new
group formation methods for in-class group work, I wanted
an unbiased record of how the students interacted in their
This section describes a new method designed for forming
teams: the latent jigsaw method. This method creates a
peer-teaching environment that promotes productivity and
requires uniform participation by all group members.
4.1 The Original Jigsaw Method
The latent jigsaw method is a modification of the original
jigsaw method [2]. The original jigsaw method creates a
peer-learning situation in which a topic has been split up
and each part mastered by a student in a group. Thus, a
student is responsible for teaching his or her share to the
group and is also dependent on the rest of the group to do
the same. The following explains the general procedure:
1. Split the class into X expert groups.
2. Each expert group learns and masters a separate topic.
3. Reshuffle the expert groups to form learning groups of
size X such that each group has at least one representative
from each of the expert groups.
4. Each student teaches their expertise to their new group.
Note that this method is not suited for group projects; it is
purely a collaborative learning exercise.
4.2 Adjustments
As an in-class group activity, the jigsaw method already
possesses the properties of immediate productivity and uniform
participation. During the learning groups stage (steps 3
and 4), each group is given the agenda of having each member
educate the others about the topic they$(C!/(Bve mastered.
However, this mastery is critical. The expert group stage requires
enough time and effort to make the students capable
of successfully educating their peers.
The latent jigsaw method skips the expert stage by utilizing
the students$(C!/(B prior knowledge and opinions. Students
are presented with a question that has multiple correct solutions
and are asked to choose from a restricted set of answers.
Figure 1 shows an example of this using a data structure scenario.
Once the answers are collected, the learning groups
are formed by grouping together students who chose different
answers. Then, like in the original method$(C!/(Bs learning
groups stage, each student explains to the rest of the group
why they chose to answer as they did. Formally, the latent
jigsaw procedure is as follows:
1. Students read an open-ended question and select one
answer among X correct solutions.
2. Students are then placed into groups of size X such
that each member chose a different solution.
3. Each student then explains to their group why they
chose their particular answer.
Note that the latent jigsaw method$(C!/(Bs educational goals
differ from those of the original method. Instead of having
students learn a new topic, this method asks students to engage
in critical thinking. The students exercise their current
knowledge and the insights of their peers in order to evaluate
alternative solutions.
Additionally, the latent jigsaw method possesses several
properties for potentially enhancing the interaction among
students. For example, during the learning group stage, each
student is motivated by the notion that their answer is the
most right, thus incurring a personal stake in the education
of their peers. Another benefit is that the expert groups
differ with every question. The exposure of students to a
wider set of different viewpoints and learning approaches
can enhance the socialization benefits of group learning.
4.3 Example
To better illustrate how this method works, consider the
following example taken from one of my sections. Students
were required for homework to complete an online survey of
scenarios like the one in Figure 1. The figure also contains
the responses for that scenario.
Because some time had occurred between filling out the
survey and section, students met briefly in $(C!0(Bexpert groups$(C!1(B
comprised of people who had chosen the same answer. Since
10 students answered Insertion Sort in Figure 1, they were
split into two groups of 5 each under the recommendation
The system you are designing requires a sort routine.
Memory usage is at such a high cost on this machine (say
it is a small, embedded device) that you cannot afford to
have much (if any) overhead in your sorting algorithm.
Which sorting routine would you choose?
a) Quick Sort ( 27% )
b) Insertion Sort ( 46% )
c) Merge Sort ( 0% )
d) Heap Sort ( 27% )
Figure 1: A restricted scenario used for the latent
jigsaw method. Responses are also shown (n = 22).
that smaller groups are more effective [11]. Heap Sort and
Quick Sort experts were placed in one group each with each
group containing 6 people. The five minutes spent in these
expert groups not only helped jog the students$(C!/(B memories
but also potentially introduced them to reasons they had
not considered when answering the scenario.
Five learning groups were formed by shuffling the expert
groups together so that each group had at least one representative
from each expert group. Care was taken to avoid
isolating any women or minority students [11]. Each learning
group had a representative from each of the Insertion
Sort expert groups. Since each expert group had a different
review experience, the insights of both experts is valuable to
the peer-learning experience. One group had two Quick Sort
experts and another had two Heap Sort experts.
After each member of the learning groups had taught the
rest of the group about their reasons for their answer, the
class came together to discuss the question as a whole.
4.4 Observations
This peer-teaching was successful as well in encouraging
interaction. Many expressed excitement at the thought of
being a teacher and channeled this excitement into their interactions
with their groups. This contagious enthusiasm
helped motivate all students to be active participants.
Another interesting effect occurred after the learning groups
had completed their tasks. I asked students to explain to the
class the merits of each answer. Since I knew who had answered
what in the survey, I purposely asked a student to
explain an answer different from their own. For example, I
would ask a student who answered Insertion Sort for Figure
1 to explain the merits of choosing Quick Sort. The students
responded with what they had learned. Interestingly
enough, many gave meta-answers in which they also mentioned
the positives and negatives associated with all the
choices. A few even admitted that their opinion on which
answer was best had changed. This shows that students paid
attention to the discussions within their learning groups and
engaged in further critical thinking.
A common strategy used in business management for forming
teams is to use personality types [1]. This section describes
how types can be used to form groups that promote
participation and productivity by creating a socially
comfortable atmosphere. Note that unlike the latent jigsaw
method, the teams formed in this section can, if desiredm
be reused for other activities.
5.1 Personality Types and Teams
Personality types, or learning styles, are tools designed by
psychologists to help classify and describe human behavior.
These styles often cover a wide range of attributes: how a
person prefers to interact with other people, acquire information,
form ideas, and act on ideas [7]. Unsurprisingly,
styles have been widely used in improving education [7].
For group projects, Jensen, et al [10] investigated the use
of the 6-Hats team formation strategy (6HTFS) for forming
teams. The 6HTFSc lassifies people according to the roles
they often take in groups (e.g., brainstormers, devil$(C!/(Bs advocates,
etc.). Students were placed into groups so that each
group had at least one member who preferred one of the
hats/roles. The idea is that each hat makes a key contribution
at some point during the solution process. In practice,
this proved to be true and resulted in both higher group
satisfaction and higher grades.
5.2 Adjustments
In order to use learning styles to form teams for in-class
group work, two major alterations are made. Firstly, Felder-
Silverman learning styles (FSLS) [4] are used. Because they
were developed to specifically describe the learning behaviors
of engineering students, these styles work on a finer granularity
than more general purpose inventories like 6HTFSan d
the Myers-Briggs Type Inventory [7].
Since a complete description of FSLS$(C!/(Bs five axes is beyond
the scope of this paper, only the two axes most relevant to
group work will be described. First, the Reflective / Active
(R/A) axis describes how an individual approaches a
problem. Reflective learners prefer to think silently before
offering a solution or starting an experiment. Active learners
instead prefer to learn by physically trying out new ideas, as
well as brainstorming out loud with a group of people. The
second axis, the Sequential / Global (S/G) axis, describes
how a person acquires information. Sequential learners typically
acquire information in small, ordered chunks to form
the big picture. Global learners often first grasp the big
picture and then the details.
The second alteration is to make the groups homogenous
in terms of the members$(C!/(B styles instead of mixing them like
in Jensen et al.$(C!/(Bs approach. Consider the effects of mixing reflective
and active learners. The reflective learners will prefer
to think in silence at first, while the active learners will likely
want to brainstorm out loud. Similarly, sequential learners
will most likely focus on the details while the global learners
prefer to look at the big picture. By making the groups consistent,
though, the members are likely to all start with the
same approach as well as focus on the same level of details.
This sameness produces both immediate productivity and
uniform participation as the members discuss the different
knowledge and ideas that each brings to the table.
In summary, groups were formed using learning styles by
the following criteria:
%G•%@ Group members should have similar R/A scores.
%G•%@ Group members should have similar S/G scores.
Additionally, a criterion was added to not isolate any at-risk
women or minority students [11].
It is important to realize that these are only guidelines for
forming teams. In some cases, it might not be possible to
achieve all the criteria. Other times, the instructor$(C!/(Bs personal
experiences with a student might be more important
when fitting students into groups. Remember, the goal is to
assign teams such that all students within a group generally
approach problems with the same style but not necessarily
the same ideas.
5.3 Example
At the beginning of the term, students were asked for
homework to complete the Index of Learning Styles Questionnaire
[6] in order to ascertain their Felder-Silverman learning
styles. This online assessment identifies the student$(C!/(Bs
dominant style on each style axis and returns a score from
1%G–%@11 (odd values only) to indicate the relative strength of
this learning style. A score of 3 or less indicates that the
subject is well-balanced on the axis and only slightly prefers
one style over the other. These results were then used to
form groups. Table 1 shows the four groups formed for a
section of 15 students, four of whom were women.
In general, the criteria from earlier were followed. Greater
emphasis was placed on the Reflective / Active axis as these
scores directly address how interaction begins within a group.
Unsurprisingly, some exceptions were made when teams were
assigned. For example, it proved difficult to form groups
with similar scores on the S/G axis.
In a few instances, special cases were made for individual
students. For example, even though student D4 has a score
of 5-A on the R/A axis, he was placed in a group of reflective
students. This was largely due to outside interactions
between him and me. D4 is naturally quiet and reserved
and tends to think before saying anything. While this is
characteristic of a reflective learner, he demonstrated to me
in office hours a strong preference for learning by doing examples.
This explains his score of being moderately active.
However, because of his tendency to think before speaking,
he was teamed with moderately reflective individuals.
Another break with the criteria was the isolation of female
students A1 and B3. Again, personal experiences with these
students allowed me to break with the criteria. Aside from
being the only active female, student A1 was quite vocal and
assertive in both lecture and section. B3 had demonstrated
in office hours a natural impulse to help explain concepts to
her peers. I had no concern that isolating them would reduce
their participation. As it turned out, both women took on
leadership roles that emphasized participation from the rest
of the members.
Table 1: Discussion groups from a section (n = 15).
Sex Reflective/Active Sequential/Global
A1 F 3%G–%@A 3%G–%@G
A2 M ? ?
A3 M 7%G–%@A 1%G–%@G
A4 M 1%G–%@R 1%G–%@G
B1 M 1%G–%@R 7%G–%@S
B2 M 9%G–%@R 3%G–%@S
B3 F 11%G–%@R 5%G–%@G
B4 M 11%G–%@R 3%G–%@S
C1 M 9%G–%@R 3%G–%@S
C2 M 7%G–%@R 1%G–%@G
C3 M 5%G–%@R 1%G–%@G
D1 M 1%G–%@R 1%G–%@G
D2 F ? ?
D3 F 9%G–%@R 7%G–%@S
D4 M 5%G–%@A 3%G–%@G
5.4 Observations
In a bit of serendipity, technical problems delayed me from
forming groups, so on the first day that group work took
place, the students were allowed to choose their own groups.
Many of the undesirable behaviors from Section 2.2 took
place. In particular, many students worked alone or not at
all. However, when assigned groups were used the next time,
the amount of participation was dramatically different. According
to my and the observer$(C!/(Bs observations, all students
were engaged and active in their group$(C!/(Bs conversations.
Of particular interest were the dramatic differences between
the active and reflective groups. Upon receiving the
problem scenario, the active groups, (e.g., Group A in Table
1) immediately started thinking out loud and bouncing
around ideas. Meanwhile, the reflective groups sat silent as
each member processed the problem. After a period of time
ranging from 30 seconds to 2 minutes, each reflective group
would begin discussing the problem together. These behaviors
were so distinctive that the independent observer, who
did not know the constituency of the groups, was able to
correctly identify each group as active, mildly reflective, or
strongly reflective. Thus, the pacing of interaction within
any group was well in line with the group member$(C!/(Bs learning
Other signs of greater participation and involvement by
the students became evident when the class came together
to discuss answers. After the students had worked on a scenario
for several minutes, I would randomly call on students
to explain what their group had come up with. Without
fail, students responded clearly and confidently, regardless
of their typical classroom persona. In particular, if a member
of their group had come up with a really good idea, they
gave credit to that person and would sometimes offer for him
or her to explain the idea in better detail. A favorite example
is when a group was describing their solution to a scenario
involving sorting. Together, they had developed a unique
list data structure that achieved significant speedups. When
describing it, the entire group got excited and started finishing
each other$(C!/(Bs sentences. Interestingly, this was a group of
highly reflective students who rarely spoke in section.
The educational benefits of group work come from the students
interacting with each other. As instructors, our goal
is to promote participation among our students. For short,
in-class group activities, we can achieve this by assigning
students to teams that encourage immediate productivity
as well as uniform participation among the group members.
This paper presented two methods that meet these goals.
The latent jigsaw method assigns groups based on prior
student knowledge in order to promote peer-teaching and
critical thinking. The other method uses Felder-Silverman
learning styles to promote participation by creating familiar
a social atmosphere to work in. When implemented, each
method created a classroom environment in which the students
were actively engaged and participating with the other
members in their groups.
By taking the time to form groups, the quality of collaborative
learning was radically changed. Additionally, my students$(C!/(B
own attitudes towards in-class group work appeared
to have changed. At the beginning of the term, a student
survey revealed that 53% of the 34 students had negative
opinions regarding in-class group work. The end of term
course evaluations reflected a different opinion, though. Out
of the 27 responses, only one student complained about the
group work. The rest of the responses were peppered with
positive comments about the group activities, including comments
about increased socialization, exposure to new ideas,
and better learning.
To repeat, interaction is the key to group learning. This
paper presented a strong argument for going the extra mile
and assigning teams for in-class group activities in order to
promote student participation. It is this author$(C!/(Bs hope that
other instructors will find these arguments and the team
formation methods useful in their own teaching practice.
I would like to thank all the students involved in this work.
Additional thanks also go to Steve Wolfman for taking the
time to observe my sections and to Ken Yasuhara for his
helpful feedback when writing this paper.
[1] W. Bridges. The Character of Organizations: Using
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