Analyzing and Designing
the Group Cognition Experience
http://www.cis.drexel.edu/faculty/gerry
Abstract. More
than we realize it, knowledge is often constructed through interactions among
people in small groups. The Internet, by allowing people to communicate
globally in limitless combinations, has opened enormous opportunities for the
creation of knowledge and understanding. A major barrier today is the poverty
of adequate groupware. To design more powerful software that can facilitate the
building of collaborative knowledge, we need to better understand the nature of
group cognition—the processes whereby ideas are developed by small groups. We
need to analyze interaction at both the individual and the group unit of
analysis in order to understand the variety of processes that groupware should
be supporting. This paper will look closely at an empirical example of an
online group problem-solving experience and suggest implications for groupware
design.
1. Individual
Learning in Groups
Groupware is software
that is specifically designed to support the work of groups.
Most software in
the past, in contrast, has been designed to support the work of individuals.
The most popular applications—such as word processors, Internet browsers and
spreadsheets—are structured for use by one individual at a time. Software for
communication among people—like an email program—assumes a model of
communication as transmission of messages from one person to other individuals.
Building on these examples, one could design groupware to support groups
conceived of as sets of individuals. Such software would allow individuals to
express their mental ideas, transmit these expressions to other people, receive
expressions transmitted from other people and make sense of received messages
as expressions of the ideas in the heads of the other people.1 Possibilities for improving these
designs might be conceived in terms of “increasing the bandwidth” of the
transmissions, possibly taking face-to-face communication as the “gold
standard” of communication with a wide bandwidth of many channels (words,
intonation, gaze, facial expression, gesture, body language).
Until
recently, most research about groups has focused on the individual people in
the group as the cognitive agents. For instance, research on cooperative
learning in the 1970s,2 assumed that knowledge resided in the individuals, and that group
interaction was most useful as a way of transferring knowledge from one
individual to another or as a way of motivating individuals to perform better.
Educational research on groups typically measured learning in terms of
individual test outcomes and tried to study what is going on in the minds of
the individuals through surveys, interviews and talk-aloud protocols. Similarly,
research in social psychology about small groups conceptualized the groups as
sets of rationally calculating individuals seeking to maximize their own
advantages. This broad tradition looks to the individual as the unit of
analysis, both to understand what takes place in group behavior and to measure quantitative
learning or knowledge-building outcomes.
In
the 1990s, the individualistic approach was thoroughly critiqued by theories of
situated cognition,3 distributed cognition,4 socio-cultural activity theory5 and ethnomethodology,6 building on the philosophies of phenomenology,7 mediation8 and dialog.9 These new approaches rejected the view that cognition or the
construction of knowledge took place exclusively in the isolated minds of
individuals, and showed how it emerged from concrete situations and
interpersonal interactions. One consequence that could be drawn from this would
be to analyze cognition at the small-group unit of analysis, as in many cases a
product of social interaction within the context of culturally-defined rules or
habits of behavior.
An
alternative approach to designing groupware based on a group conception of
cognition would provide functionality to support the working of a group as an
organic whole, rather that just supporting the group members as individuals and
treating the group as the sum of its parts. In the past, a number of
researchers have tried to develop groupware that supports the functioning of
the group itself, such as the formation of groups,10 intertwining of perspectives11 and negotiation of group decisions.12; 13
Here
I would like to further develop the approach focused on the group that I
presented in Group Cognition14 and that is being investigated in the Virtual Math Teams (VMT)
project at the Math Forum at Drexel University. In part I of the book, I
present my own attempts to design software to support small-group interactions
(building, of course, on previous work by others), and conclude that we need to
better understand how groups work before we can effectively design groupware.
In part II of the book, I then discuss how to analyze the methods that are used
in groups to construct meaning and knowledge. Then I develop a concept of group
cognition in part III to talk about what takes place at the group unit of
analysis.
In
this paper, I report on a group of students working on a set of math problems
in an online chat room. In the VMT project, we were interested in seeing how well
groups work together using a minimal chat system so we could see what forms of
interaction might be supported by groupware with special functionality designed
to increase the effectiveness of collaboration.
In
order to capture both the individual and the group contributions to discourse
and to compare their results, we arranged an experiment with a combination of
individual and group work. It consisted of an individual phase where the
knowledge of the individuals can be objectively assessed, followed by a group
phase in which the references and proposals can be analyzed at both the
individual and the group units of analysis. By seeing what the individuals knew
before they participated in the group phase, it was possible to see what the
group interaction added.
In
previous work at the VMT project, we have characterized two different general
patterns of chat discourse: expository
narrative and exploratory inquiry.15 These are two common methods of conducting online discourse that
embody different relationships of the group to its individual members. We view online
chat as a form of text-based interaction, where short texts respond to each
other.16 We analyze the chat discourse with a variation of conversation
analysis—a scientific methodology
based on ethnomethodological principles for analyzing everyday verbal
conversation. In the VMT project, we have begun to adapt conversation analysis
to chat by taking into account the consequences introduced by the textual
medium, the math content, the physical separation and other differences from
everyday conversation.
Expository
narrative involves one person dominating the interchange by contributing more
and longer texts.17 Basically, the normal turn-taking procedures in which group members
take roughly equal and alternating turns is transformed in order to let one
person narrate an extended story or explanation. For instance, if a student has
already solved a math problem that the group is working on, that student might
propose their solution or indicate that they have a solution and the others
might request an explanation of the proposed solution. There would still be
some forms of interaction, with members of an audience asking questions,
encouraging continuation, indicating understanding, raising questions, etc. But
in general, the proposer would be allowed to provide most of the discourse. In
conversation, this kind of pattern is typical where one member narrates a story
or talks in detail about some events or opinions.18 Exposition in math has its own characteristics, such as providing
mathematical warrants for claims, calculating values, addressing issues of
formal logic, etc. But it follows a turn-taking profile similar to that of
conversational narrative.
Exploratory
inquiry has a different structure. Here, the group members work together to
explore a topic. Their texts contribute from different perspectives to
construct some insight, knowledge, position or solution that cannot be
attributed to any one source but that emerges from the “inter-animation of
perspectives.” 9; 19 Exploratory inquiries tend to take on the appearance of group
cognition. They contrast with expository narratives in a way that is analogous
to the broad distinction between collaboration
and cooperation.20 Collaboration involves a group of people working on something
together, whereas cooperation involves people dividing the work up, each
working by themselves on their own part and then joining their partial
solutions together for the group solution. Expository narratives tend to take
on the appearance of cooperation, where individuals contribute their own
solutions and narrate an account of how they arrived at them. In a rough way,
then, exploratory and expository forms of discourse seem to reflect group
versus individual contributions to constructing shared knowledge.
I
will now analyze our experiment involving a group of students in an online chat
discussing a series of math problems. I will try to tease apart the individual
and the group contributions to meaning making, knowledge building and problem
solving. We conducted the experiment using a set of well-defined math problems
for which it is clear when an individual or a group arrives at the correct
answer. We gave the individuals an opportunity to solve the problems on their
own and submit their results. We then had them interact in an online chat room
and decide as a group on the correct answers. By collecting their individual solutions
and logging the chat, we obtained data about the individual and the group
knowledge, which we can objectively evaluate and compare.
The
students were given 11 problems. The problems were a variety of algebra and
geometry problems, some stated as word problems. Most required some insight.
They came from the Scholastic Aptitude Tests (SAT), which are taken by high
school students in order to apply to colleges in the United States. They are
primarily multiple choice questions with five possible answers, only one of
which is correct. [*]
For
the individual phase of the experiment, the students had 15 minutes to complete
the problems individually and submit their answers. The students then worked in
randomly-assigned groups to solve the same problems online. They worked
together in chat rooms for 40 minutes.
In
this paper, I analyze the results of one group of five students who worked
together in one chat room. None of the students in this group did impressively
well on the test as an individual. They each got 2 or 3 question right out of
the 11 (see table 1) for a score of 18% or 27%.
Table 1.
Problems answered correctly by individuals and the group.
|
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
Score |
|
Hal |
|
X |
X |
|
|
|
|
X |
|
|
|
27% |
|
Dan |
|
|
X |
X |
|
|
|
|
|
|
|
18% |
|
Cosi |
|
|
X |
|
|
|
X |
|
X |
|
|
27% |
|
Mic |
|
|
|
|
X |
|
X |
|
|
|
|
18% |
|
Ben |
|
|
X |
|
|
|
|
X |
|
|
|
18% |
|
Group |
|
X |
X |
X |
X |
|
X |
X |
X |
X |
X |
82% |
For
the experiment’s group phase, the students worked in a chat room using a
generic group chat facility without a shared whiteboard. The software is simple
and familiar to the students. The students did not know each other and did not
have any information about each other. They had not worked together before and
had not participated in a chat like this before. The result of the group work
was that the group decided upon the correct answers to 9 of the 11 problems,
for a group score of 82%. Thus, the group did considerably better than any of
the individual students.
However,
it seems that each of the correct group answers can be attributed to one of the
students. Although each student got only 2 or 3 answers right, together at
least one of them correctly answered questions 2, 3, 4, 5, 7, 8, 9. No one
understood question 1, and the group did not get this answer either. Question 2
was correctly answered by Hal, who persuaded the group. Question 3 was
correctly answered by everyone except Mic. Question 4 was correctly answered by
Dan. Question 5 gave the group a lot of frustration because no one could figure
it out (although Mic had gotten it right on his own); they eventually accepted
the correct answer from someone outside the group. No one understood question
6, and the group got it wrong. They got question 7 right (following Cosi and
Mic). Only Hal got question 8, but he persuaded the others. (Ben also got it on
his own, but did not participate in the group discussion.) Cosi got the answer
to question 9. No one got questions 10 or 11, so the group had to work on these
together. The discussion of question 10 was particularly interesting. As we
will see, it looks like Cosi got the answer to question 10 and explained it to
the others (although she had not gotten it on her own). Hal got question 11
right and the others accepted it (although he had not gotten it on his own).
So
it appears as though the math problems were actually solved by individuals. The group responded to proposed answers. In
instances where there were competing answers or other issues, the group required
the proposer to give an account, defense or explanation. This resulted in an
expository form of discourse where one member proposed an answer and explained
why it was right. Although the group was not experienced in working together,
they succeeded in selecting the best answers that their members could come up
with. The result of the group cooperation was to achieve a sum of their best individual
results.
It
is particularly interesting to observe how the group negotiated their group
answers given proposals from various members. In some cases, everyone proposed
the same answer and it was easy to establish a consensus. In certain other
cases, only one person proposed an answer and the others simply went along with
it. In more interesting cases, when someone proposed an answer that
contradicted other people’s opinions or was questionable for some other reason,
the proposer was required to give an explanation, justification or accounting
of their proposal. We do not have space here to analyze each of the negotiations:
how they were begun, how people contributed, how the discussion was continued,
how decisions were made and how the group decided to move on to a new problem.
In particular, we cannot go into the integration of social chatter and math
reasoning or fun making and decision making. Rather, we will take a look at the
discussion of question 10, which was particularly interesting because no one
had already solved this problem and because we can see the solution emerging in
the discourse.
Question 10 is a
difficult algebra word problem. It would take considerable effort and expertise
for a student to set up and solve equations for it. The group manages to
finesse the complete algebraic solution and to identify the correct
multiple-choice answer through some insightful reasoning. Question 10 is:
Three years ago, men made up two out of every
three internet users in
(A) 50,000,000 (B) 60,000,000 (C) 80,000,000 (D)
100,000,000 (E) 200,000,000
The core discussion of this question takes place in the chat excerpts shown in Table 2.
Table 2.
Excerpts from the chat discussion about problem 10.
|
Line |
Time |
Name |
Message |
Interval |
|
350 |
4:31:55 |
Mic |
how
do we do this.. |
|
|
351 |
4:31:59 |
Mic |
without
knowing the total number |