Groups, Group
Cognition & Groupware

Gerry Stahl

Drexel University

Philadelphia, USA

[email-masked]

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
knowledge being constructed by a small group 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 [as in 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 [still in 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 theory [5] and ethnomethodology [6], building on the philosophies of phenomenology [7], mediation [8] 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 perspectives [11] 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 Cognition [14] 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 our preliminary analysis in VMT of a group of students
working on a set of math problems in an online chat room. We are interested in
seeing how they work together using a minimal system of computer support in
order to see what forms of interaction might be supported by groupware with
special functionality designed to increase the effectiveness of the
collaboration.

In
order to capture both the individual and the group contributions to discourse
and to compare their results, we recently arranged an experiment with a
combination of individual and group work. It consists 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 should be possible to see what
the group interaction added.

In
previous work at VMT, 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 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 approaches to constructing shared knowledge.

I
will now analyze our experiment involving a group of college 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 with pencil and paper. We then had them enter an online
chat room and decide as a group on the correct answers. By collecting the
individual papers 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 on two sheets of paper with room to show their
work and to give their answers. 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 working silently with paper and pencil. Most students stopped work
before the time was up. Their papers were collected and new sheets of paper
with the same questions were distributed. The students were then instructed to
work in randomly-assigned groups and solve the same problems online. They
worked together in chat rooms for 39 minutes.

In
this paper, I analyze the results of one group of five students who worked
together in one chat room group. 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
Blackboard’s 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 except for the login
names. 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 paper); 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 paper, 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, Cosi got the answer to question 10 and explained
it to the others (although she had not gotten it on her paper). Hal got
question 11 right and the others accepted it (although he had not gotten it on
his paper).

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
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
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 America.
Today the ratio of male to female users is about 1 to 1. In that time the
number of American females using the internet has grown by 30,000,000, while
the number of males who use the internet has grown by 100%. By how much has the
total internet-user population increased in America in the past three years?

(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

0:00:04

352

4:32:01

Mic

of
internet users?

0:00:02

….

357

4:32:23

Dan

it
all comes from the 30000000

358

4:32:23

Mic

did
u get something for 10?

0:00:00

359

4:32:26

Dan

we
already know

0:00:03

360

4:32:44

Mic

30000000
is the number of increase in american females

0:00:18

361

4:33:00

Mic

and
since the ratio of male to female

0:00:16

362

4:33:02

Mic

is
1 to 1

0:00:02

363

4:33:09

Mic

thats
all i got to give. someone finish it

0:00:07

364

4:33:10

Mic

haha

0:00:01

365

4:33:18

Cosi

haha
you jackass

0:00:08

366

4:33:20

Mic

haha

0:00:02

367

4:33:21

Dan

hahaha

0:00:01

368

4:33:26

Mic

u
all thought i was gonna figure it out didnt

0:00:05

369

4:33:27

Mic

u

0:00:01

370

4:33:28

Mic

huh?

0:00:01

371

4:33:28

Hal

it
would be 60,000,000

0:00:00

372

4:33:30

Mic

hal

0:00:02

373

4:33:31

Mic

its
all u

0:00:01

374

4:33:33

Mic

see

0:00:02

375

4:33:34

Mic

i
helped

0:00:01

376

4:33:54

Cosi

ok,
so what’s 11 – just guess on 10

0:00:20

….

386

4:34:45

Mic

lets
get back to 5

387

4:34:47

Cosi

i
think it's more than 60,00000

0:00:02

388

4:34:57

Mic

way
to complicate things

0:00:10

389

4:35:03

Cosi

haha
sorry

0:00:06

390

4:35:05

Mic

life
was good until you said that

0:00:02

391

4:35:07

Mic

:(

0:00:02

392

4:35:18

Cosi

they
cant get higher equally and even out to a 1 to 1 ratio

0:00:11

393

4:35:27

Cosi

oh,
no wait, less than that

0:00:09

394

4:35:32

Cosi

50000000

0:00:05

395

4:35:34

Cosi

yeah,
it's that

0:00:02

396

4:35:36

Cosi

im
pretty sure

0:00:02

397

4:35:37

Mic

haha

0:00:01

398

4:35:38

Mic

how?

0:00:01

399

4:35:57

Cosi

because
the women pop had to grow more than the men in order to even out

0:00:19

400

4:36:07

Cosi

so
the men cant be equal (30)

0:00:10

401

4:36:11

Mic

oh
wow...

0:00:04

402

4:36:16

Mic

i
totally skipped the first sentencwe

0:00:05

403

4:36:16

Cosi

therefore,
the 50,000,000 is the only workable answer

0:00:00

404

4:36:19

Dan

very
smart

0:00:03

405

4:36:21

Cosi

Damn
im good

0:00:02

We can see here that
the group is meandering somewhat in trying to solve problem 10. Mic raises the
question of how to solve it (lines 350-352). Dan suggests that the 30,000,000
figure is key, and Mic tries to build on this suggestion. But Mic ends his
attempt with a laugh, clowning around that he was only pretending to figure out
the problem. Hal proposes that the answer is 60,000,000 (line 371), but then
Cosi complicates matters by questioning this answer (line 387).

Having rejected
Hal’s proposal, Cosi proceeds to solve the problem on her own. She
reasons that the male and female population cannot grow by the same amount from
uneven numbers to arrive at equal numbers (line 392). From this, she concludes
that the answer is 50,000,000. She announces that she is “pretty
sure” of this answer (line 396). At this point, it seems that Cosi has
solved the problem on her own.

Mic responds to
the statement that Cosi is only “pretty sure” and not positive by
requesting an explanation of how Cosi arrived at her opinion that the answer is
50,000,000—and not the 60,000,000 that Hal proposed (line 398).

In the following
lines (399, 400, 403), Cosi provides an account of her reasoning. If the
females grew by 30,000,000 then the males must have grown by less than that.
Therefore, the total growth must have been less than 60,000,000. The only
answer listed that meets this condition is 50,000,000—so that must be the
correct answer.

Cosi’s
extended turn providing an exposition of her thinking is interrupted only by Mic
(lines 401, 402), who simultaneously affirms Cosi’s approach, provides an
excuse for not having solved the problem himself, and admits to not having read
the problem carefully in the first place. In this way, Mic continues to move
the group toward making good decisions about which proposed answers to accept
while himself playing the fool. Dan speaks on behalf of the group (line 404),
accepting Cosi’s answer and proof by praising her as “very
smart,” to which she responds (line 405), “Damn, I’m
good.” In the subsequent discussion, both Hal and Mic agree with
Cosi’s solution. Cosi is anxious to move on to another problem and
finally says (line 419), “ok great, im smart, lets move on.”

From our
analysis, we can see the advantages that have long been claimed by other
researchers for collaborative learning [summarized in 21]. A number of students each contributed
their best ideas. Some students knew some answers, some others, and together
they arrived at a position where they effectively shared the whole set of best
answers that any of them had to start with. In addition, the group work
sustained their time-on-task beyond what any one student was willing to do,
arriving at correct answers for the final two problems.

According to the
foregoing analysis, the actual mathematical reasoning was done by individual
minds. The group was able to take the results of these individual achievements
and gather them together in a particularly effective way. In the end, all
members of the group had the opportunity to know more correct answers than they
could arrive at on their own. It may not be obvious that every student could
then solve all the problems on their own, but there were a number of
indications in the chat that students gained insights into aspects of the
problem solving that we can assume would stay with them as individual learning
outcomes.

In this
experiment, we were able to see how the group took good advantage of the
knowledge of its members, even though the group had not had any previous
experience working together and had no external scaffolding from the teacher or
the software in how to collaborate. As researchers, we know which students were
able to solve which problems on their own and we could then observe how they
interacted to solve the problems in the group context. Furthermore, we had a
simple, objective measure of mathematical skill based on correct answers to
standardized SAT problems. We observe that a group of students who individually
scored 18-27% was able to score 87% when working together. Furthermore, this
impressive result can be understood in terms of simply making good decisions
about which proposals to listen to on each problem and then spending more
engaged time-on-task on the two final problems.

2. Group
Cognition in Online Math

In the previous
section, the work of the student group was interpreted primarily at the
individual unit of analysis. The problem solving was discussed as the
accomplishment of individuals. The group decisions were discussed as a form of
voting among people who largely made up their minds individually. In many cases,
individuals did not hold strong opinions about the answers to the problems and
therefore left the group decision up to other individuals—who might have
a higher likelihood of knowing the correct answer—by remaining silent.
However, it is possible to analyze the chat differently, taking the group as
the unit of analysis.

The
central point of the alternative approach is that the meaning constructed in a
group discourse is often the result of the subtle ways in which utterances of
different speakers or writers interact, rather than through a simple addition
of ideas expressed or represented in the individual utterances.

Perhaps the
greatest problem in understanding how groups work is to clarify the relation of
individual to trans-individual contributions to the group meaning making.
Clearly, individual group members may have ideas of their own that they
introduce into the discourse. Their utterances may have to wait for the right
moment in the conversational flow and they might have to design their contributions
to fit into the discourse context in order to be accepted as useful proposals
with a chance of being taken up, but they also may bring with them some
premeditated meaning constructed by their proposer. Individuals also play a
necessary role as the interpreters of
the group meaning in an on-going way as they respond to the discourse [14, chapter 16]. On the other hand, the formative roles
of adjacency pairs and other references among utterances underline the
importance of analyzing meaning making at the group unit of analysis, not just interpreting the utterances of
individuals.

A more detailed
analysis of the negotiations of the answers for questions 1 through 9 in the
experiment shows that the group had methods for interacting that were quite
effective in making good decisions. They had subtle ways of coalescing the
individual group members into a collective that could work through the set of
math problems, discover solutions and decide which solutions to adopt as the
group’s answers. This suggests that the problem solving methods used by
the group of students is qualitatively different from the methods they use
individually. Another way of putting it is that the group collaboration brings
additional methods at the group unit of analysis that supplement the individual
cognitive methods of problem solving. It may be important to distinguish these
different classes of methods at the different levels of analysis, as well as to
see subsequently how they work together.

In defining his
concept of the zone of proximal
development, Vygotsky strongly distinguished between what a student could
accomplish individually and what that student could accomplish when working
with others [8, p 86]: “It is the distance between the
actual developmental level as determined by independent problem solving and the
level of potential development as determined through problem solving under
adult guidance or in collaboration with more capable peers.” Based on
psychological experiments, Vygotsky argued that what children “could do
only under guidance, in collaboration, and in groups at the age of
three-to-five years they could do independently when they reached the age of
five-to-seven years” (p. 87). In the chat, we have seen that older
students can also achieve significantly more in collaborative groups than
independently—and we have seen the methods of group interaction that one
particular group adopted in one case study to accomplish this.

We can also revisit
the solving of problem 10 as a group achievement. Of course, the sequence of
recorded events—the lines in the chat log—are the same. But now we
no longer attribute the source of the messages to the individuals as the
“expression” of internal mental ideas that they have worked out in
advance. Rather, we look for evidence in the details of the log of how messages
are responses to each other.

Mic’s
opening question (lines 350-352) is based on the problem statement. The problem
asks how much the population has increased. A straight-forward calculation of
this increase might involve subtracting from the total number of Internet users
now the corresponding figure for three years ago. But the two numbers needed
for such a calculation are missing from the problem statement. The problem only
gives indirect clues. The problem statement thereby calls for a less direct
strategy. Mic’s messages respond to this implicit requirement by making
it explicit.

Dan responds to
Mic’s question by proposing an approach for coming up with a strategy. He
says (lines 357 and 359), “It all comes from the 30,000,000 we already
know.” In other words, the strategic key is to start with the clue about
the number of females having grown by 30,000,000.

(Note that to
analyze the log we must disentangle line 358 from the middle of the two
fragments of Dan’s text and re-join Dan’s text [22]. Mic’s question (line 358) is posted
at the same time as Dan’s proposal, and as a consequence it is ignored
and left as a failed proposal [14, chapter 21] ).

Mic’s next
turn (lines 360-364) picks up on the 30,000,000 figure from Dan and tries to
take it further by adding the fact that came before that figure in the problem
statement, namely that “Today the ratio of male to female users is about
1 to 1.” Mic puts this forward and asks for the group to continue to
develop the strategy.

Mic’s
contribution is not the expression of some rational problem solving that we
might speculate took place in Mic’s mind. In fact, his contribution–if
considered as an individual proposal with math content—only vaguely
suggests a mathematical logic. It was primarily an interactive move to keep the
group effort going. Following Dan’s posting to the chat, there was an
unusually long pause of 18 seconds. In face-to-face conversation, a pause of a
few seconds is embarrassingly long and exerts considerable pressure on the
participants to make another contribution; in chat, 18 seconds can have a
similar effect. So Mic repeats Dan’s reference to 30,000,000. Following
another pause of 16 seconds, Mic adds the reference to the 1-to-1 ratio. He
then explicitly calls on the other group members to join in. He admits that he
cannot take it further himself, and he laughs.

Cosi, Dan and
Mic have a good laugh at Mic’s expense, taking his contribution as a
practical joke, as an attempt to look like he was making a significant
mathematical contribution and then stopping short of delivering. This fills in
an otherwise discouraging silence during which no one knows how to advance
mathematically with the problem. The laughter lightens up the interaction,
allowing people to throw ideas into the mix without worrying that they will
necessarily be taken too seriously if they are only partial, or even wrong.
After Mic’s jackass-like behavior, any other contribution would seem an
improvement. In fact, Mic’s proposal and request are taken up.

Hal then
proposes that the answer “would be 60,000,000” (line 371). This is
a direct consequence of finishing Mic’s partial proposal. If there are
30,000,000 females (line 360) and the ratio of males to females is 1 to 1
(lines 361-362) and you want to know the total number (line 351), then the
conclusion that “it would be 60,000,000” is at hand. Mic takes this
to be the answer to problem 10 and tries to take partial credit for it by
pointing out, “u see I helped” (lines 373-375).

At that point,
Cosi suggests the group should go on to problem 11 and “just guess”
on 10 (line 376). This declines to affirm Mic’s acceptance of 60,000,000
as the answer to question 10, but does so without raising this as a topic for
further group discussion. Without making a decision about 10, the group goes on
to all decide that the answer to problem 11 is C (lines 378-385, spanning just
half a minute), as already stated by Hal in line 353.

Mic then
summarizes the group’s status as: “So we got B for 10 and c for 11;
lets get back to 5” (lines 384-386). At this point, Cosi objects to
Mic’s continued assumption that Hal’s 60,000,000 is the answer to
problem 10. Mic and Cosi joke about their disagreement. Again, the
group’s light-hearted attitude avoids the potential of disagreements
within the group becoming disruptive of the group functioning.

Cosi then
formulates an argument (line 392) why the answer cannot be 60,000,000. The male
and female populations cannot get higher equally (i.e., by 30,000,000 each)
because they have to even out from unequal numbers according to the problem
statement. After formulating this text, Cosi checks and then corrects her
previous claim that “I think it’s more than 60,000,000” (line
387): “Oh, no wait, less than that: 50,000,000” (lines 393-394).

Cosi is somewhat
hesitant about her revised claim. First she checks it and says, “Yeah,
it’s that” (line 395), followed by the hedge, “Im pretty
sure” (line 396). Mic continues the laughter and then requests an account
of how Cosi is pretty sure that the answer should be 50,000,000.

After a 19
second pause, Cosi takes the extended expository turn that Mic had offered her
and the others had left open. She lays out a concise proof of her claim. Her
argument concerns the increase in the number of females and the ratios of male
to female users—the issues raised at the beginning of the group
discussion by Dan and Mic. It is plausible that Cosi used the 19 second pause
to reflect upon the solution that the group had come to and that her
contributions had completed. Thus, her well-worked out retrospective account
seems like the expression of her mental work in constructing the narrative
explanation, although her earlier contributions to solving the math of the problem
seemed more like spontaneous reactions to the flow of the group discourse.

A solution to
problem 10 carried out from scratch using algebraic methods that translated the
word problem into a set of equations to be solved for unknown values would have
looked very different from Cosi’s argument. Her contributions to the chat
did not express an independent, individual approach to the problem. Rather,
they were responses to preceding contributions. Cosi’s texts performed
checks on the previous texts and extended their arguments in directions opened
up and called for by those previous contributions. Although Dan, Mic and Hal did
not carry out the further steps that their own contributions required, they
succeeded in starting a discourse that Cosi was able to repair and complete.

This analysis of
the log excerpt gives a more group-centered view of the collaborative solving of the math problem by the group. Of course, at
the level of individual postings, each contribution was that of an individual.
But it is not necessary to see those contributions as expressions of prior
private mental activities. Rather, they can be seen as responses to the
previous texts, the context of the problem-solving task (e.g., the elements of
the problem 10 text) and elicitations of contributions to come. These ties of
the individual postings to the sequentially unfolding group discourse can be
seen in the form of the postings themselves: single
utterances do not stand on their own, but make elliptical references to previous mentionings, indexical references to matters in the physical and discourse
situation and projective references
to anticipated future responses or actions of other people [see 14, chapter 12]. The
references weave a temporal fabric of discourse that defines the meaning of
each text within its narrative context. Thus, the individual contributions are
incorporated into a problem solving dialog at the group unit of analysis, which
is where the meaning of the log is constructed.

In weaving the
discourse fabric, groups use different methods. We have discussed two methods of
group discourse used in math problem solving in this chat: exploratory inquiry
and expository narrative. In the excerpt concerning problem 10, we have seen
that the group first explores a solution path by different students making
small contributions that build on each other sequentially. When a candidate
answer is reached that someone is “pretty sure” about, that person
is asked to provide an extended account or proof of the answer. Thus, Cosi
participates first in the joint exploratory inquiry and then provides an
expository narrative. Both these methods are interactive discourse methods that
involve responding to requests, structuring texts to be read by other group
members and eliciting comments, questions and uptake.

Conversation
analysts have identified adjacency pairs
as a powerful way in which meaning is interactively constructed. An adjacency
pair is a set of utterances by different people that forms a smallest meaningful
unit [23]. For instance, a greeting or a question
cannot meaningfully stand alone. You cannot meaningfully express a greeting or
a question without someone else being there in the discourse to respond with a return
greeting or an answer. The other speaker may ignore, decline or respond to your
greeting or question, but your utterance cannot be a greeting or a question
without it addressing itself to a potential respondent. The respondent may just
be an imaginary dialog partner if you are carrying out the dialog in your mind [see 9]. Adjacency pairs are fundamental
mechanisms of social interaction; even very young speakers and quite disabled
speakers (e.g., advanced Alzheimer sufferers) often respond appropriately to
greetings and questions. Adjacency pairs are important elements for weaving
together contributions from different participants into a group discourse.

When I analyzed
a different online chat of mathematics problem solving, I defined an adjacency
pair that seemed to play a prominent role. I called it the math proposal adjacency pair [14, chapter 21]. In that chat, a math proposal adjacency
pair consisted of a problem solving proposal by one person followed by a
response. The proposal addressed the other students
as a group and required one or more of them to respond to the proposal on
behalf of the group. The proposal might be a tactical suggestion, like
“I think we should start with the 30,000,000 figure.”
Alternatively, it might be a next step in the mathematical solution, like
“They can’t get higher equally and even out to a 1 to 1
ratio.” The response might simply be “k”—“okay,
that’s interesting, what’s next?” The pattern was that
progress in problem solving would not continue after someone made a proposal
until the group responded to that proposal. If they responded affirmatively, a
next step could then be proposed. If they responded with a question or an
objection, then that response would have to be resolved before a next proposal
could be put forward. It was important to the group that there be some kind of
explicit uptake by the group to each proposal. A counter-example proved the
rule. One participant made a failed proposal. This was an attempt to suggest a
strategy involving proportions. But the proposer failed to formulate his
contribution as an effective first part of a math proposal adjacency pair, and the
rest of the group failed to take it up with the necessary second pair-part
response.

In the chat we
are analyzing now, the math proposal adjacency pairs have a somewhat different
appearance. We can identify proposals in, for instance, lines 352, 357, 360,
362, 371, 387, 392 and 394. None of these is followed by a simple, explicit
response, like “ok.” Rather, each is eventually followed by the
next proposal that builds on the first, thereby implicitly affirming it. This
is an interesting variation on the math proposal adjacency pair method of
problem solving. It illustrates how different groups develop and follow
different group methods of doing what they are doing, such as deciding upon
answers to math problems.

If we combine
the proposals from Mic, Dan, Hal and Cosi, they read like the cognitive process
of an individual problem solver:

How can I figure out the increase in users without knowing
the total number of internet users? It seems to all come from the 30,000,000
figure. 30,000,000 is the number of increase in American females. Since the
ratio of male to female is 1 to 1, the total of male and female combined would
be 60,000,000. No, I think it must be more than 60,000,000 because the male and
female user populations can’t get higher at equal rates and still even
out to a 1 to 1 ratio after starting uneven. No, I made a mistake, the total
must be less than 60,000,000. It could be 50,000,000, which is the only
multiple choice option less than 60,000,000.

Mathematical
problem solving is a paradigm case of human cognition. It is common to say of
someone who can solve math problems that he or she is smart. In fact, we see
that taking place in line 404. Here, the group has solved the problem by
constructing an argument much like what an individual might construct. So we
can attribute group cognition or intelligence to the group [see 14, esp. chapter 19].

Unfortunately,
the group of students in the chat log does not seem to attribute the problem
solving intelligence to itself, but only to one of its members, Cosi. Because
she takes the final step and arrives at the answer and because she provides the
narrative account or proof, Dan says of her, “very smart” (line
404). Later (line 419), Cosi agrees, downgrading the self-praise by using it to
close the discussion of problem 10 and of her role in solving it by proposing
that the group move on to a remaining problem: “Ok great, im smart, lets
move on.” Casting Cosi as the smart one who solves problems leaves Mic
cast as the jackass or class clown when in fact Mic is very skilled at
facilitating the chat so that the whole group solves problems that neither Mic
nor the others solved independently.

There is an
ideology of individualism at work here that encourages both educational
researchers and student participants to view problem solving as an
accomplishment of individuals rather than groups. This has serious consequences
for the design and adoption of groupware to support problem solving, as well as
for research methodology and student learning. If groupware designers tried to
support collaborative interactions, then they might design more than just
generic communication platforms for the transmission of expressions of personal
ideas. If researchers studying the use of groupware focused on processes of
collaboration and the methods that groups used to solve problems—as
opposed to treating exclusively individuals as cognitive agents—then
research methods might focus more on conversation analysis [17], video analysis [24] and their application to discourse logs
than on surveys and interviews of individual opinions. If students using
groupware conceived of their work as interactively achieving a group solution,
they might take more advantage of groupware collaboration features and might
structure their textual contributions more explicitly as parts of an interwoven
fabric of collaborative knowledge-building group discourse.

3. Groupware to
Support Group Cognition

The first step in
thinking about the design of groupware today is to understand the methods that
groups use to accomplish problem solving, scientific inquiry, decision making,
argumentation and the other tasks that they want to do. Generic communication
platforms developed to meet the needs of corporations will continue to make new
technologies available in response to market pressures. Within education,
course management systems to support the administration of distance education
will proliferate under their own economic drives. But those developments are
almost exclusively guided by a philosophy of individual cognition and the
transfer of representations of mental contents.

The preceding analysis
of a case study of group cognition suggests a variety of new design principles.
Clearly, one or two case studies is not enough to inform a new approach to
groupware design. This paper has only suggested the kind of analysis that is
needed to investigate and characterize the methods that groups of students
might use to do their work collaboratively. Different age groups, tasks,
cultures and environments will introduce considerable variety in how groups
constitute themselves, define their work, socialize, problem solve, persuade,
guide, decide, conclude, etc. Nevertheless, a number of principles can already
be suggested. It is important to start thinking about groupware design because
ideas for innovative functionality and prototypes of new components will have
to be tried out with online groups and the resultant logs analyzed. One cannot
know how new technologies will lead to new member methods without such
investigation.

Here are some
very preliminary suggestions for groupware design principles:

Persistency and
Visibility. Make the group work visible and persistent so that everyone in
the group can easily see what has been accomplished by all members. Ideally,
important contributions should stand out so that people do not have to search
for them, but are made aware of them with little or no effort. This is a
non-trivial requirement, since the work of a group quickly becomes too
extensive for everyone to read and keep track of. The software must somehow
help with this.

Deictic
Referencing. As discussed above, the references from one message to another
or to objects in the problem context are essential to the meaning making.
Software could make these references visible under certain conditions. Patterns
of references among proposals, adjacency pairs and responses between different
group members could also be displayed in order to give participants indicators
about how their group interaction is going.

Virtual Workspaces.
Ideally, the groupware would encourage noticing, recognizing and reflecting
on related contributions. There should certainly be group workspaces for
different kinds of work to be done together, creating shared artifacts. For
instance, there could be group workspaces for taking notes and annotating them,
for jointly navigating the Internet, for constructing shared drawings, for
building formal arguments together, for collecting annotated bibliographies and
other lists or collections. Issues of turn-taking, ownership and control become
important here.

Shared and
Personal Places. It may be useful to distinguish and sometimes to separate
individual and group work [13]. However, it may be important to make even the
individual work visible to everyone. Group accomplishments build on the
individual contributions. Even contributions that the proposer does not
consider significant may, as we have seen above, provide a key to progress of
the group. In addition, group members often want to know what people are doing
when they are not active in the group. Content should move fluidly from place
to place.

Computational
Support. Of course, a major advantage of having groupware systems running
on computers is that they can provide computational support to the work of
their users. They can filter or tailor different views or computational
perspectives [14, chapter 6] of materials in the chat or
workspaces, as well as providing search, browsing and annotating facilities.
They can play various moderator roles.

Access to Tools
and Resources. Another advantage of the networked computer infrastructure
is that groupware can provide structured access to information, tools and other
resources available on the Internet, for instance in relevant digital libraries
and software repositories.

Opening New
Worlds and (Sub-)Communities. Finally, Internet connectivity allows for
groups and their members to participate in larger online communities and to
interact with other groups—either similar or complementary. Groupware
could facilitate the building of open-ended networks of individual, group and
community connections, or the definition of new sub-communities.

Allowing Natural
Language Subtleties. While computer support brings many potential
advantages, it also brings the danger of destroying the extreme flexibility and
adaptability of the natural language used in conversation and group
interactions. Groupware designs should be careful not to impose rigid ontologies
and sets of allowable speech acts for the sake of enabling automated analyses. It
should permit the use of overloaded, multiple functioning, subtle linguistic expression
that is not reified, stereotyped, coded or packaged, but that opens space for
interpretation, engagement, creativity, problem solving. As we saw in the chat,
even a simple laugh can perform multiple complex roles simultaneously. Chat is
a vibrant form of human interaction in which people exercise their creativity
to invent linguistic novelties such as abbreviations, contractions, emoticons
and new ways of interacting textually. Groupware should support this, not cramp
it.

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[*] The 11 questions and the complete chat
log are available at:

http://www.cis.drexel.edu/faculty/gerry/publications/conferences/2005/criwg.

The analysis
in this paper is indebted to conversation analysis data sessions at the VMT
project, led by Alan Zemel, and comments from Stephen Weimar and Martin
Wessner.