Abstract. We are
investigating the nature of shared knowledge under distributed circumstances.
In particular, we are exploring the possibility that a small group of students
collaborating online on math problems can construct group knowledge that
exceeds the knowledge of the individual group members.
The term “shared knowledge” is ambiguous. It can refer to:
· Similarity of individuals’ knowledge: The knowledge in the minds of the members of a group happen to overlap and their intersection is “shared.”
· Knowledge that gets shared: Some individuals communicate what they already knew to the others.
· Group knowledge: Knowledge is interactively achieved in discourse and may not be attributable as originating from any particular individual.
Collaboration theory argues that “common ground” – a form of shared knowledge – is required for successful communication. But it is not always clear which of the above forms authors are referring to, or whether repairs to breakdowns in such common ground comes from ideas that existed in someone’s head and are then passed on to others until a consensus is established, or whether the common ground might be constructed in the interaction of the group as a whole. It is possible that shared knowledge can sometimes be explained in one way, sometimes another. At any rate, it seems that the question of the source of shared knowledge in a given case might best be treated as an empirical question.
At Drexel University, we are undertaking a research project to investigate empirically whether knowledge sharing under distributed conditions can construct group knowledge that exceeds the individual knowledge of the group’s members. Our hypothesis is that precisely such a result is, in fact, the hallmark of collaborative learning, understood in an emphatic, visionary sense.
We are investigating not only whether computer-supported
collaborative learning under distributed conditions can construct novel group
knowledge, but what conditions are favorable to fostering such an outcome. We
will do this by designing and implementing an experimental service in the Math
Forum @ Drexel (www.mathforum.org), a
popular online site with resources and problems related to K-12 school
mathematics. Students visiting the site will be invited to join small virtual
teams to discuss and solve math problems collaboratively online. We will
analyze the interactions in these teams to determine how they build shared
knowledge under distributed circumstances.
Our work is motivated by the following circumstance: Research
on learning and education is troubled to its core by a conflict of paradigms.
Sfard (1998) reviewed some of the history
and consequences of this conflict in terms of the incompatibility of the
acquisition metaphor (AM) of learning and the participation metaphor (PM). AM
conceives of education as a transfer of knowledge commodities and their
subsequent possession by individual minds. Accordingly, empirical research in
this paradigm looks for evidence of learning in changes of mental contents of
individual learners. PM, in contrast, locates learning in intersubjective,
social or group processes, and views the learning of individuals in terms of
their changing participation in the group interactions. AM and PM are as
different as day and night, but Sfard argues that we must learn to live in both
complementary metaphors.
The conflict is particularly pointed in the field of CSCL
(computer-supported collaborative learning). The term “collaborative learning”
can itself be seen as self-contradictory given the tendency to construe
learning as taking place in individual minds. Having emerged from a series of
paradigm shifts in thinking about instructional technology (Koschmann, 1996), the field of CSCL is still
enmeshed in the paradigm conflict between opposed cognitive and sociocultural
focuses on the individual and the group (Kaptelinin & Cole,
2002).
In a keynote at the CSCL ’02 conference, Koschmann argued that even exemplary
instances of CSCL research tend to adopt a theoretical framework that is
anathema to collaboration (Koschmann, 2002a). Koschmann recommended that
talk about “knowledge” as a thing that can be acquired should be replaced with
discussion of “meaning-making in the context of joint activity” in order to
avoid misleading images of learning as mental acquisition and possession.
Although Koschmann’s alternative phrase can describe the
intersubjective construction of shared meanings achieved through group
interaction, the influence of AM can re-construe meaning-making as something
that must perforce take place in individual human minds, because it is hard for
most people to see how a group can possess mental contents. In a paper at CSCL
’03 responding to Koschmann’s earlier keynote, (Stahl, 2003b) argued that both Koschmann’s
language and that of the researchers he critiqued is ambiguous and is subject
to interpretation under either AM or PM. A simple substitution of wording is
inadequate; it is necessary to make explicit when one is referring to
individual subjective understanding and when one is referring to group
intersubjective understanding – and to make clear to those under the sway of AM
how intersubjectivity is concretely possible.
The problem with recommending that researchers view learning
under both AM and PM or that they be consistent in their theoretical framing is
that our common sense metaphors and widespread folk theories are so subtly
entrenched in our thinking and speaking. The languages of Western science
reflect deep-seated assumptions that go back to the ideas of Plato’s Meno and
the ego cogito of Descartes’ Meditations.
It is hard for most people to imagine how a group can have knowledge, because
we assume that knowledge is a substance that only minds can acquire or possess,
and that only physically distinct individuals can have minds (somewhere in
their physical heads).
We are addressing this central research issue head-on by
studying online collaborative learning in the specific context of Math Forum
problems, with the aim of presenting empirical examples of concrete situations
in which groups can be seen to have knowledge that is distinct from the
knowledge of the group members. By analyzing these situations in detail, we
will uncover mechanisms by which understanding of mathematics passes back and
forth between the group as the unit of analysis and individual group members as
units of analysis.
One example might be a group of 5 high school students
collaborating online over a two week period. They solve an involved algebra
problem and submit a discussion of their solution to the Math Forum. By looking
carefully at the computer logs of their interactions in which they
collaboratively discussed, solved and reflected upon the problem, we can see
that the group solution exceeds the knowledge of any individual group members
before, during or after the collaboration. For instance, there may be some
arguments that arose in group interaction that none of the students fully
understood but that contributed to the solution. Or a mathematical derivation
might be too complicated for any of the students to keep “in mind” without
reviewing preserved chat archives or using an external representation the group
developed in an online whiteboard. By following the contributions of one member
at a time, it may also be possible to find evidence of what each student
understood before, during and after the collaboration, and thereby to follow
individual trajectories of participation in which group and individual
understandings influenced each other,
While we do not anticipate that group knowledge often
exceeds that of all group members under generally prevailing conditions, we
hypothesize that it can do so at least occasionally under particularly
favorable conditions. We believe that we can set up naturalistic conditions as
part of a Math Forum service and can collect sufficient relevant data to
demonstrate this phenomenon in multiple cases. The analysis and presentation of
these cases should help to overcome the AM/PM paradigm conflict by providing
concrete illustrations of how knowledge can be built through group
participation as distinct from – but intertwined with – individual acquisition
of part of that knowledge. It should also help to clarify the theoretical
framing of acts of meaning-making in the context of joint activity.
We believe that the theoretical confusion surrounding the
possibility of group knowledge presents an enormous practical barrier to
collaborative learning. Because students and teachers believe that learning is
necessarily an individual matter, they find the effort at collaborative
learning to be an unproductive nuisance. For researchers, too, the
misunderstanding of collaborative learning distorts their conclusions, leading
them to look for effects of pedagogical and technological innovation in the
wrong places. If these people understood that groups can construct knowledge in
ways that significantly exceed the sum of the individual contributions and that
the power of group learning can feed back into individual learning, then we
might start to see the real potential of collaborative learning realized on a
broader scale. This project aims to produce rigorous and persuasive empirical
examples of collaborative learning to help bring about the necessary public
shift in thinking.
CSCL grows out of research on cooperative learning that
demonstrated the advantages for individual learning of working in groups (e.g., Johnson &
Johnson, 1989).
There is still considerable ambiguity or conflict about how the learning that
takes place in contexts of joint activity should be conceptualized. While it
has recently been argued that the key issues arise from ontological and
epistemological commitments deriving from philosophy from Descartes to Hegel (Koschmann, 2002b;
Packer & Goicoechea, 2000), we believe that it is more a matter of focus on
the individual (cognitivist) versus group (sociocultural) as the unit of
analysis (Stahl, 2003a, 2003b). Positions on the issue of
the unit of learning take on values along a continuous spectrum from individual
to group:
·
Learning is always accomplished by individuals,
but this individual learning can be assisted in settings of collaboration,
where individuals can learn from each other.
·
Learning is always accomplished by individuals,
but individuals can learn in different ways in settings of collaboration,
including learning how to collaborate.
·
Groups can also learn, and they do so in
different ways from individuals, but the knowledge generated must always be
located in individual minds.
·
Groups can construct knowledge that no one
individual could have constructed alone by a synergistic effect that merges
ideas from different individual perspectives.
·
Groups construct knowledge that may not be in
any individual minds, but may be interactively achieved in group discourse and
may persist in physical or symbolic artifacts such as group jargon or texts or
drawings.
·
Group knowledge can be spread across people and
artifacts; it is not reducible to the knowledge of any individual or the sum of
individuals’ knowledge.
·
All human learning is fundamentally social or
collaborative; language is never private; meaning is intersubjective; knowledge
is situated in culture and history.
·
Individual learning takes place by internalizing
or externalizing knowledge that was already constructed inter-personally; even
modes of individual thought have been internalized from communicative
interactions with other people.
·
Learning is always a mix of individual &
group processes; the analysis of learning should be done with both the
individual and group as units of analysis and with consideration of the
interplay between them.
In this project, we take a rather strong position on
collaborative learning as our working hypothesis:
·
H0 (collaborative
learning hypothesis): A small online group of learners can (on occasion and
under favorable conditions) build knowledge and understanding that exceeds that
of its individual members.
The different positions listed above are supported by a
corresponding range of theories of human learning. Educational research on
small group process in the 1950’s and ‘60’s maintained a focus on the
individual as learner (Johnson & Johnson,
1989; Stahl, 2000).
Classical cognitive science in the next period continued to view human
cognition as primarily an individual matter – internal symbol manipulation or
computation across mental representations, with group effects treated as
secondary boundary constraints (Simon, 1981; Vera &
Simon, 1993).
In reaction to these views, a number of sociocultural theories have become
prominent in the learning sciences in recent decades. To a large extent, these
theories have origins in much older works that conceptualized the situated-ness
of people in practical activity within a shared world (Bakhtin, 1986;
Heidegger, 1927/1996; Husserl, 1936/1989; Marx, 1867/1976; Schutz, 1967;
Vygotsky, 1930/1978).
Here are some representative theories that focus on the group as a possible
unit of knowledge construction:
·
Collaborative
Knowledge Building. A group can build knowledge that cannot be attributed
to an individual or to a combination of individual contributions (Bereiter, 2002; Fuks,
Gerosa, & Pereira de Lucena, 2001; Hakkarainen & Lipponen, 2002; Scardamalia
& Bereiter, 1996; Wasson & Morch, 2000).
·
Social
Psychology. One can and should study knowledge construction at both the
individual and group unit of analysis, as well as studying the interactions
between them (Daradounis, Xhafa,
& Marques, 2003; Fischer & Granoo, 1995; Palen, 1999; Resnick, Levine,
& Teasley, 1991).
·
Distributed
Cognition. Knowledge can be spread across a group of people and the tools
that they use to solve a problem (Hutchins, 1996;
Hutchins & Palen, 1998; Solomon, 1993; Wasson & Morch, 2000).
·
Situated
Cognition. Knowledge often consists of resources for practical activity in
the world more than of rational propositions or mental representations (Hewitt, Scardamalia,
& Webb, 1998; Polanyi, 1966; Schön, 1983; Suchman, 1987; Winograd &
Flores, 1986).
·
Situated
Learning. Learning is the changing participation of people in communities
of practice (Chaiklin & Lave,
1993; Graether & Prinz, 2001; Hewitt, 1997; Lave & Wenger, 1991; Prinz,
1999; Schlager, Fusco, & Schank, 2002; Shumar & Renninger, 2002).
·
Zone of
Proximal Development. Children grow into the intellectual life of those
around them; they develop in collaboration with adults or more capable peers (Brown & Campione,
1994; Goldman-Segall, 1998; Hmelo-Silver, 2004; Lemke, 1990; Vygotsky,
1930/1978).
·
Activity
Theory. Human understanding is mediated not only by physical and symbolic
artifacts, but also by the social division of labor and cultural practices (Engeström, 1999; Gay
& Bennington, 1999; Kaptelinin, 1996; Nardi, 1996a; Nardi, 1996b).
·
Ethnomethodology.
Human understanding, inter-personal relationships and social structures are
achieved and reproduced interactionally (Dourish, 2001;
Garfinkel, 1967; Hall, 1999; Heritage, 1984; Koschmann & LeBaron, 2003;
Stahl, 2002b; Streeck, 1996; Streeck & Mehus, 2003).
One does not have to commit to one of these theories in
particular in order to gain a sense from them of the possible nature of group
knowledge. We have selected a working hypothesis that is in line with these
theories in general without opting for one specifically. Based on our previous
empirical work, we believe that we can study the issues raised by these
theories without circularity by structuring collaborative activities, varying
their parameters and critically evaluating the results. By reflecting on the
theoretical issues within our work, we believe we can avoid the pitfalls of
theory-laden research without claiming unattainable value neutrality.
We previously conducted a pilot study involving a group of
five middle school students collaborating on a problem involving data from a
computer simulation. Like many studies of collaborative learning (e.g., Hmelo-Silver,
2004; Koschmann & LeBaron, 2003) (but unlike the new study),
this one involved face-to-face interaction with an adult mentor present. Close
analysis of student utterances during an intense interaction suggested that the
group developed an understanding that certainly could not be attributed to the
utterances of any one student (Stahl, 2002b). In fact, the utterances
themselves were meaningless if taken in isolation from the discourse and its
activity context.
There were a number of limitations to the pilot study: (1)
Although the mentor was quiet for the specific interaction analyzed, it might
be possible to attribute something of the group knowledge to the mentor’s
guiding presence. (2) The digital videotape was limited in capturing gaze and
even some wording. (3) The data included only two sessions, too little to draw
conclusions about how much individual students understood of the group
knowledge before, during or after the interaction. To overcome such
limitations, in our current study: (1) Mentors are not active in the
collaborative groups – although the group will work on problems that have been
carefully crafted to guide student inquiry and advice can be requested by email
from Math Forum staff. (2) The online communication is fully logged, so that
researchers have a record of the complete problem-solving interaction. (3)
Groups will be studied over a period of a couple weeks – and longer for several
groups that work on a sequence of problems.
Despite its limitations, the pilot study clearly suggests
the feasibility of studying group knowledge. It shows that group knowledge is
constructed in discourse and that discourse analysis can “make visible” that
knowledge to researchers. Student discourse is increasingly recognized as of
central importance to science and math learning (Atkins, 1999; Bauersfeld,
1995; Lemke, 1990; Schifter, 1996). Discourse analysis is a
rigorous human science, going under various names: conversation analysis,
interaction analysis, micro-ethnography, ethnomethodology (Coulthard, 1977;
Duranti, 1998; Garfinkel, 1967; Heritage, 1984; Jordan & Henderson, 1995;
Mehan, 1979; Sacks, 1992; Sinclair & Coulthard, 1975; Streeck & Mehus,
2003).
The focus on discourse suggests a solution to the confusion
between individual and group knowledge, and to the conceptual conflict about
how there can be such a thing as group knowledge distinct from what is in the
minds of individual group members (Stahl, 2003a). One way of putting it is
that meaning is constructed in the group discourse. The status of this meaning
as shared by the group members is itself something that must be continually
achieved in the group interaction; frequently the shared status “breaks down”
and a “repair” is necessary. In the pilot study, the interaction of interest
centered on precisely such a repair of a breakdown in shared understanding
among the discussants (Stahl, 2002b). While meaning inheres in the discourse, the individual group members must
construct their own interpretation of
that meaning in an on-going way. Clearly, there are intimate relationships
between the meanings and their interpretations, including the interpretation by
one member of interpretations of other members. But it is also true that
language can convey meanings that transcend the understandings of the speakers
and hearers. It may be precisely through divergences among different
interpretations or among various connotations of meaning that collaboration
gains much of its creative power (Stahl, 2003b). These are questions that we
will investigate as part of our micro-analytic studies of collaboration data,
guided by our central working hypothesis. We believe that such an approach can
maintain a focus on the ultimate potential in CSCL, rather than losing sight of
the central phenomena of collaboration as a result of methods that focus
exclusively on statistical trends (Stahl, 2002a).
Collaborative success is hard to achieve and probably
impossible to predict. CSCL represents a concerted attempt to overcome some of
the barriers to collaborative success, like the difficulty of everyone in a
group effectively communicating their ideas to all the other members, the
complexity of keeping track of all the inter-connected ideas that have been
offered or the barriers to working with people who are geographically distant.
As appealing as the introduction of technological aids for communication,
computation and memory seem, they inevitably introduce new problems, changing
the social interactions, tasks and physical environment. Accordingly, CSCL
study and design must take into careful consideration the social composition of
groups, the collaborative activities and the technological supports.
In order to observe effective collaboration in an authentic
educational setting, we are adapting a successful math education service to
create conditions that will likely be favorable to the kind of interactions
that we want to study. We must bring together groups of people who will work
together well, both by getting along with and understanding each other and by
contributing a healthy mix of different skills. We must also carefully design
mathematics curriculum packages that lend themselves to the development and
display of deep math understanding through collaborative interactions –
open-ended problems that will not be solved by one individual but that the
group can chew on for a week or two of online interaction. Further, the
technology that we provide to our groups must be easy to use from the start,
while meeting the communicative and representational needs of the activities.
As part of our project, we will study how to accomplish these group formation,
curriculum design and technology implementation requirements. This is expressed
in three working hypotheses of the project: H1, H2 and H3. Two further working
hypotheses define areas of knowledge building that the project itself will
engage in on the basis of our findings. H4 draws conclusions about the
interplay between group and individual knowledge, mediated by physical and
symbolic artifacts that embody knowledge in persistent forms. H5 reports on the
analytic methodology that emerges from the project:
·
H1 (collaborative
group hypothesis): Small groups are most effective at building knowledge if
members share interests but bring to bear diverse backgrounds and perspectives.
·
H2 (collaborative
curriculum hypothesis): Educational activities can be designed to encourage
and structure effective collaborative learning by presenting open-ended
problems requiring shared deep understanding.
·
H3 (collaborative
technology hypothesis): Online computer support environments can be
designed to facilitate effective collaborative learning that overcomes
limitations of face-to-face communication.
·
H4 (collaborative
cognition hypothesis): Members of collaborative small groups can
internalize group knowledge as their own individual knowledge and they can
externalize it in persistent artifacts.
· H5 (collaborative methodology hypothesis): Quantitative and qualitative analysis and interpretation of interaction logs can make visible to researchers the online learning of small groups and individuals.
Gerry Stahl, College
of Information Science and Technology, Drexel University, Philadelphia, USA, Gerry.Stahl@drexel.edu.
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