Aalst Jan van, Distinguishing knowledge-sharing, knowledge-construction, and knowledge-creation discourses (2009).pdf

Computer-Supported Collaborative Learning (2009) 4:259 – 287

DOI 10.1007/s11412-009-9069-5

Distinguishing knowledge-sharing, knowledge-

construction, and knowledge-creation discourses

Jan van Aalst

Received: 11 September 2008 /Accepted: 28 May 2009 / Published online: 20 June 2009

# The Author(s) 2009. This article is published with open access at Springerlink.com

knowledge-creation model. Distinctions were set up between three modes of discourse:

knowledge sharing, knowledge construction, and knowledge creation. These were applied to

the asynchronous online discourses of four groups of secondary school students (40 students

in total) who studied aspects of an outbreak of Severe Acute Respiratory Syndrome (SARS)

and related topics. The participants completed a pretest of relevant knowledge and a

collaborative summary note in Knowledge Forum, in which they self-assessed their collective

knowledge advances. A coding scheme was then developed and applied to the group

discourses to obtain a possible explanation of the between-group differences in the

performance of the summary notes and examine the discourses as examples of the three

modes. The findings indicate that the group with the best summary note was involved in a

threshold knowledge-creation discourse. Of the other groups, one engaged in a knowledge-

sharing discourse and the discourses of other two groups were hybrids of all three modes.

Several strategies for cultivating knowledge-creation discourse are proposed.

’

Keywords Knowledge sharing . Constructivism . Knowledge building .

Knowledge creation . Argumentation

Introduction

For two decades, Carl Bereiter and Marlene Scardamalia have been developing an educational

model intended to make the processes experts use to advance the state of knowledge in their fields

more common in education. The model was initially called

“

intentional learning

”

suggesting that knowledge is the product of

a constructive process (Bereiter and Scardamalia 1993 ). But as constructivism has gained wide

“

knowledge building,

”

J. van Aalst ( * )

Faculty of Education, The University of Hong Kong, 323 Runme Shaw Building, Pokfulam Road,

Hong Kong, SAR, China

e-mail: vanaalst@hkucc.hku.hk

Abstract The study reported here sought to obtain the clear articulation of asynchronous

computer-mediated discourse needed for Carl Bereiter and Marlene Scardamalia

to emphasize

that learning needs to be an intended goal rather than the by-product of activities (Bereiter and

Scardamalia 1989 )andthen

260

J. van Aalst

acceptance in education, it has become difficult to distinguish knowledge building from

constructivist learning, and Bereiter and Scardamalia have begun to favor the term

“

knowledge

which is well established in the literature on innovation (Gundling 2000 ; Nonaka and

Takeuchi 1995 ). 1 The term refers to a set of social practices that advance the state of

knowledge within a community over time (Paavola et al. 2004 ). Knowledge creation involves

more than the creation of a new idea; it requires discourse (talk, writing, and other actions) to

determine the limits of knowledge in the community, set goals, investigate problems, promote

the impact of new ideas, and evaluate whether the state of knowledge in the community is

advancing. To support this discourse, Scardamalia and colleagues have developed a Web-based

environment, Knowledge Forum® (Scardamalia 2003 ), which includes tools for asynchronous

problem-solving interactions, idea development, synthesis, and refection.

The integration of computer-mediated asynchronous discourse into classroom practice

needs to be addressed if educational models such as knowledge creation are to be

implemented widely. My experience of working with many teachers suggests that

participant understanding of the nature of the discourse needed for knowledge creation is

crucial for such integration (van Aalst 2006 ). The goal of the study reported here was to

obtain a clearer articulation of the online discourse needed for knowledge creation.

To this end, I distinguish three modes of discourse

”

knowledge sharing, knowledge

construction, and knowledge creation — which correspond to three established theoretical

perspectives. Knowledge sharing refers to a transmission theory of communication (see Pea

1994 ), knowledge construction to cognitive psychology (constructivism), and knowledge

creation to interactive learning mediated by shared objects (Paavola et al. 2004 ). This

division extends the cognitively oriented distinction between knowledge-telling and

knowledge-construction models of writing (Bereiter and Scardamalia 1987 ) in light of

recent theoretical developments that posit cognition as being situated in authentic situations

and practices (Brown et al. 1989 ; Hutchins 1995 ; Lave and Wenger 1991 ). The distinctions

are then applied to the analysis of a Knowledge Forum database.

The remainder of this paper is organized as follows. The next two sections describe the three

modes of discourse and their theoretical underpinnings, and provide a brief introduction to

Knowledge Forum. A case study is then presented, covering the collaboration of four large

student groups that investigated aspects of Severe Acute Respiratory Syndrome (SARS), Avian

Flu, and related topics. The case first examines evidence of collective knowledge advancement

within the groups, and then examines the nature of each group

—

s discourse in Knowledge Forum

using a newly developed coding scheme. The analysis of the group discourses is matched to

both the evidence of collective knowledge advancement and the three modes of discourse.

Ways to encourage knowledge-creation discourse are then discussed.

’

Knowledge sharing, knowledge construction, and knowledge creation

Knowledge sharing

Knowledge sharing refers to the transmission of knowledge between people. Strictly

speaking, only information can be transmitted; information is knowledge for the sender and

s earlier work as part of a

continuous line of research and refer to their model as “ knowledge creation ” throughout, although it is not a

term they have used in their published work.

’

creation,

1 Private communication, August 8, 2008. The shift in terminology makes the discussion of earlier

contributions difficult. In this paper, I consider Bereiter and Scardamalia

Computer-Supported Collaborative Learning

261

receiver if they comprehend its content and significance. Examples are providing factual

information to answer a query or uploading various kinds of information to an intranet. One

thing that makes such interactions effective is that the receiver has already identified a need

for the information. For example, someone new to editing digital video may need to be

shown how to add music to the video, which will address an already meaningful goal.

As a social practice, knowledge sharing is an accomplishment, especially in competitive

environments; people are not naturally inclined to share what they know unless doing so is

likely to enhance their own social position. The management literature indicates that

knowledge-sharing practices can make organizations more effective, but they need to be

cultivated (Lencioni 2002 ). In a community engaged in collaborative inquiry, knowledge-

sharing practices involve the introduction of information and ideas without paying

extensive attention to their interpretation, evaluation, and development. The perceived lack

of a need for interpretation and evaluation can be related to naïve realism, an epistemic

position according to which data speak for themselves (Science Council of Canada 1984 ).

A related epistemic belief is

“

quick learning,

”

Knowledge construction

Knowledge construction refers to the processes by which students solve problems and

construct understanding of concepts, phenomena, and situations, considered within

cognitive psychology. It is effortful, situated, and reflective, and can be individual or

social (Sullivan Palincsar 1998 ). The basic assumption of constructivism is that the student

must make ideas meaningful in relation to his or her prior knowledge and to the situation in

which the need for ideas arises (von Glasersfeld 1995 ). The cognitive processes are

“

“ qualitative changes in the complexity of students ’

thinking about and

(Moore 2002 , p. 27; also see Biggs

1987 ). Dole and Sinatra ( 1998 ) conceptualize the effort students invest in information

processing as

”

ranging from simple processing that leads to assimilation

(low), to deeper processing and some reflection that leads to knowledge restructuring

(moderate), and on to substantially metacognitive processing (high).

At moderate to high levels of engagement, knowledge construction can lead to the

substantial restructuring of knowledge, which may include the invention of new concepts

and enhanced meta-conceptual knowledge (e.g., knowledge about the hierarchical nature of

networks of concepts). For example, students may initially consider the motion of an apple

that falls from a tree to be unrelated to the motion of the earth in its orbit around the sun,

but then come to realize that both can be described using the universal law of gravitation.

This change would imply deeper insight into the nature of gravity and would lead to a

restructuring of knowledge; the resulting knowledge structure would explain a greater range

of observations and require fewer assumptions. More generally, synthesis that results in

understanding phenomena on a higher plane and the creation of new concepts is an

important form of knowledge advancement. For example, Mendeleev

“

engagement,

”

s introduction of the

periodic table of the elements accelerated progress in chemistry by predicting the existence

of unobserved elements and the creation of new concepts to explain the partially observed

patterns. Scardamalia ( 2002 ) conceptualizes such advances as

’

“

rise-above,

”

which she

which has been linked to overconfidence in

knowledge (Schommer 1990 ). The ideas shared are not modified by the sharing interaction

(Bereiter and Scardamalia 1987 ; Pea 1994 ), and knowledge sharing is not reflective.

because they are mediated (enabled) by social interactions within the particular

group that is working together and by the particular technologies used (Brown et al. 1989 ;

Hutchins 1995 ). Knowledge construction is often associated with deep learning, which

involves

situated

”

conceptualization of context-specific subject matter

262

J. van Aalst

(p. 79). Although Scardamalia proposes rise-above as a knowledge-creation

principle, I regard it as a cognitive act whereby students articulate higher levels of

understanding and not merely reorganize knowledge (Gil-Perez et al. 2002 ); nevertheless,

the need for rise-above is greater when the need for synthesis is greater.

Knowledge construction involves a range of cognitive processes, including the use of

explanation-seeking questions and problems, interpreting and evaluating new information,

sharing, critiquing, and testing ideas at different levels (e.g., conjectures versus explanations

that refer to concepts and/or causal mechanisms), and efforts to rise above current levels of

explanation, including summarization, synthesis, and the creation of new concepts.

However, educational approaches vary considerably in the extent to which they make it

possible for students to engage in these processes. Although most emphasize working with

information and ideas (e.g. Goldberg and Bendall 1995 ; Hunt and Minstrell 1996 ; Linn

et al. 2003 ), there may be limited opportunities for students to pursue problems they have

identified themselves or to synthesize ideas and formulate new concepts. For example, in

problem-based learning (Hmelo-Silver and Barrows 2008 ), students are provided problems,

although these are ill-structured and need considerable articulation. In other approaches,

students may collaborate in small groups on relatively simple tasks that require little

synthesis and reflection on progress. In the vast majority of approaches, knowledge-

construction processes are directed at acquiring the reliable knowledge of a field (Edelson

et al. 1999 ; Kolodner et al. 2003 ; Krajcik et al. 2008 ). Knowledge construction, with its

emphasis on building on students ’ prior ideas, concepts and explanations, and their

metacognition, produces deeper knowledge in complex domains than does knowledge

sharing (Bransford et al. 1999 ; Hmelo-Silver et al. 2007 ).

”

Knowledge creation

is used in the literature on expertise and innovation to describe

how companies, organizations, and academic fields develop the ideas needed to sustain

innovation (e.g. Engeström 2001 ;Gundling 2000 ; Nonaka and Takeuchi 1995 ). Knowledge

creation depends on conditions in which creative work on ideas is valued and there are

mechanisms for choosing the most promising ideas for further development, and rewarding

creativity. These elements need to work together to create what Gundling ( 2000 ) has called an

“

knowledge creation

”

(p. 14).

At one level, knowledge-creation discourse involves the design and improvement of

intellectual artifacts such as theories, explanations, and proofs (Bereiter 2002 ). Drawing

from Popper

”

that produces

“

a dazzling variety of new products each year

”

s theory of objective knowledge, Bereiter considers ideas to be real objects

similar to bicycles or telephones. We may ask how a bicycle can be improved, and we can

ask the same of an idea. This aspect of the discourse is known as

’

(Bereiter

and Scardamalia 2003 ), with an emphasis on explanations, casual mechanisms, and the

coordination of claims and evidence.

However, knowledge creation is not just a rational effort. For example, the community

periodically needs discourse to identify priorities and long-term goals, decide how to

mentor newcomers, and evaluate knowledge advances. As studies of scientific practice

have shown, the associated discourse tends to be more argumentative (Feyerabend 1975 ;

Kuhn 1970 ; Lakatos 1970 ; Latour 1987 ). To mention just a few examples, in science, good

“

design-mode

”

described as “ working toward more inclusive principles and higher-level formulations of

problems. It means learning to work with diversity, complexity and messiness, and out of

that achieve new syntheses. By moving to higher planes of understanding knowledge

[creators] transcend trivialities and oversimplifications and move beyond current best

practices

The term

ecology of innovation

Computer-Supported Collaborative Learning

263

s reluctance to make public the health hazards

associated with radium, see Quinn 1995 ). In other words, belief-mode discourse also plays

an important role in knowledge creation. Despite individual idiosyncrasies, members of a

scientific field share a goal of innovation and the advancement of knowledge. Commitment

to shared goals within a team is also important in a variety of other innovative contexts

(Gundling 2000 ; Lencioni 2002 ; Nonaka and Takeuchi 1995 ).

In Bereiter and Scardamalia

’

s knowledge-creation model (Bereiter 2002 ; Bereiter and

Scardamalia 1996 ; Scardamalia 2002 ; Scardamalia and Bereiter 2006 ), a class of students is

considered a community that shares a commitment to creative work on ideas and advancement

of the state of knowledge in that community. Ideas are considered intellectual artifacts of the

community; they reside in the community

’

s minds. The

community needs to be able to identify gaps in its collective knowledge, map out ways to fill

those gaps, design and manage inquiries, manage social processes, and evaluate progress.

Thus, the community

s discourse rather than in people

’

constructive use of

authoritative sources ” (Scardamalia 2002 ) such as books, websites, and experiments, treating

them as potentially useful for informing their work. They are also expected to engage in

progressive problem solving, reinvesting cognitive resources to deepen their understanding of

problems and taking on more difficult problems over time (Bereiter and Scardamalia 1993 ).

One of the most important roles of the teacher in this process is to facilitate the development of

an innovation ecology. Important progress has been made in this direction by the development

of a system of principles that describe the socio-cognitive and socio-technological dynamics of

knowledge creation, including collective cognitive responsibility for knowledge advancement,

real ideas/authentic problems, epistemic agency, improvable ideas, rise-above, and constructive

use of authoritative sources (Scardamalia 2002 ). These principles provide a technical

vocabulary that students, teachers, and researchers can use to reflect on the extent to which

there is evidence of a knowledge-creation discourse. Initial studies show that elementary and

secondary school students are capable of engaging in the dynamics described by these

principles (Niu and van Aalst in press ; Zhang et al. 2007 , 2009 ). However, more work is

needed to characterize the innovation ecology, such as by determining the social practices that

make collaboration possible, the overall school culture, and the community ’ s experience at

knowledge creation and its long-term goals (Bielaczyc 2006 ;Truong 2008 ). Knowledge

creation requires discourse for maintaining social relations, setting goals, deepening inquiry,

and lending support to ideas that are already understood by some in the community. For

example, van Aalst ( 2006 ) discusses how a Grade 6 student referred to the scientist Francis

Bacon to support an explanation he had proposed earlier that had not been accepted by the

community. This move was directed less at improving understanding than at improving the

impact of the student ’ s own ideas. Similarly, students who wish to further a line of inquiry need

the ability to argue the case for doing so. These types of moves cannot be understood by

examining short-term goals such as the problem students are currently attempting to

understand, but require the consideration of higher level and longer term goals such as the

diffusion of new insight throughout the community and progressive problem solving (Hmelo-

Silver 2003 ). In groups that work together for short periods, there is less need for such moves.

There are important theoretical differences between knowledge construction and

knowledge creation, although they involve similar processes such as posing questions,

formulating conjectures and explanations, summarizing progress, and proposing rise-above

s goals are emergent. Students are expected to make

“

problems may not be investigated because they are not currently considered important

(Latour 1987 ). Researchers promote their own work and that of close colleagues by alerting

the community to recent findings, and may ignore important new findings that they do not

find appealing (Reeves 2008 ). Other researchers may not make their insights public, for fear

of attracting criticism (e.g., Madame Curie

’

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