ONLINE COLLABORATIVE LEARNING
Marc Bélanger
Online Collaborative Learning
Even if not made explicit, all views of education are grounded in basic questions
such as: What is knowledge? What is true? What is false? How do we gain knowledge?
Posing these sorts of questions and attempting answers is the study of epistemology, the
theory of knowledge, that “branch of philosophy that deals with questions concerning the
nature, scope, and sources of knowledge” (DeRose, 2004). Difficult as it may be to
answer questions such as these, it is important that we try because: “The way we teach in
higher education will be driven primarily by our beliefs or by the commonly agreed
consensus within an academic discipline about what constitutes valid knowledge in the
subject area.” (Bates and Poole, 2003, p. 26). This means that for online educators our
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choice of teaching methods – how we do what we do – is founded in the theory of
knowledge we believe to be the most valid for our purposes.
The two dominant epistemological positions in North American higher education
today are objectivism and constructivism (Bates and Poole, 2003). Objectivists believe
that there is an objective set of facts, principles and theories that have been discovered or
will be discovered. On the other hand:
Constructivists believe that knowledge is essentially
subjective in nature, constructed from our perceptions
and mutually agreed upon conventions. According to
this view we construct new knowledge rather than
simply acquire it via memorization or through
transmission from those who know to those who do
not know. We construct meaning by assimilating
information, relating it to our existing knowledge and
cognitively processing it, that is, thinking about it.
(Bates and Poole, p. 28).
By adopting the use of one or the other theory (either as a foundational
epistemology for all educational activities or just some) we make decisions concerning
how we design our learning and teaching experiences. For online educators the difference
between the two theories can be most clearly seen by contrasting Online Collaborative
Learning (OCL) with two other delivery modes: Online Distance Education (ODE) and
Online Computer-Based Training (OCGT). ODE refers to individuals using computer
communications to access prepared lesson materials and background resources. Students
read the pre-packaged information and complete assignments which are sent by email to
tutors for grading. It is not much different than traditional distance education which uses
the postal system and telephone access to tutors. OCBT differs from ODE in that learners
make more use of computers as they interact with programs to learn particular skills. In
the design of both ODE and OCBT, objectivist decisions have been made that there is an
existing body of knowledge to be passed on. Online Collaborative Learning adopts a
constructivist orientation which stresses the social interaction in knowledge creation.
OCL can be defined as the use of asynchronous computer communication
networks to provide social spaces for communities to collaboratively participate in the
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construction of knowledge. The epistemologically key phrase in this definition is the last:
the construction of knowledge. OCL participants working within computerized
environments are not empty vessels waiting to be filled. They are active creators of
knowledge. They do this by interacting with the system and working collaboratively with
the instructor and the other participants. Two complementary areas of investigation are
opened by viewing OCL in this way: people learning from the structures in which they
participate and the dynamics related to groups learning together.
Sawchuck et al. (2002) discovered as they were researching online labour
education that they needed a theory of learning. The theory they developed is rooted in
the work of Vygotsky (1978) and Leont'ev (1978). One of Vygotsky's central concepts is
that human action is tool-mediated within structures of participation (Zone of Proximal
Development, ZPD) both linguistic and material. Leont'ev (1978, p. 10) added to this
view by arguing that the structures within which a person interacts “...bear within
themselves the motives and goals of his activity, its means and modes.” Sawchuck et al.
(2002) concluded that:
…the pertinence of ZPD and the concept of
activity is that it allows us to understand learning as
more than simply an information or knowledge
exchange: learners actively construct knowledge
together through tool-mediated participation (p. 84)
The second avenue of investigation relates to how the groups which are within the
structures of participation work together to create knowledge. This investigation is rooted
in the works of Johnson and Johnson (1975), Bouton and Garth (1983) and Bruffee
(1993). In Bruffee's view people re-acculturate themselves from the knowledge
communities they are part of and work collaboratively with other people in transitional
communities to gain membership to another knowledge community (Bruffee, 1993, p.
20). A key element in this is writing, which “...lies at the centre of collaborative learning
as one of the most important elements in the craft of interdependence.” (Bruffee, 1993, p.
52). Writing is, of course, the central activity of educational computer conferencing - the
participants have no presence in the conference unless they write comments. It is the
fundamental building block of online collaborative work.
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The two areas of investigation – the structures of participation and collaborative
learning dynamics – are especially relevant to the use of OCL in designing educational
experiences. This is because of the binary nature of online collaborative learning: online
refers to the computer hardware and software; collaborative learning refers to the
andragogies. Both need to be considered if OCL is to design effective education.
Turoff (1995) has argued that “we can use the powers of the computer to actually
do better than what normally occurs in the face to face class.” We can use the computer to
store, search and display participant writings in ways that make them a resource to be
consulted, quoted and built upon. Collaborative learning could be powerfully enhanced
by designing computer systems which promote it. Some systems have been designed
with this view in mind, for example, the Virtual Classroom (Turoff, 1995) and Virtual U
(Harasim et al., 1995).
However, in keeping with the views put forth by Vygotsky, Leont'ev, Sawchuck et
al. that activities within structures of participation affect those within them, it should be
recognized that the systems themselves educate. Even before a participant writes the first
comment, learning is in progress. If the system is poorly designed or a prototype, then the
lesson may be that computer conferencing is difficult and frustrating. On the other hand,
if the system is intuitively easy to work with, the student may not even notice it but will
move on quickly to interaction with other users. In this case, the lesson is that online
learning can be enjoyable and productive. Either way, the participant will be affected by
the system and the people who designed it.
The second area of investigation, the dynamics of collaborative learning, is
equally important when considering the design of an educational computer conferencing
system. Turoff has concentrated on designing software which promotes collaborative
learning with facilities such as question and answer procedures (which force a student to
answer an instructor's question before they can enter a conference to see the answers of
other students), commonly editable areas, and pen names which can be adopted for role
playing (Turoff, 1995). Harasim has worked at the boundary of technical design and
collaborative learning andragogy by designing different virtual educational spaces, each
with specific functions and characteristics (Harasim, 1987; 1990; Harasim et al., 1995).
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This design work allows both formal and informal learning. While the system may
be used with students in academic settings (Hiltz, 1997; Hislop, 1999; Graham et al.,
1999; Picciano, 2002; Shea et al., 2000) it can also be used for informal learning. For
example, Virtual U was used by participants of the Global Educators Network, a
community of educators who came together to discuss common issues (Harasim, 2002). It
was also used for a series of informal seminars by labour activists in the mid-1990s
(Sawchuck et al., 2002).
Still, the technical system is inconsequential until it becomes populated, until
people begin using it for educational purposes. Here again, the theory of knowledge
which is adopted is crucial. If the andragogy is objectivist, the system, even if it is
designed for collaborative learning, can be used to simply provide a lecture space for
instructors or be used as a rote-memorization training system. A constructivist approach,
however, has been shown to be more effective in promoting online education. It can equal
or improve on the learning outcomes of classroom-based learning (Hiltz, 1997). It can
enhance critical thinking skills (Gokhale, 2002). It can improve in-depth investigation and
development of a topic (Harasim,1990), and it can help students retain the information
being learned longer (Hafner and Ellis, 2004). This is all assuming, of course, that it is
implemented correctly.
Fortunately, there is a rich and growing literature describing how collaborative
learning can be implemented successfully (Harasim et al., 1995; Khan, 1997; Beaudin,
1999; Rossman, 1999; Schrum and Hong, 2002; Achtemeir et al., 2003). The key appears
to be preparation by the instructor in scheduling collaborative learning events throughout
the experience (Hiltz, 1997) including projects for co-production (Harasim, 2002).
Suggestions for success include the use of collaborative learning activities such as
debates, group projects, role-playing, and collaborative essays (Harasim et al., 1995). The
first week or so is crucial as the participants must learn to quickly trust the community
they are joining (Coppola et al., 2004). Participants should be coached in simple activities
at first and then gradually, as support is removed, left to work on their own (Wegerif,
1998).
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The role of the instructor is important to the success of a collaborative learning
course. The instructor's role becomes to observe, monitor, facilitate and provide
information (Harasim et al., 1995; Teles et al., 2001). This is a significantly different role
than that of the traditional university lecturer. It demands more interaction with the
participants, but this can improve chances of successful education. Studies have shown
that the students who reported the highest levels of interaction with the instructor also
reported the highest levels of satisfaction and learning in an online course (Shea et al.,
2000).
A potential problem for expanding the use of collaborative learning to informal
education is that much of the current literature is based on studies involving students in
graded environments. Hiltz (1997) has noted that students must be told they are being
graded to make them participate effectively in collaborative learning exercises. There is a
need to verify if other factors, such as feelings of community and co-production, can
substitute for grading systems. Some indications exist that this is possible. An example is
the Global Authors Network (GAN) of the early 1990s which produced a book, “Global
Networks: Computers and International Communication” (Harasim, 1993). The key in
this case was to focus the participants on a common project, the book (Harasim and Wall
1993). Another example is the Global Educators Network which connected educators
from all over the word (Harasim, 2002). Its participants did not work on a common task
yet built a community of learners. The factor leading to success in this case may have
been the fostering of feelings of community. There is a need for more sound research to
better understand how non-graded collaborative learning can be successful.
One of the criticisms of research into online education is that it often does not
include a theoretical or conceptual framework (Phipps, Merisotis and O'Brian, 1999). A
theoretical framework can help focus and guide research plus discover hypotheses which
are open to empirical testing or to provide for the qualitative exploration of a subject To
be effective it needs a comprehensive and coordinated set of indicators of success
(Marshall and Rossman, 1999; Palys, 2003).
Meyer (2004) studied four different “frames” in analyzing 17 online discussions in
two doctoral-level classes in educational leadership. The frames were: King and
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Kitchener's reflective judgment model; Perry's model of intellectual and ethical
development; Garrison's four stage critical thinking model; and Bloom's taxonomy of
education activities. Meyer concluded that each frame has value, as each focuses attention
on a particular aspect or quality. Consequently, investigators may need to use different
frames to suit different situations (Meyer, 2004). In order to do this what is needed is a
preliminary set of criteria which should be met by the application of a particular
framework. The following are criteria for a framework which would work for
investigating informal, non-graded OCL:
based on the concept of the social construction of knowledge;
investigates online collaborative learning;
provides a comprehensive theory for better understanding group learning online;
recognizes community building as an essential ingredient of online learning;
is not necessarily geared to credit-granting courses.
The application of these criteria to the four frameworks studied by Meyer suggest
that none of them are appropriate for informal OCL learning such as might be found in
communities like the labour movement. First, they all are concerned with credit-granting
post-secondary environments. Secondly, they lack a focus on the dynamics of online
group learning: one of Meyer's conclusions was that there was a need for frameworks
other than those she studied, including one which provides “a way to assess how a group
conversing online works as a group, how it works together to develop an understanding of
and solutions to a problem.” (Meyer, 2004).
A framework which better meets the criteria is Harasim's (1990; 2002; 2004). It
accepts the idea of discourse as central to knowledge-building and views learning as a
social, negotiated, consensual process. It was created to help improve the understanding
of learning effectiveness in online environments. It contains a set of tools by which we
can understand “how and under what circumstances collaboration and discourse
contribute to learning.” It recognizes “the processes of democratic participation,
intellectual progress and gradual convergence to adumbrate the trajectory of online
learning ...” (Harasim, 2002).
Since the framework's first exposition (Harasim, 1990) it has become informed by
experience with the Global Authors Network and the Global Educators Network. By
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proposing ways of studying online learning by people in a non-credit environment the
framework may meet the needs of researchers investigating the use OCL by informal
learning communities.
Harasim's framework stipulates three phases and provides indicators for each.
Phase 1: Idea generating. Indicators include verbalization, brainstorming,
information generating and democratic participation.
Phase 2: Idea linking. Indicators include an increased number of replies,
references to other messages and a qualitative change in the nature of the
discourse.
Phase 3 Intellectual Convergence. Indicators include an increased number of
substantive contributions and more conclusive statements supported by the group.
This framework could meet Meyer's call for a theory which shows how “a group
online works together to develop an understanding of and solutions to a problem.”
(Meyer, 2004)
Another factor which may need investigation if informal OCL is to be successful
is how a sense of community is built online. Feelings of community may substitute for
grading as a way to encourage people to participate in collaborative learning exercises.
Rovai's Classroom Community Scale (Rovai, 2001; 2002a; 2002b) could help here. The
scale measures the sense of community in an online group so that sense can be
encouraged and fostered. “The CSS consists of 20 questions: 10 items related to feelings
of connectedness and 10 items related to feelings regarding the use of interaction within
the community to construct understanding and the extent to which learning goals are
being satisfied within the classroom setting.” (Rovai, 2002a). By applying it at various
times in an online experience, investigators could measure if the sense of community
grows or if it is related to particular events in the experience. A potentially valuable
project might be to correlate data collected during an analysis of an OCL experience
using Harasim's theory and findings which result from the application of Rovai's CSS. A
significant research question could be: Does intellectual convergence occur more often as
the sense of community develops?
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Data collection for researching online activity involves analyzing messages,
checking system statistics such as logon times and durations, using online questionnaires
and conducting online interviews. If the participants are available in person, then
interviews, group meetings (and the recording of those events) can be used. The problem
is not usually a lack of data, but how to manage the analysis of a body of data. By using a
comprehensive theory of learning such as Harasim's , which includes clear indicators, and
applying tested instruments such as Rovai's CSS, data can be collected and analyzed
systematically. The theory is especially important because it allows the large amount of
data to be categorized and therefore makes analysis of the whole experience possible.
Once a theory is chosen the researcher needs to decide how to proceed in coding
the data in the search for evidence of the indicators. Again, the problem is often too much
data. Methods have to be found to allow investigators to analyze the data without getting
lost in it all. Campos (2004) has developed a method which “enables the assessment of
conceptual change, collaborative learning and knowledge-building through the study of
networked cognitive communication.” Its unit of analysis is the sentence. Since one
computer conference, never mind a collection, could consist of thousands of sentences,
the sheer amount of data could be overwhelming. Campos himself admits the application
of his method is difficult and he is considering the use of “some kind of partial automatic
procedure in the future” (Campos, 2004, p. 26). The alternative to the sentence as a unit
of analysis is the message, but there again the problem is that one message may contain
numerous instances of indicators. The traditional response to the workload this presents
has been to assign one indicator per message. The disadvantage of this procedure is that it
may result in enough missed indicators to seriously mar the study.
Anderson et al. (2001) have developed a method which might bridge the gap
between too small a unit (the sentence) and too broad a coding system (one indicator per
message). They allowed for the assignment of multiple indicators to each message:
In the present study we again used the message unit.
However, rather than simply assigning each message
unit that demonstrated some sort of teaching presence
to one and only one of the categories of teaching
presence, we allowed for the possibility that a single
message might exhibit characteristics of more than
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one category. Therefore, each message posted by the
instructor was coded as exhibiting or not exhibiting
one or more indicators of each of the three categories
of teaching presence. (Anderson et al., 2001)
The advantages of this procedure included: lessening the workload of the coders
by pre-determining the number of coding decisions (three decisions per message); quick
implementation; and meaningful expression by reporting the percentage of total posting
that contained each of the categories. “We feel that the procedure is reliable, efficient and
practical” (Anderson et al., 2001)
This method could prove valuable when working with a theory that precisely
defines its indicators, such as Harasim's. Analysis of a conference, or conferences, could
code messages according to Harasim's three phases – idea collection, idea linking and
intellectual convergence.
In conclusion: this paper has discussed OCL as an epistemology which can be
used to frame OCL educational design, implementation and research. It has provided a
definition of OCL which differentiates it from Online Distance Education and Online
Computer-Based Training. It has also discussed a particular theory which could be used
in the investigation of OCL in informal fields such as labour education. Finally, it has
described how data could be collected and analyzed in light of that theory.
References
Achtemeir, S.D., Morris, L.V. and Finnegan, C. L. (2003). Considerations for developing
evaluations of online courses. In Journal of Asynchronous Learning, 7(1).
Anderson, T., Rourke, L., Garrison, R.D. and Archer, W. (2001). Assessing teaching in a
computer conferencing context. In Journal of Asynchronous Learning Networks,
5(2)
Bates A.W. and Poole, G. (2003). Effective teaching with technology in higher education.
San Francisco: Jossey-Bass.
Beaudin, B.P. (1999). Keeping online asynchronous discussions on topic. In Journal of
Asynchronous Learning Networks. Vol. 3, Issue 2, November.
Benbunan-Fich, R. and Hiltz, S.R. (1999). Impacts of asynchronous learning networks on
individual and group problem-solving: A field experiment. (pp. 409-426). In
Group Decision and Negotiation. Dordrecht: Kluwer Academic Publishers.
10
Bouton, C. and Garth, R. (1983). Learning in groups: New directions for teaching and
learning. San Francisco: Jossey-Bass.
Bruffee, K. A. (1993). Collaborative learning: Higher education, interdependence and
the authority of knowledge. Baltimore: The Johns Hopkins University Press.
Campos, M. (2004). A Constructivist method for the analysis of networked cognitive
communication and the assessment of collaborative learning and knowledgebuilding. In Journal of Asynchronous Learning Networks, 8(2).
Coppola, N.W., Hiltz, S.R. and Rotter, N. (2004) Building trust in virtual teams. In IEEE
transactions on professional communication. Vol. 47 No. 2, June.
DeRose, K (2004) What is epistemology: A brief introduction to the topic. Available at
http://pantheon.yale.edu/%7Ekd47/What-Is-Epistemology.htm. Accessed
04/10/2004.
Gokhale. A.A. (2002). Collaborative learning enhances critical thinking. Digital library
and archives. http://scholar.lib.vt.edu/ejournals/JTE/jte-v7n1/gokhale.jtev7n1.html. Retrieved 15/09/2004.
Graham, M., Scarborough, H. and Goodwin, C. (1999). Implementing computer-mediated
communication in an undergraduate course – a practical experience. In Journal of
Asynchronous Networks. Vol 3, Issue 1, May.
Hafner, W. and Ellis, T. (2004). Project-based, asynchronous collaborative learning.
Presented at the Proceedings of the 34th Hawaii international conference on
system sciences.
Harasim, L. (2004). Collaboration. In Encyclopedia of Distributed Learning. Thousand
Oaks, California: Sage Publications.
Harasim, L. (2002). What makes online learning communities successful? The role of
collaborative learning in social and intellectual development. In Distance
Education and Distributed Learning (pp. 181-200). Information Age Publishing.
Harasim, L. (2003). The case for collaborative learning online. Keynote presentation to
the Korean Society for Educational Technology, KSET Proceedings, June, 2003.
Harasim, L. (1990). Online education: An environment for collaboration and intellectual
amplification. In L. Harasim (ed.), Online education: Perspectives on a new
environment (pp. 39-64). New York: Praeger.
Harasim, L. (1987). Teaching and learning on-line: Issues in computer-mediated graduate
courses. In Canadian Journal of Educational Communication, 16(2).
Harasim, L., Hiltz, S. R., Teles, L. and Turoff, M. (1995). Learning networks: A field
guide to teaching and learning online. Cambridge, Massachusetts: The MIT
Press.
11
Harasim, L. and Wall, J. (1993). The Global Authoring Network. In L. Harasim (ed.),
Global networks: Computers and international communication (pp. 343-355).
Cambridge, Massachusetts: The MIT Press.
Hiltz, S. R. (1998). Collaborative learning in asynchronous learning networks: Building
learning communities. Invited address presented at the Web98 Conference,
Orlando, Florida, http://eies.njit.edu/~hiltz/collaborative_learning_in_asynch.htm.
Acessed 10/9/2004.
Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks:
Some preliminary results. In Journal of Asynchronous Learning Networks, 1(2).
Hislop, G.W. (1999). Anytime anyplace learning in an online graduate professional
degree program. In Group decision and negotiation 8. Netherlands: Kluwer
Academic Publishers.
Johnson D.W. and Johnson, R.T. (1975). Learning together and alone: Cooperation,
competition, and individualization. Englewood Cliffs, NJ: Prentice Hall.
Johnson-Lenz, P. and Johnson-Lenz, T. (1982). Groupware: The process and impacts of
design choices. In E.B. Kerr and S.R. Hiltz (eds.), Computer-mediated
communication systems: Status and evaluation (pp. 45-56). New York: Academic
Press.
Khan, B. ed. (1997). Web-based instruction. Englewood Cliffs: Educational Technology
Publications.
Leont'ev, A.N. (1978). Activity, consciousness, and personality. Englewood Cliffs, NJ:
Prentice-Hall.
Marshall, C. and Rossman, G. (1999). Designing qualitative research. Thousand Oaks,
California: Sage Publications.
Meyer, K. (2004). Evaluating online discussions: Four different frames of analysis. In
Journal of Asynchronous Learning Networks, 8(2).
Palys, T. (2003). Research decisions: Quantitative and qualitative perspectives.
Scarborough, Ontario: Nelson.
Phipps, R. and Merisotis, J. And O’Brian(1999). What's the difference? A review of
contemporary research on the effectiveness of distance learning in high
education. The Institute for Higher Education Policy.
http://www.ihep.com/Pubs/PDF/Difference.pdf. Accessed 11/09/2004.
Picciano, A. G. (2002). Beyond student perceptions: issues of interaction, presence and
performance in an online course. In Journal of Asynchronous Learning Networks.
Volume 6, issue 1, July.
Rossman, M. (1999). Successful online teaching: Using an asynchronous learner
discussion forum. In Journal of Asynchronous Learning, 3(2).
12
Rovai, A. (2002a). Development of an instrument to measure classroom community. The
Internet and Higher Education, 5, pp.197-211.
Rovai, A. (2002b). A preliminary look at the structural differences of higher education
classroom communities in traditional and ALN courses [Electronic version].
Journal of Asynchronous Learning Networks, 6(1).
Rovai, A. (2001). Building classroom community at a distance: A case study. In
Educational Technology Research and Development, 49(4), pp.33-48.
Sawchuk, P.H., Gawron, Z., and Taylor, J.(2002). E-Learning and Union Mobilization. In
Journal of Distance Education, Vol. 17, No 3, pp. 80-96.
Schrum, L. and Hong, S. (2002). Dimensions and strategies for online success: Voices
from experienced educators. In Journal of Asynchronous Learning, 6(1).
Shea, P., Fredericksen, E., Alexandria Pickett, Peltz, W. and Swan, K. (2000). Measures
of Learning Effectiveness in the SUNY Learning Network. In S. Hiltz (Ed.),
Online education, volume 2, learning effectiveness, faculty satisfaction and cost
effectiveness. Sloan-C Series. http://tlt.suny.edu/ALNWorkshop2000.doc.
Accessed 10/9/2004.
Teles, L., Ashton, S., Roberts T. and Tzoneva, I. (2001). The role of the instructor in elearning Collaborative environments. TechKnowLogia May/June.
Turoff, M. (1995). Designing a virtual classroom. Presented at the International
conference on computer assisted instruction, Hsinchu, Taiwan, March.
Vygotsky, L.S. (1978). Mind in society: The development of higher psychological
processes (M. Cole, Ed.) Cambridge, MA: Harvard University Press.
Wegerif, R. (1998). The social dimension of asynchronous learning networks. In
Journal of Asynchronous Learning Networks. Vol. 2, issue 1, March.
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