Supporting Collaboration in Web–based Problem–based Learning

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Supporting Collaboration in Web–based Problem–based Learning

Key Considerations in Supporting Collaboration for ePBL
Computer-supported Collaborative Argumentation
Computer-supported Knowledge Building

Seng Chee Tan
Chee Kit Looi


Before the mid-1960s, lectures and laboratory practice were the standard approach in medical education for building up students’ knowledge base, especially in the early years of their undergraduate training. In a field that is full of both complex and ill-structured problems, students found this method of learning less interesting and less rewarding than their clinical experiences in later years. This pedagogical approach of learning theoretical knowledge first and applying it later may interfere with the fundamental goals of education (Feltovich et al., 1993). Problem-based learning (PBL) was then introduced to address the inadequacies of traditional instructional approaches (Barrows, 2000).

In contrast to the traditional, discipline-oriented curriculum, PBL uses ill-structured problems or teaching cases as focus to engage students in collaborative and self-directed learning. Students analyze the problems from multiple perspectives and gather and apply knowledge from multiple sources in their quest for solutions. Guided by teachers acting as facilitators, they seek a common understanding of the problem, formulate hypotheses, conduct information searches, perform experiments, formulate and negotiate solutions, and determine the best fit of these solutions to the problem. Among the six principles of effective learning and instruction in PBL set out by Koschmann and colleagues (1996) is the principle of multiplicity, which refers to multiple representations, multiple revisits of concepts and cases, and multiple perspectives. There are two main approaches to achieving multiplicity: one is through the use of multiple cases to allow students to revisit the same concepts in various cases; another is through group interaction in collaborative learning settings. To solve ill-structured problems, identifying and clarifying alternative perspectives is crucial because there could be multiple representations of the problem and its problem states. Conflicting conceptualizations of the problem have to be reconciled and the best plan to solve the problem determined. Thus, collaborative learning is an important element in PBL (Barrows, 2000; Hmelo-Silver, 2004). In PBL, students collaborate on complex problems, distributing the cognitive load among the group members and taking advantage of the distributed expertise within the group (Pea, 1993).

In terms of implementation, in the past, PBL was conducted in face-to-face settings supported with physical resources. In recent years, advances in technology have enhanced the potential of PBL in various ways (Jonassen, 1997). For example, multimedia enables rich contextualized problem cases to be represented realistically and digitally, which means that learners can review the problems many times in an electronic format and scrutinize the problem in its rich context. Modeling tools allow problem solvers to construct different and integrated mental representations of the problem space, a crucial step in linking domain knowledge with the problem. Hypertext allows access to case stories that support the problem-solving process. Likewise, technological advances provide affordances for computer support for communication, collaboration, and joint development of shared artifacts, perspectives, and solutions.

This chapter discusses how technologies could mediate collaboration in ePBL environments. We first walk through a few important questions that we need to ask when considering using technologies to support ePBL. Then we highlight two types of advanced technology for supporting group learning: computer-supported collaborative argumentation (CSCA) and knowledge-building tools. Here we take ePBL to mean the use of technology to augment or support parts or the whole process of PBL, which may be a blended process involving both online and face-to-face collaboration.

Key Considerations in Supporting Collaboration for ePBL

When considering supporting collaboration in an ePBL environment, there are a few key questions to ask. First, what are our goals? What do we want learners to achieve? Second, what exactly are we supporting? In order to answer this question, we need to know what kinds of collaboration are needed in PBL. Next, what kinds of technology can provide such support? Finally, what are the roles of instructors?

What Are Our Goals?

PBL originated in medical education and was designed to anchor the learning of medical knowledge in complex authentic cases with the aim of achieving transfer of learning to real-life problems, in contrast to the traditional approach of using well-defined textbook-type exercises. PBL also focuses on cognitive outcomes rather than material artifacts as in the case of project-based learning. According to Bereiter (1992), when students conduct “research” on certain topics, they would end up accumulating knowledge in a particular field. He refers to the knowledge thus learned as referent-centered knowledge, as it is organized around a certain topic. Bereiter thinks that such learning is defective because, being linked to specific topics, it is not likely to be activated and transferred when the learner is faced with real-life problems. Project-based learning and design-based learning are likely to result in referent-centered knowledge because the end goal is an artifact.

For PBL to be effective, it has to be anchored in the resolution of a complex situation or a perplexing phenomenon. Bereiter calls knowledge learned in this way problem-centered knowledge. We need to recognize that, in PBL, the goal is not simply to arrive at a solution to a complex problem, or to create an artifact, but also to achieve cognitive learning at the level of knowledge and principles so that what is learned can be transferred to other cases and to practice. This has profound implications for what we are supporting in ePBL and the appropriate technologies that can be employed.

What Are We Supporting?

As mentioned earlier in the introduction, PBL is designed for the acquisition of a complex, ill-structured domain of knowledge through collaborative as well as self-directed learning. In this chapter, we use the broad definition of collaborative learning to refer to social learning within a community toward a common goal. One of the key benefits of collaborative work is the deep learning afforded by the multiple perspectives held by various members in the community. In the context of PBL, multiple perspectives could arise for the following reasons:

  • PBL deals with ill-structured problems, which may come with multiple representations. For example, in a real-life problem such as water pollution by industrial discharges, various stakeholders are involved: the government, the environment protection agency, industry, residents living in the vicinity of the river, consumers, and others.
  • There may also be multiple solutions to the problem. Since the various stakeholders may define the problem space differently, working within the frameworks of the different stakeholders is likely to generate different solutions. Even within each stakeholder’s framework, there could be multiple ways of solving the same problem. For instance, a manufacturing plant could either use an alternative method of production or treat the waste differently.

When solving ill-structured problems, learners need to identify and clarify the different perspectives of all the possible stakeholders involved, reconcile conflicting conceptualizations of the problem (Churchman, 1971) and decide on the problem schema that is most relevant and useful for solving the problem (Sinnott, 1989). When there are multiple solutions to the same problem, learners may also need to put forth their arguments to justify their choice of solution. Even when there are no conflicting views, learners could build on and improve the ideas of others. Empowering students to consider multiple perspectives when solving a problem is an important mechanism for developing expertise to cope with authentic problems.

To help establish shared knowledge and interpretations in the PBL process, we need support for grounding. According to Clark (1996), grounding is the process through which shared knowledge is established in interaction. This process is dependent on the participants’ prior beliefs, their previous knowledge, and the material artifacts that are available in any communicative encounter. Studies have indicated that different technological tools provide different constraints and affordances for the grounding process (Baker et al., 1999; Dillenbourg & Traum, 1999). Through social interaction, students’ mental states are articulated and coordinated.

Thus, we are supporting the process of intersubjectivity, where multiple perspectives could be established, grounded, debated, and discussed. The environment should help learners to achieve deeper understanding through constructive and productive discussion. In addition, we could also support idea improvement. Even when learners agree with each other, there is always room to build on and improve ideas put forth in a public space.

Suthers (2005) describes the epistemology of intersubjective learning as going beyond an information-sharing conception of collaborative learning in two ways: it can be about sharing interpretations as well as information, and these interpretations can be jointly created through interaction in addition to being formed by individuals before they are offered to the group. Intersubjectivity is to be understood in a participatory sense and may involve disagreement as well as simple sharing of information (Matusov, 1996). In this epistemology, learning in PBL is not only accomplished through the interactions of the participants but also consists of those interactions (Koschmann et al., 2005).

What Technologies? The Affordances of Technologies

Various computer-mediated communication technologies (CMCs) are available, which one should we use to support collaboration in ePBL and why? As noted earlier, our goal is to achieve shared interpretations and deeper learning of concepts and/or principles, beyond creating an artifact or arriving at a solution. Thus, a CMC that merely facilitates communication may not be sufficient. We have argued that we need to facilitate intersubjectivity and/or improvement of ideas. To match the technology with what we are supporting, we have to understand the affordances of the various technologies. We can analyze CMCs by looking at these aspects: (1) synchronicity versus asynchronicity, (2) structural constraints imposed on the communication, (3) cognitive and metacognitive scaffolding, and (4) a persistent medium to record collaborations for reflection and interpretation.

While synchronous CMCs, such as online chat or videoconferencing, resemble face-to-face communication more than asynchronous CMCs, such as online discussion forums, asynchronous CMCs have the advantage of “slowing down” the discussion (Leeman, 1987), which provides opportunities for reflective and critical thinking. Moreover, everyone can post messages and simultaneously participate in multiple discussions without fear of interruption (Hammond, 1999).

Applications such as Internet relay chat and email do not impose much structural constraint on the process of communication. The messages appear in chronological order, but sometimes it can be puzzling as to which message a particular message is responding to. Threaded discussion forums, on the other hand, impose some structure on the messages posted so that users are aware of the chronological order and some relationships between the messages. Advanced technologies like QuestMap impose more constraints such that relationships between messages can be more accurately specified. This feature can be adopted to scaffold the argumentation structure (e.g., pointing a rebuttal to a claim but not the other way). In essence, such structural constraints are meant to mold the discussion in productive ways with the implicit goal of teaching students how a productive discourse can be constructed. This will be elaborated further when we discuss CSCA.

Beyond imposing structural constraints, such technologies as Knowledge Forum allow instructors (or experts) to provide cognitive or metacognitive cues that guide users to think about the problem like experts do. For example, in Knowledge Forum, cues like “My theory is,” “I need to understand,” and “A better theory is” are commonly used to foster knowledge-building skills.

In addition, QuestMap, Knowledge Forum, and the like use a graphical interface that allows users to visualize the discussion thread. Such graphical representations make explicit the trajectory of argumentation (Suthers, 1998) or idea improvement (Scardamalia, 2004) and provide context to the collaboration.

Technology can also be viewed as a resource to be drawn upon to support the process of learning collaboratively (Suthers, 2005). Technological environments record communication in a persistent medium that can support reflection and interpretation. Disciplinary representations such as models, simulations, and visualizations also serve as resources for conversation. They become objects about which learners engage in sense-making conversations (Roschelle, 1994). Another way technology can serve as a resource for collaborative learning is through fostering group awareness (see, e.g., Erickson et al., 2002). The mere awareness that others are present and will evaluate one’s actions may influence one’s choice of actions. Visualizations of conflict or agreement between members may lead to further argumentation or establishment of consensus.

What Are the Roles of Instructors?

Instructors play the crucial role of helping to direct PBL effort toward the appropriate goals, to gear learners toward achieving the goals, to moderate and synthesize discussions, to induce learners to capitalize on the affordances of the technologies, and to provide complementary support to the technologies. They scaffold the learning process and facilitate the group processes to ensure that the participants maintain focus.

Too often, students are engrossed in finding solutions to the problem and neglect the need to understand the underlying knowledge and principles. The telltale signs appear when students try to search for existing solutions, usually from the Internet, to plug into the problem without much deliberation on the knowledge or principles involved in solving the problem. We can also tell when students do not contest the basic assumptions but merely engage in discussion on whether the solution fits. Instructors can help bring forth intersubjectivity by probing students’ basic assumptions, nudging students for alternative definitions of the problem space and for alternative solutions, encouraging discussion on the appropriateness of the alternative problem space and solutions, asking for justification for the solutions, and requesting for explanations of the knowledge and principles used.

In the case of e-collaboration, it is critical to tap the potential of the collaborative technologies. Technologies such as CSCA tools and Knowledge Forum would be reduced to cumbersome chat tools if the software supports are not utilized appropriately. In one instance, the first author observed a class of 35 grade 9 students using Knowledge Forum like a synchronous chat tool. The end result was a web of notes full of trivial content, and the discussion suffered premature death when the sudden burst of Internet traffic froze the system.

If the software imposes structural constraints, the instructor needs to explain to students why the constraints are imposed and how to contribute to productive discussion. Contrasting positive and negative uses of the tools at the initial stage will help foster productive discussion.

Having discussed the four key areas of consideration in supporting collaborative ePBL, we shall now look at two specific examples of technology-supported collaboration.

Computer-supported Collaborative Argumentation

In this section, we examine the role of argumentation in problem solving and how CSCA can be used to support PBL.

Argumentation and Problem Solving

Rittel and Webber (1973) contend that informal argumentation is the central activity in solving ill-structured problems, which invariably involves debate, negotiation, and conflict. Voss (1991) also relates informal argumentation to solving ill-structured problems, characterizing informal argumentation as “reasoning performed in non-deductive situations that are essentially everyday situations of life and work.”

Central to informal argumentation is the claim-support relationship in which one makes a claim and builds a case for it with supporting evidence, as well as reconciles opposing claims. Since there are multiple representations of any problem, each leading to a different solution, problem solvers should present their arguments for the preferred solution and the reasons against alternative solutions. This means that problem solvers have to make claims for their solutions, warrant those claims, and back them up with supporting evidence (Voss, 1988). In a problem-solving discussion, participants can evaluate and challenge arguments put forth by each other, thus incrementally restricting the alternatives, culminating in a cogent argument for the best problem representations and solutions for the group (Jonassen, 1997).

Technology-supported Argumentation

CSCA technology refers to computer-based conferencing tools that are structured specifically to support argumentation during the problem-solving process. Sensemaker (Bell, 1997), Belvédère (Suthers, 1998), and QuestMap are examples of CSCA tools that provide students with a shared work space for collaboration and argumentation.

QuestMap, designed and developed by Conklin (1993), has been employed commercially by some corporations for group activities such as strategic planning or new product design (Conklin, 1999) and can be adapted to educational settings for collaborative discussion (Carr, 1999). Structurally, it can be used to model a simplified version of Toulmin’s model of argumentation (Toulmin, 1958; Toulmin et al., 1984), as shown in Figure 8.1.

A user can start by creating the problem statement (denoted by the “?” icon). The same user or another participant can put forth his or her claim (bulb icon) of a possible solution to the problem, and support the claim with evidence, or ground (book icon). The warrant (“+” icon) explains why the ground is the evidence to support the claim. A rebuttal (“-” icon) shows an exceptional case in which the ground is not relevant. Secondary elements of argument like “backing” and “qualifier” are not explicitly represented in QuestMap but may be incorporated in the detailed notes embedded in the icons.

A CSCA tool can help scaffold argumentation skills by providing an argumentation structure and notation that support learners in their zone of proximal development (Vygotsky, 1978), thus enabling the learners to perform what they cannot do without the framework. The main assumption is that, by making the structure of argumentation explicit, learners can construct and communicate their arguments (Brown, 1986). Restricting learners to certain argumentation structures helps clarify reasoning by encouraging the learners to make explicit important assumptions, distinctions, and relationships (Buckingham Shum et al., 1997).

Graphical CSCA tools like QuestMap have added advantages. Suthers (1998) argues that visual representations can provide both cognitive and collaborative support, as cognitively “concrete representations of abstractions turn conceptual tasks into perceptual tasks.” Graphical representations allow users to visualize internal abstractions and make the deliberation process explicit in such a way that participants can view the steps that lead to the creation of an argument. They also make apparent alternative interpretations and points of view which would otherwise be difficult to see in the linear form of text. In terms of collaborative support, these “shared objects of perception” serve as “referential objects” and “status reminders,” coordinating group work by allowing participants to keep track of and refer to ideas under discussion.

CSCA may also help promote thinking by “slowing down” the argumentation process so that learners can better understand the reasoning (Leeman, 1987). Gordon and associates (1999) contend that CSCA not only supports learning of domain knowledge but also promotes reflective thinking and critical thinking through the process of argumentation. This is because the argumentation environment prompts students to question the arguments put forth by their teachers or fellow students instead of accepting them at face value.

Using CSCA for PBL

The following describes an example of how CSCA was used to support PBL for a class of graduate students studying turfgrass management. Turfgrass management is a complex, ill-structured domain that requires understanding of a wide range of knowledge, including agronomic principles of turfgrasses, expectations of golfers, pest control, management of employees, project management, and budget control (Danneberger, 1994). In the class, 30 students were engaged in PBL activities to analyze complex real-life cases before suggesting their solution strategies and detailed action plans for dealing with issues emerging from their analyses.

The instructor set up a web site on which rich descriptions of the case problems along with related information and pictures were provided. The course spanned a period of seven weeks. The students met twice a week with the instructor for 1 hour and 15 minutes each time. The instructor spent the first seven class meetings discussing the first case problem. Three important components of the case studies were considered: problem identification, analysis and solution; financial management; and project management. The instructor used the first case study to demonstrate the strategy for problem solving in turfgrass management. Subsequently, students were given three other case-based problems as assignments to be done in groups of 3-4 randomly assigned students.

Prior to the class discussion of a case, students met in small groups and prepared a group report, which included problem analysis and solution performed using QuestMap. During a typical class meeting, a group would role-play the various stakeholders involved in a case so as to represent and define the problem. A second group would present their analysis of the problem, and a third group would explain their solutions to the problem. Each group presentation was followed by a question-and-answer session, during which the students or the instructor could seek clarification of issues brought out during the presentation. After the presentations, the instructor would elaborate on key issues of the case and conduct short lectures on relevant concepts, rules, and principles when appropriate.

Computer-supported Knowledge Building

Knowledge Building and PBL

The notion of knowledge-building communities in schools was first proposed by Scardamalia and Bereiter (2003). They define knowledge building as “the production and continual improvement of ideas of value to a community, through means that increase the likelihood that what the community accomplishes will be greater than the sum of individual contributions and part of broader cultural efforts” (p. 1371). In a knowledge-building community, a group of learners jointly identify authentic problems and assume collective cognitive responsibilities to advance each other’s knowledge in regard to the problems (Hewitt, 2001; Scardamalia, 2002). In other words, the primary goal is to advance knowledge through problem solving.

How is knowledge building related to PBL? According to Bereiter (2002), knowledge building focuses on the problem of understanding. In knowledge building, the investigation can be triggered by a problem encountered in real life, but the goal is to advance conceptual knowledge that is robust enough to explain the problem, rather than arriving at a solution to the problem. For example, there might be a lighting problem in a theater. Students should be led to a discussion on how light is formed, how it travels, and so on, instead of just solving the lighting problem. Bereiter argues that knowledge that is built around and is indexed by problems (problem-centered knowledge) is usable knowledge. In contrast, knowledge that is learned at an abstract conceptual level and indexed by topics (referent-centered knowledge), as how it is presented in most textbooks, will be inert. This is similar to the argument by Brown and colleagues (1989) that contextual information is not ancillary to learning but is an integral part of knowledge. Decontextualized learning leads to inert knowledge that is not applicable in a real-world context.

Technology-supported Knowledge Building

A knowledge-building tool mediates the process of collaboration among learners; promotes inquiry, sense making, and reflective thinking; facilitates knowledge building; and provides record keeping. An example is Knowledge Forum (Figure 8.2).

We can leverage the affordances of Knowledge Forum to support collaborative problem solving (for details, see Scardamalia, 2004). The affordances are as follows. First, the tool provides a public space in the form of a graphical interface where views can be created for discussion on different aspects of the problem. A new view is like a blank sheet of paper to which graphics and notes can be added. Second, ideas and thoughts are reified as objects of inquiry. Ideas posted are subject to review, critique, or comment by other group members. The historical interactions of these processes are automatically captured in a database. Thus, ideas in our minds become “objects” that can be acted and improved upon. Third, notes posted can be connected and related in various ways: built on, cited, annotated, or referenced. Intersubjectivity of ideas can be facilitated.

Fourth, customizable scaffolds are provided to cue users in problem solving. Unlike QuestMap, which imposes a structure on the way ideas are related (e.g., a rebuttal note points to a claim note but not the other way), these cues, constructed by the expert instructor, serve as cognitive prompts to model “ways of thinking” about the problem. Users, however, are free to express their ideas in other ways. Fifth, a problem field is provided at the head of a note. Notes that build on each other will inherit the same problem title in the default mode unless it is changed by a user. Sixth, the “rise above” function allows users to collapse related notes into one note represented by a special icon. This function helps tidy up a cluttered view full of connected notes after discussion at some length. By so doing, the learners also achieve “clarity of mind” by synthesizing their summaries or consensus. Lastly, embedded and transformative assessment is possible by allowing searching and tracking of contributions from individuals and groups, as well as concurrent feedback to these processes. Individual or group portfolios can also be organized through the views.

Using Knowledge-building Tools for PBL

The following presents a case example of a PBL activity involving kinematics being conducted in a high school science classroom supported by knowledge-building technology.

Crowding round the teacher’s table was a group of 25 fourteen-year-old boys and girls looking intently as the teacher demonstrated how they could use a remote-controlled car running on raised tracks to release a cube-shaped plasticine onto an area below the track. This was a simulation of a mission given to the students—to send a food parcel to victims trapped in a war zone—in which the toy car represented an aircraft delivering a food parcel (represented by plasticine) to war victims (represented by a target area drawn below the track).

In groups of five, these students worked together through an iterative process of generating hypotheses, identifying learning issues, and investigating the hypotheses to solve the problem. While these stages of problem solving guided students to work toward a solution, a knowledge-building approach was adopted to encourage deep understanding of the content domain of the problem. In each of the stages, students constantly sought to advance the group’s understanding. They put forth their ideas onto a public space, clarified their ideas with their group members, and negotiated for shared understanding. Supporting this collaborative process was Knowledge Constructor (Figure 8.3), a knowledge-building tool with affordances similar to those of Knowledge Forum.

Knowledge Constructor is a public space shared by all the members in a group. All members can post their initial ideas and information that they have found or that they know in this space. For instance, in the observed classroom, one student posted his initial idea on how the problem could be solved based on his own naive theory.

Expecting that the “parcel” would fall vertically downward instead of taking a parabolic path, he suggested this solution:

This note and others contributed by his group members produced a diversity of initial ideas on how the problem could be solved. These ideas, placed in a public domain in Knowledge Constructor, were given equal opportunities to be viewed, commented, or even queried by group members, unlike in the case of a face-to-face interaction, where some members would dominate the discussion. Even half-baked ideas or “incorrect” solutions were read, challenged, or refined by the group members. In the instance above, another student challenged the student’s hypothesis that the parcel would drop vertically downward:

As the students worked toward a shared understanding, they questioned, sought clarification, and challenged each other about the motion of the parcel. Finally, they realized that the parcel would not fall directly down but would “move some [horizontal] distance”

because the “object will travel at first with a speed equivalent to the ‘plane’.” Mediating this discussion were the scaffolds that guided students in the different ways they could build on to their group members’ ideas. These scaffolds are “My Hypothesis,” “My Comments,” “My Queries,” “What I Know,” “What I Need to Understand,” and “What I Have Found Out.”

With the knowledge-building process built into each stage of PBL, the students inquired deeper into their understanding, constantly trying to advance the group’s knowledge. The students, in trying to better understand the motion of the parcel, came to an understanding of the relationship between the forces acting on the parcel and the motion of the parcel, as evidenced in one of the students’ note:

Hence, knowledge-building technology, as seen in the example, serves as a useful tool that mediates students’ collaboration in problem solving. It provides a public space that facilitates intersubjectivity, inquiry, and reflective thinking. Such technology, when incorporated into PBL, not only supports parallel advancement of the group’s understanding of the problem and conceptual understanding within the content domain, but extends further beyond.


We have argued that collaboration among participants is inherent in PBL. Social epistemology and intersubjectivity underlie the proposition of collaboration in PBL and allow participants to bring different perspectives to the problem and negotiate a common understanding. Participants construct representations to solutions and discuss the meaning of these representations in context. Technology has a role to play in supporting collaboration to enable meaning making among participants. It offers scaffolding through providing structural constraints on the communication, cognitive and metacognitive cues, and a persistent medium to record collaborations for reflection and interpretation.

We hold that, to implement ePBL, we need to understand the goals of PBL, identify the kinds of support we need to provide, leverage appropriate technologies to augment or scaffold the PBL process, and, last but not least, coordinate, guide, and facilitate the process.

We have discussed two approaches to using technology to support collaboration in ePBL: argumentation using QuestMap and knowledge building using Knowledge Forum. Argumentation tools provide the structure for posing arguments and rebuttals, while knowledge-building tools provide the scaffolding for articulating ideas, identifying the type of contribution, and building on ideas for solving problems. We highlighted in the illustrative examples the critical role of instructors in structuring the PBL process and moderating the discussion.


Baker, M., Hansen, T., Joiner, R., & Traum, D. (1999). The role of grounding in collaborative learning tasks. In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches. Oxford: Elsevier.

Barrows, H. S. (2000). Problem-based learning applied to medical education. Springfield, IL: Southern Illinois University Press.

Bell, P. (1997). Using argument representation to make thinking visible for individuals and groups. Paper presented at the Second International Conference on Computer Support for Collaborative Learning CSCL ’97. Toronto.

Bereiter, C. (1992). Referent-centred and problem-centred knowledge: Elements of an educational epistemology. Interchange, 24 (4), 337-61.

Bereiter, C. (2002). Education and mind in the knowledge age. Hillsdale, NJ: Erlbaum.

Brown, J. S. (1986). From cognitive ergonomics to social ergonomics and beyond. In D. A. Norman & S. W. Draper (Eds.), Design rationale: Concepts, techniques and use. Hillsdale, NJ: Erlbaum.

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Research, 18, 32-42.

Buckingham Shum, S., MacLean, A., Bellotti, V. M. E., & Hammond, N. V. (1997). Graphical argumentation and design cognition.

Carr, C. (1999). The effect of computer-supported collaborative argumentation (CSCA) on argumentation skills in second-year law students. Doctoral dissertation, Pennsylvania State University.

Churchman, C. W. (1971). The design of inquiring systems: Basic concepts of systems and organization. New York: Basic Books.

Clark, H. (1996). Using language. New York: Cambridge University Press.

Conklin, E. J. (1993). Capturing organizational memory. In D. Coleman (Ed.), Proceedings of GroupWare ’92 (pp. 133-37). San Mateo, CA: Morgan Kaufmann.

Conklin, E. J. (1999). Seven years of industrial strength CSCA in an electric utility. Paper presented at the Computer Supported Collaborative Learning Conference CSCL ’99. Stanford University, Stanford, CA, December 12-15.

Danneberger, T. K. (1994). Integrating classroom instruction with turfgrass field experience through a golf course project. Journal of Natural Resource in Life Science Education, 23, 56-58.

Dillenbourg, P., & Traum, D. (1999). The long road from a shared screen to a shared understanding. In C. Hoadley & J. Roschelle (Eds.), Proceedings of the Computer Supported Collaborative Learning Conference CSCL ’99. Designing new media for a new millennium: Collaborative technology for learning, education, and training. Mahwah, NJ: Erlbaum.

Erickson, T., Halverson, C., Kellogg, W. A., Laff, M., & Wolf, T. (2002). Social translucence: Designing social infrastructures that make collective activity visible. Communications of the ACM, 45 (4), 40-44.

Feltovich, P. J., Spiro, R., & Coulson, R. L. (1993). Learning, teaching and testing for complex conceptual understanding. In N. Fredrickson, R. Mislevy & I. Bejar (Eds.), Test theory for a new generation of tests (pp. 181-217). Hillsdale, NJ: Erlbaum.

Gordon, T. F., Johnigk, S., Schmidt-Belz, B., Voβ, A., & Petersen, U. (1999). Distance learning applications of the Zeno mediation system. Retrieved on November 8, 2006, from

Hammond, M. (1999). Issues associated with participation in online forums— The case of the communicative learner. Education and Information Technologies, 4, 353-67.

Hewitt, J. (2001). From focus on task to focus on understanding: The cultural transformation of a Toronto classroom. In T. Koschmann, R. Halls & N. Miyake (Eds.), CSCL 2: Carrying forward the conversation (pp. 11-42). Mahwah, NJ: Erlbaum.

Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16 (3), 235-66.

Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45 (1), 65-94.

Koschmann, T., Kelson, A. C., Feltovich, P. J., & Barrows, H. S. (1996). Computer-supported problem-based learning: A principled approach to the use of computers in collaborative learning. In T. Koschmann (Ed.), CSCL: Theory and practice of an emerging paradigm. Mahwah, NJ: Erlbaum.

Koschmann, T., Zemel, A., Conlee-Stevens, M., Young, N., Robbs, J., & Barnhart, A. (2005). How do people learn? Members’ methods and communicative mediation. In R. Bromme, F. W. Hesse & H. Spada (Eds.), Barriers and biases in computer-mediated knowledge communication—and how they may be overcome. Dordrecht, Netherlands: Kluwer.

Leeman, R. W. (1987). Taking perspectives: Teaching critical thinking in the argumentation course. Paper presented at the 73rd Annual Meeting of the Speech Communication Association. Boston, MA (ERIC Document Reproduction Service No. ED 292 147).

Matusov, E. (1996). Intersubjectivity without agreement. Mind, Culture and Activity, 3 (1), 25-45.

Pea, R. D. (1993). Practices of distributed intelligence and designs for education. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 47-87). New York: Cambridge University Press.

Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Science, 4, 155-69.

Roschelle, J. (1994). Designing for cognitive communication: Epistemic fidelity or mediating collaborative inquiry? Arachnet Electronic Journal on Virtual Culture, 2 (2).

Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal education in a knowledge society (pp. 67-98). Chicago: Open Court.

Scardamalia, M. (2004). CSILE/Knowledge Forum. In A. Kovalchick & K. Dawson (Eds.), Education and technology: An encyclopedia (pp. 183-92). Santa Barbara, CA: ABC-CLIO.

Scardamalia, M., & Bereiter, C. (2003). Knowledge building. In J. W. Guthrie (Ed.), Encyclopedia of education (2nd ed., pp. 1370-73). New York: Macmillan Reference.

Sinnott, J. D. (Ed.) (1989). A model for solution of ill-structured problems: Implications for everyday and abstract problem solving. In Everyday problem solving: Theory and application (pp. 72-99). New York: Praeger.

Suthers, D. (1998). Representations for scaffolding collaborative inquiry on ill-structured problems. Paper presented at the 1998 AERA Annual Meeting. San Diego, CA.

Suthers, D. (2005). Technology affordances for intersubjective learning: A thematic agenda for CSCL. In T. Koschmann, D. D. Suthers & T.-W. Chan (Eds.), Proceedings of the Computer Supported Collaborative Learning Conference CSCL 2005: The Next 10 Years! (pp. 662-71). Mahwah, NJ: Erlbaum.

Toulmin, S. (1958). The uses of argument. Cambridge: Cambridge University Press.

Toulmin, S., Rieke, R., & Janik, A. (1984). An introduction to reasoning (2nd ed.). New York: Macmillan.

Voss, J. F. (1988). Learning and transfer in subject-matter learning: A problem solving model. International Journal of Educational Research, 11, 607-22.

Voss, J. F. (1991). Informal reasoning and international relations. In J. F. Voss, D. N. Perkins & J. W. Segal (Eds.), Informal reasoning and education. Hillsdale, NJ: Erlbaum.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

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Supporting Collaboration in Web–based Problem–based Learning

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