The effects of the Collaborative Representation Supporting Tool on problem-solving processes and outcomes in web-based collaborative Problem-Based Learning (PBL) environments.Web-based collaborative Problem-Based Learning (PBL) environments have great potential for learner improvement in solving ill-structured problems in practical situations. Web-based environments, however, offer learners relatively few chances to solve problems through face-to-face interactions compared to traditional classrooms, thereby making it difficult for learners to develop a shared understanding for particular mutual task performances. Therefore, academic efforts are needed to overcome this limitation. As one such effort, this study suggests the use of Collaborative Representation Supporting Tool (CRST), which is newly developed to support learners in constructing their shared knowledge structures collaboratively. This visibly persistent tool may effectively lead people toward more focused discourses by providing them with the means to externalize their emerging knowledge. As a result of providing the CRST, the conclusion could be made that this tool was highly beneficial for learners. In PBL processes as well as PBL outcomes, the use of the CRST had more positive effects statistically than the use of a web bulletin board without the CRST. The results of this study suggest that the CRST can be a helpful tool to support collaborative learning in web-based collaborative PBL environments. ********** The Web, as a recently emerging communication medium, has become a dominant means for empowering people to perform their work well in a variety of fields in our society. In particular, web-based instruction has also become a type of instructional delivery system for improving human learning. When the Web is used as an instructional delivery system, learners might interact with others without the constraint of time and geography. So people are expected to conduct the given learning tasks collaboratively through the vivid learning community composed of hands-on devices for sharing their collective data and products. Yet, as Jacobson (1994) pointed out, the majority of studies on web-based learning environments have depended very heavily on technology-driven views. As a result, it is not easy to obtain expected learning effects in web-based learning environments. Therefore, when the Web is used for the purpose of education rather than a simple delivery system, the design and development of web-based learning environments have to be inspired by educational epistemology and be embodied by physical artifacts based on education theories and specific educational strategies. Among many education epistemologies, constructivism proposes a variety of implications for the design and development of powerful web-based learning environments. Specifically, Problem-Based Learning (PBL), inspired by constructivist epistemology, has many possibilities to improve human learning by posing meaningful, authentic situations and provides many resources, instructions, and guidance for learners to develop their domain knowledge (Mayo, Donnelly, Nash, & Schwartz, 1993). Also, Gagne (1980) stated, "The central point of education is to teach people to think, to use their rational powers, to become better problem solvers" (p.95). Therefore, PBL has been used in many practical settings as well as in academic fields. On the other hand, when applying PBL in distributed groups, learners can encounter a number of limitations. Unlike learning in the same place and time with others, people have to express their thoughts by interacting with computer-mediated protocols such as web-based bulletin boards and email servers. Thus, if learners study in a web-based collaborative learning environment, it can be very difficult for them to negotiate the meaning and to construct a shared understanding necessary for effective collaborative learning. Moreover, poor communication channels not rooted in any theoretical foundation may make it difficult for learners to perform cognitive activities when solving given or emerging problems through social interaction. This study proposes an approach to build more robust collaborative learning environments to support PBL. As one of our efforts, we designed and developed the Collaborative Representation Supporting Tool (CRST), which is expected to support learners in constructing their shared knowledge structures collaboratively. After developing and implementing the tool, we analyzed the effects of the CRST on problem-solving performance. The empirical inquiries investigated the effectiveness of CRST on problem-solving processes and outcomes. RESEARCH QUESTIONS The following research questions were addressed in this study: 1. Are there significant differences in problem-solving processes when the CRST is given in web-based collaborative PBL, in comparison to web bulletin boards without the CRST? 2. Are there significant differences in problem solving outcomes when the CRST is given in web-based collaborative PBL, in comparison to web bulletin boards without the CRST? THEORETICAL FRAMEWORK Human Learning and Constructivism The recently emerging education epistemology, constructivism, emphasizes the learner's vivacious learning and high order thinking such as problem solving, situated learning, and reasoning (Jonassen, 2000). From this perspective, learners can be defined as active beings who can choose necessary learning issues and learn them independently or together. Moreover, the central roles learners play in the overall learning processes are as follows: (a) setting their learning goals, (b) collecting necessary materials, (c) solving problems, (d) evaluating their learning activities. Also, constructivism describes knowledge as the product of the meaningful interpretation of information within the context of personal and/or group perspectives (Savery & Duffy, 1996). Constructivism brings heightened attention to new learning processes that can occur in naturalistic settings. According to Stahl (1999), generic aspects of the learning process can be classified into two categories: individual-oriented learning processes and group-oriented collaborated learning processes. The latter is primarily needed for learners to tune the accuracy or suitability of their personal understanding. These processes may be characterized as very closely related and two components should occur in an interactive fashion. Figure 1 describes Stahl's (1999) human learning model, which scrutinizes how learners build their knowledge. Starting in the lower left corner, Figure 1 shows the cycle of personal understanding. The rest of the diagram depicts how personal beliefs that we become aware of in our learning activities can be articulated in language and enter into a collaborative learning process with other learners and with shared cultural artifacts. Undoubtedly, the cultural artifacts can't be absolute, and they can be changed by learners' continued questions, explanations, and negotiations. The focus of this study relies on the step of "public statements" with which learners externalize their personal beliefs in words. [FIGURE 1 OMITTED] It is not always possible to resolve a problem in personal understanding, particularly when it is provoked by others (Stahl, 2002). Then learners may need to enter into the social knowledge building process and create new meanings collaboratively. To do this, learners typically articulate their initial belief in words and express what they know in public statements. Computer-mediated interaction totally depends upon the artifacts being expressed. Therefore, according to how well learners externalize their thoughts in the step of "public statements," ensuing argumentations and explanations could vary. It might even affect this entire cycle of human learning. Likewise, in the web-based collaborative PBL where learning occurs by way of indirect discourse, the more accurate externalization of personal representations and beliefs will be more important than any other factors. COLLABORATIVE PROBLEM-BASED LEARNING ON THE WEB Web-based collaborative PBL is inspired by the thought that "learning is a social process" (Vygotsky, 1978). The social constructivist view emphasizes that learners negotiate their thoughts and build mutual understandings (Littleton & Hakkinen, 1999). Essentially, web-based collaborative PBL is the result of social interactions by negotiations and mutual understandings, and is subsequently based on the claim that problem solving in daily life is affected by conversations with adults or significant others. In the collaborative PBL, learners are expected to solve given or emerging problems together. The concept of "collaborative" could be thought of in the following three aspects of learning (Dillenbourg, 1999). First, in the situational aspect, the term "collaborative" refers to the fact that learners in collaborative learning solve given problems with common goals and perform similar level tasks. Additionally, collaboration is more likely to occur between people of a similar status than between a teacher and a pupil. Second, in terms of interactivity, the degree of interactivity among peers might be decided by the extent to which these interactions influence the peers' cognitive processes, not by the frequency of interaction. Moreover, in collaborative learning, there are both synchronous and asynchronous interactions. Through these interaction manners, learners could externalize their opinions and interact with others. Third, in the aspect of processes, when learners study collaboratively, they first articulate their knowledge or beliefs in their own language. Learners may experience personal and social cognitive conflicts in the midst of a discussion, so they try to disentangle these conflicts by explaining their own understanding and arguing to their peers with reasonable evidence or rationale. It is also worth noting what PBL actually is. Basically, learning in PBL is expected to occur as a side effect of problem solving by improving problem-solving performances (Dillenbourg, 1999). Also, the reasons for emphasis on "Problematic" in constructivism are that it plays the role of grabbing the learners' interest and it leads learners to study voluntarily (Schank, 1992). The "problematic" situation may make learners accommodate when their current experience can't be assimilated in an existing schema. According to Jonassen (2002), PBL can have two critical properties. First, problem solving requires the mental representation of problematic situations in the world. That is, problem solvers construct an internal representation of the problem, known as the problem space (Newell & Simon, 1972). They may do that personally, or they may socially construct some representation of the problem. Second, problem solving requires some active manipulation of the problem space, involving a host of activities such as model building, hypothesis generation, speculation, solution testing, and information gathering. Manipulation of the problem space, be it an internal mental representation or an external physical representation, necessarily engages conscious activity. That is, it is crucial how well problem solvers can manipulate their problem space more systematically and more clearly. In summary, the term "collaborative PBL" can be defined as a learning theory in which learners have a common goal, perform given tasks at the same level, and interact with one another while influencing their peers' cognitive processes. And in collaborative PBL, learners are expected to construct a problem representation and to manipulate the problem space, transferring their internal representations into external representations. ILL-STRUCTURED PROBLEM SOLVING PROCESSES PBL processes can differ depending on how well a problem is organized, how complicated the problem is, and whether the problem is related to authentic fields or not. But the PBL processes generally occur as follows (Jonassen, 2000). First, learners identify a problem and represent it internally enough to understand. Second, they set some plans to solve the problem. Then, they solve the problem according to their plans. Finally, they perform a review and evaluate their PBL processes and PBL outcomes. However, the PBL processes described could not sufficiently account for collaborative PBL processes in the case of solving ill-structured problems. When learners solve ill-structured problems, there are not absolute and accurate solutions, so learners are supposed to interact and persuade each other by presenting their claims and their rationales. Learners themselves tackle complexity and engage in meaningful learning. They actively seek learning resources, and exchange and negotiate their perspectives. They collaborate to study emerging learning issues as they strive to generate viable solutions. In this way, problem-solving processes with ill-structured problems may be less systematic and more dynamic than with well-structured problems. Therefore, to improve the entire collaborative PBL, the understanding of authentic and practical collaborative PBL processes has to precede all others. As one of the most authentic PBL processes, Miao (2000) suggested PBL-net schema as shown in Figure 2. The PBL-net schema gives us a chance to have a better understanding of ill-structured PBL process. In this Figure, the typed nodes and typed links are founded on the learners' various activities that make up the PBL processes. Based on the PBL-net schema, more productive and more realistic awareness of PBL processes can be obtained. For example, when solving ill-structured problems collaboratively, it is conceivable that learners (a) explore and represent the problem, (b) identify what they know, (c) identify what they do not know, (d) identify the goals and make an action plan, (e) collect information, (f) discuss the information collected, (g) apply their knowledge to the problem, and (h) review the above process. These processes are very dynamic rather than step-by-step procedures. Therefore, the sequences can differ more or less according to the various individuals' emerging opinions. With a whole awareness of PBL-net schema, the collaborative representation supporting tool (CRST) was designed and developed to enhance learners' authentic PBL processes in web-based collaborative learning. [FIGURE 2 OMITTED] DESIGNING OF COLLABORATIVE REPRESENTATION SUPPORTING TOOL (CRST) According to recent theories of human cognition, human intelligence is the result of tool use and of social mediations as well as of biological development (Stahl, 2000). Also, "Collaboration is a coordinated, synchronous activity that is the result of a continued attempt to construct and maintain a shared conception of a problem" (Roschelle & Teasley, 1995, p. 70). That is, an individual working in a group must constantly refer back to the shared external representation while coordinating activities with others. Thus it is conceivable that external representations have a greater effect on individual cognition in a social context than they do when a person is working alone. Also the external representations have some possibilities to be reconstructed with the change of learners' internal representation. Here, internal representations are in the mind as propositions, mental images, and so forth, while external representations refer to the visualization of the learners' thinking, such as physical symbols, or diagrams consisting of nodes and links (Hayes, 1989; Ellis & Siegler, 1994). However, external representations are not simply peripheral aids (Roschelle & Teasley, 1995). They are an indispensable part of cognition. This is because cognition is concerned with representational states, and people can develop their understanding depending on how representations act as intermediaries in dynamically evolving collaborative processes. Moreover, the relations of external representation and internal mental representation are interwoven, leading learners to solve given problems in a dynamic manner (Zhang, 1997). Roschelle and Teasley (1995) suggested that the representation tool and the collaborative learning process could be designed together for more effective learning. That is, the two factors can be combined with a more powerful instructional representation tool resulting. In fact, as Suthers (2000) pointed out, "representation tools mediate collaborative learning interactions by providing learners with the means to express their emerging knowledge in a persistent medium, inspectable by all participants, where the knowledge then becomes part of the shared context" (p. 2). In addition to primary ideas about the representation tool defined by Suthers (2000), the CRST, the PBL-net schema in Figure 2, refers to the graphical external representation tool to support learners to display, organize, and reorganize their thoughts in PBL processes. Learners can easily interact with one another and reach a mutual understanding as they work with group members. Specifically, the CRST reflects ongoing learning activities that learners perform according to the six phases of PBL. It also becomes a resource for further conversation and elaborated argumentation rather than a simple delivery tool. When utilizing the CRST, learners are required to construct representation diagrams by using a restricted set of typed nodes and typed links. All nodes and links reflect their thoughts and relationship between their thoughts. Considering continuous changes of our thoughts, the CRST is composed of different kinds of typed nodes and typed links according to six phases of PBL. Through constructing the CRST, learners are expected to effectively externalize their opinions and directly perceive and use a lot of information. OTHER PBL SUPPORT SYSTEMS STUDIES ON SUPPORTING PROBLEM-BASED LEARNING The CRST supports collaborative learning discourse by providing learners with the means to visualize their emerging knowledge in a constant tool. When using the CRST, learners can freely express their own opinions whether they are right or not. Namely, learners can reflect their internal representations on a physical medium by externalizing their thoughts (Zhang, 1997). The socially constructed CRST reflects the status of consistent, conflicting, and complementary knowledge among participants. The CRST in turn stimulates individuals' cognitive processes and initiates further social learning interaction. Thus, it is conceivable that external representation has greater effects on individual cognition in a social context than they do when working alone. So, if an external representation tool that perfectly reflects learners' thoughts can be developed, learners will be able to interact with one another without any restraint of communication. Because of these reasons, the study of representation tools has received extensive attention by researchers using different representation tools for similar objectives. This study analyzes the following six main PBL supporting systems, focusing on whether they support learners' external representation or not and how they support it. The comparison of existing PBL support systems is next. As shown in Table 1, the representation supports of ideas and relations in major PBL supporting systems have some limitations in order to scaffold a variety of learning activities that can occur in whole collaborative PBL processes (Miao, 2000). Only Belvedere provided partial representation supports of relations between ideas such as 1) against, 2) for. Most PBL supporting systems were designed and developed not considering representation supports of relations between ideas, but considering some representation supports of a variety of ideas. In the web-based collaborative PBL, different learning activities are required according to each phase consisted of collaborative PBL processes. In addition, human representations can be varied with the change of learners' experience based on a time and geography. Therefore, an effective representation supporting tool fitted to each of the PBL's six phases is needed to improve whole collaborative PBL. Therefore, this study focused primarily on creating a CRST for supporting all of the processes of collaborative PBL. The CRST was designed and developed based upon the learner's activities with the six phases of PBL. In PBL, learners are expected to (a) identify problems, (b) identify learning issues, (c) set goals & make plans, (d) learn information, (e) apply knowledge, (f) assess and reflect (Miao, 2000). Using different representation notations (consisted of typed nodes and typed links) according to the six phases of PBL may make it easier for learners to externalize their knowledge and to understand others' ideas. Table 2 presents the specific components and functions of the CRST. Learners can perform their problem solving constructively by choosing idea types and relation types that are given differently according to six phases of PBL. That is, learners can express their thoughts by constructing and selecting the most appropriate idea type and relation type. The concrete explanations of Table 2 are as follows. At first, four predefined idea types and three predefined relation types are given to learners in the phase of "identifying problem." Learners can express and be aware of collaborative representations, using the four predefined idea types as follows: (a) What?, (b) Cue?, (c) What prevent?, and (d) My opinion. And, these idea types can be connected by using three predefined relation types such as (a) Question, (b) Answer, and (c) Comment. When using these ideas types and relation types, learners can easily reach to a mutual agreement on a problem representation. Second, learners, in the phase of "identifying learning issues," are supposed to extract specific learning issues after identifying a problem in the first phase. When using the CRST, people can be supported as following idea types; (a) Issues, (b) More what?, and (c) My opinion. And these ideas can be connected by links typed by (a) Question, (b) Answer, and (c) Comment. By using these idea types and relation types, it is expected that learners will come to a mutual agreement about identifying learning issues through the more accurate and visible interaction. Third, in the phase of "setting goal and making plan," the CRST supports learners to set goals and make plans by giving them some representation aids. The representation aids include idea types such as (a) Resource, (b) Who?, and (c) My Opinion as well as relation types such as (a) Question, (b) Answer, and (c) Common. People can easily generate some goals and plans by using these representation aids. Fourth, "learning information" is the phase in which learners are involved in studying learning issues. In this phase, learners are expected to perform learning activities such as proposing plausible solutions or insisting something with rationales. In this case, the CRST supports external representations about (a) Resources, (b) Principles, (c) Evidence, and (d) My idea. And it supports learners' relation representations by asking them to connect ideas by using links such as (a) For, (b) Against, (c) Question, (d) Answer, and (e) Comment. Fifth, in the phase of "Applying Knowledge," learners are supposed to apply their new solution to a given problem. The CRST supports learners' representation of ideas and relations needed to solve a problem. Concretely, two predefined idea types (Solution and My opinion) are provided as ideas representation supports. Likewise, the six link types (Solve, For, Against, Question, Answer, and Comment) are provided as relation representation supports. Sixth, in the phase of "assessing and reflecting," the CRST helps learners to have a chance to assess and reflect their learning processes which they have performed by giving them idea representation aids and relation representation aids. At first, idea representation aids are provided by the nodes predefined by (a) Identifying problem, (b) Identifying learning issues, (c) Setting goal and Making plan, (d) Learning information, (e) Applying Knowledge, and (f) Assessing and Reflecting. And relation representation aids are provided by a predefined link such as (a) Comment. These representation aids make individuals solve a problem focusing on their assessment and reflection. After all, their initial thoughts are elaborated while they use the CRST. In addition, by displaying learners' current status in six prespecified phases at the right side of each six screen, learners may acquire information on their own current progress and draw up specific plans for learning. Also, learners can easily have a chance to reach a mutual agreement by writing down their common consensus in the space at the bottom of interface. The space for writing a common consensus is given at every phase. On the other hand, the chances of free rider may be reduced because of providing the specific colored link according to each individual. Ultimately, the purpose of providing the CRST is to improve the effects of learning by increasing the efficiency and effectiveness of learners' external representations on collaborative problem solving. The specific interface of the CSRT is shown in Figure 3. The CRST is to support learners to represent the structure of knowledge, which group participants have constructed. According to six phases of problem-solving process, creating the CRST requires learners to analyze structural relationships among contents they study. For instance, in the phase of "identifying a problem," the CRST required learners to participate in the following activities such as "sharing their problem" representations, explaining and arguing what they understand and externalizing mutual agreements by using given nodes (e.g. What?, Cue?, What prevent?, and Opinion) and given links (e.g., Question, Answer, and Comment). So the CRST plays the role of scaffolding by requiring people to use only specific responses that are extracted in PBL-Schema. Likewise, the structures constructed by predefined nodes and links result in more coherent and cogent conversations. The CRST consists of six interfaces with seven main parts, shown in Table 3. According to the six phases of PBL, there are different kinds of nodes and links. And they are based on expected learners' activities on specific phases. On the dynamic bulletin board for collaborative discussions, learners can create and revise new nodes that are connected by predefined links. The representation artifacts have the potential to be developed continuously if learners want to elaborate. [FIGURE 3 OMITTED] When learners click a phase among the six phases of PBL on the right side of interface in the Figure 3, the current interface is transferred into the interface in the chosen phase. Of course, the interfaces differ in the given nodes and links and expected learners' activities. Figure 4 is an actual screen shot of students in Korea using the CRST in problem-solving activities. As shown in Figure 4, the students are on the phase of Identifying Learning Issues. In this step, they were supposed to identify learning issues to solve their given problem. Specifically, each team member needed to describe the learning issues based on their own thoughts. After doing that, they could compare each of the students' messages and give comments or questions to other students' messages. Finally, they wrote a mutual consensus about identifying learning issues through more accurate and visible interaction. METHODS Participants Participants of the study were college students who registered for an educational technology and methods course offered by the department of Educational Technology at Hanyang University in South Korea. Forty-one students agreed to participate in the beginning of the study. Participation was voluntary based and participants were assured of the confidentiality of their responses. [FIGURE 4 OMITTED] Materials Software: Two software packages were used: Bulletin Board Systems (BBS) (Text) and CRST (Visual). Control groups used BBS, while treatment groups used CRST. Groups using CRST were provided with predefined nodes and predefined links for external representation of PBL performance. Instructional challenging problem: Participants were presented with "Instructional challenging problem" in a web-browser. An instructional challenging problem is based on instructional design models, and learners are required to find the best instructional design model among many models through debating. It is an ill-structured problem: at any given point, many possible knowledge units may reasonably be considered. Procedure A total of 41 learners were randomly assigned to one of the two groups to test the effects of the selected treatment variables. There were no significant differences between control groups and treatment groups in their mean grade points (t=.57, p>.05). All groups were supposed to perform the identical task of exploring and challenging an ill-structured problem on Instructional System Design (ISD) Model. The treatment used the CRST while the control group did not. Then the results of this study were analyzed, through the posttest. PBL Performance Evaluation The posttest was performed as follows. To measure the PBL process, O'Neil and Abedi's (1996) analysis of the problem process, and Park and Woo's (1999) test for PBL were adjusted and used for this evaluation. This PBL processes test was a multiple-choice test, which was composed of 42 items. The Cronbach's Alpha' was calculated to test the reliability of the assessment and the result was as follows in Table 4. PBL Outcomes Assessment To measure PBL outcomes, each team's final report was assessed. The final reports were to design instruction based on their chosen ISD model. PBL outcomes were assessed on the basis of (a) inquiry activities, (b) the qualities of outcome, (c) the degree of collaboration, and (d) creativity (KERIS, 2001). The Cronbach's Alpha' was calculated to test the reliability of the assessment and the result was .73. RESULTS Difference on the Problem-Solving Processes The learners' problem solving processes were evaluated by both a PBL processes paper test and interaction frequencies. The PBL processes paper test was a multiple-choice test which was composed of 42 items. To analyze the effects of the CRST, a t-test was used. The statistical power was also included to assist the interpretation of how meaningful the statistical test was. The statistical analyses were done with the software SAS version 8. The results can be found below. The Results of the PBL Processes Paper Test In analyzing the group's differences from the result of the PBL processes paper test, we could see that providing the CRST was not statistically significant for problem solving processes (t=.10, p>.05) as seen in Table 5. The Results of Analyses of Interaction Frequencies The analyses of interaction frequencies were also performed to identify the effects of the CRST on PBL processes. These analyses were done in the three ways. First, using a t-test, we investigated the frequencies at which the learners posted their opinions on the bulletin board. Second, we examined the frequencies at which learners responded to their peers' opinions at least once, again with a t-test. Finally, we analyzed how learners elaborated their opinions. Throughout these analyses, we use the term "elaboration" in the sense of subsequent consideration. We classified an elaboration as any subsequent response to a posted message. As seen in Table 6, in the viewpoint of the frequencies that learners wrote their opinions on the web bulletin board, there are no statistically significant differences between the treatment group and the control group (t=1.57, p>.01). However, Table 7 presents the frequencies that learners responded to peers' opinions. It has the statistical significance of the t-test (t=4.40, p<.00*). From this result, we can conclude that the CRST has some potential to facilitate learners' social interactions, which may be important in collaborative learning. Third, the results of level of elaboration are as follows (Figure 5, Figure 6). We classified an elaboration as any subsequent response to a posted message. In the case of the groups who were provided with the CRST, as shown in Figure 5, the frequencies were high, and the most number of subsequent responses was eight. That is, the CSRT stimulated learners' ongoing advance of discourse by visualizing their conversations. The results of analyzing the control groups are presented in Figure 6. A frequency of 0 (No-response) was in most common and the greatest number of subsequent responses was three. This result may imply that the control groups just studied together rather than collaborated with one another, because most of the participants only proposed their opinions, but rarely discussed issues by responding to peers' opinions successively. Difference on the PBL Outcomes The problem-solving outcomes of learners were evaluated by learners' outputs of group performance on given tasks. To analyze the effects of the CRST, a T-test was used. The following is the results of the statistical analyses. Table 8 shows the results of the t-test on the PBL outcomes. There was a statistically significant difference between the treatment and control groups in learners' problem solving outcomes (t=2.51, p<.01). This lends support to the hypothesis that the CRST will affect learners' problem-solving outcomes. CONCLUSION New perspectives on learning are emphasizing the social as well as the constructivist nature of the learning process. In actual learning situations, we often learn by socially negotiating meaning, not by teacher-centered activities. Problem-based learning, as one of the constructivism theories, encourages learners to engage in meaningful learning and collaboration among other learners. However, learners may encounter two crucial problems in web-based collaborative PBL. First, learners may have some limitations in interacting with one another because of the nature of indirect communication on the Web. Second, groups of learners may have problems constructing shared knowledge in the web-based learning environment. From the perspective of social constructivism, collaborative PBL can be viewed as a culturally and socially mediated activity. All actions are socially embedded, and all objects associated with such actions are cultural tools. When applying PBL in distributed groups, it has to be bridged by means of technology. So we can directly observe the knowledge that is being built, because it necessarily takes place in observable media. Accepting this view, we argue that it is important to provide a powerful artifact-mediated and society-aware virtual learning environment for geographically distributed people to conduct PBL activities effectively. Our approach is to provide the CRST to support collaborative PBL. The CRST is composed of representational notations (nodes and links) that are based on the necessary learners' activities according to the six phases of PBL. We expect that people will be able to increase their communal understanding by using the CRST. It will also be able to affect the PBL processes as well as PBL outcomes. The experimental results are as follows. First, whether the CRST was given or not, there were no statistically significant differences in problem solving processes. However, the CRST facilitated learners' collaboration when it was used in solving a problem. It helped learners interact with other learners more frequently and develop their opinions more elaborately. In essence, the CRST guided learners to problem-based discourse. Second, the CRST enabled learners to improve PBL outcomes. Thus, we can conclude that the results appear to be consistent with our hypothesis. This line of work is expected to demonstrate that we have a deep understanding of the instructional systems design for future web-based learning environments. It will provide a better theoretical foundation and experimental results for further study on collaborative representation supports.
Table 1 Comparison of Major PBL Support Systems
Support
representation
Support representation of various
of various types of relations
Existing PBL support systems ideas between ideas
CCL (Collaborative * *
Learning Laboratory)
CSILE 1) My theory
(Computer Supported Intentional 2) I need to understand
Learning Environment) 3) New Information *
4) What we have learned
5) Comment
CALE (Computer Assisted 1) Observed facts
Learning and Exploration 2) Hypothesis *
3) Need more
information
CNB 1) Question
(Collaboratory Notebook) 2) Conjecture
3) Evidence for
4) Evidence against *
5) Information
6) Plan
7) Step in plan
McBAGEL 1) Facts
2) Ideas *
3) Learning Issues
4) Action plans
Web-SMILE 1) Facts
2) Ideas *
3) Learning Issues
Belvedere 1) Data 1) Against
2) Hypothesis 2) For
3) Unspecified
'*' indicates "not available"
Table 2 The Components and Functions of CRST Corresponding to Six PBL
Processes
Ideas Relations Main
Phases Representations Representations functions
Identifying 1) What 1) Question - Guiding learners to
problem 2) Cue 2) Answer have a common
3) What prevent? 3) Comment understanding about a
4) My Opinion given problem itself by
explanation and debate.
Identifying 1) Issue 1) Question - Guiding learners to
Learning 2) More what? 2) Answer have a common
issues 3) My Opinion 3) Comment understanding about
identifying learning
issues by visualizing
learners' responses and
giving a chance to
choose learning issues.
Setting 1) Resource 1) Question - Guiding learners to
goal & 2) Who? 2) Answer reach a mutual
Making 3) My Opinion 3) Comment consensus about setting
plan goals and making plans
by visualizing
necessary learning
resources and assigned
roles.
Learning 1) Resource 1) For - Guiding learners to
Information 2) Principle 2) Against reach a mutual
3) Evidence 3) Question consensus about
4) My Idea 4) Answer learning information by
5) Comment visualizing principles
and evidences, which
can be foundations for
problem solving and
peers' responses.
Applying 1) Solution 1) Solve - Guiding learners to
Knowledge 2) My Opinion 2) For reach a mutual
3) Against consensus about
4) Question applying knowledge by
5) Answer visualizing their
6) Comment comparison among
solutions and peers'
responses.
Assessing & 1) Identifying 1) Comment - Guiding learners to
Reflecting Problem reach a mutual
2) Identifying consensus about
Learning assessing and
Issues reflection by
3) Setting goal & visualizing learners'
Making plan opinions about
4) Learning assessments and
Information reflections of whole
5) Applying problem solving
Knowledge processes.
6) Assessing &
Reflecting
Table 3 The Description of CRST's Functions and Characteristics
Descriptions
1) Learners who participated in collaborative PBL (Specific colored
links are given to each learner)
2) Description of expected learners' activities according to the six
phases of PBL
3) The predefined nodes are provided for supporting learners'
visualization of their thoughts. (According to the six phases of
PBL, different nodes are provided)
4) The predefined links are provided for supporting learners'
visualization of the relationship of their thoughts. (According to
the six phases of PBL, different links are provided)
5) A dynamic bulletin board as a kind of problem solving space is
provided for learners' collaborative discussion. (Learners are
likely to choose an appropriate node and link in the toolbox on the
left side of interface; thereby, the chosen node and link are shown
in the bulletin board. And then, learners are expected to write
their thoughts into nodes and connect the nodes by links)
6) Six phases of PBL (When learners click a phase among the six phases
of PBL, the current interface is transferred into the interface in
the chosen phase.)
7) A blank for writing mutual consensus
Table 4 The Reliability of Assessment
Cronbach's
Phases of PBL The number of items Alpha'
Identifying problem 1, 2, 3, 4, 5, 6, 7 .62
Identifying learning issues 8, 9, 10, 11, 12, 13, 14 .89
Setting goal & Making plan 15, 16, 17, 18, 19, 20, 21 .58
Learning information 22, 23, 24, 25, 26, 27, 28 .82
Applying Knowledge 29, 30, 31, 32, 33, 34, 35 .85
Assessing & Reflecting 36, 37, 38, 39, 40, 41, 42 .65
Table 5 T-test for PBL Processes Paper Test
Group N Mean SD T DF p
Treatment Group 20 143.00 16.40 .10 39 .92
Control Group 21 143.52 17.20
Table 6 t-Test for the Number of Students' Opinions on the Web Bulletin
Board
Group N Mean SD T DF p
Treatment Group 20 24.95 13.00 1.57 39 .12
Control Group 21 20.71 7.77
Table 7 t-Test for the Number of Responding Comments on Peer's Opinions
Group N Mean SD T DF p
Treatment Group 20 22.05 12.73 4.40 39 .00*
Controlgroup 21 8.61 5.66
The level of elaboration
The number of subsequent responses Frequency
0 92
1 146
2 129
3 78
4 53
5 26
6 15
7 8
8 1
Figure 5. The level of elaboration (Treatment Group)
The level of elaboration
The number of subsequent responses Frequency
0 247
1 146
2 31
3 9
Figure 6. The level of elaboration (Control Group)
Table 8 t-Test for PBL Outcomes
Group N Mean SD T DF p
Treatment Group 20 10.30 1.41 2.51 39 .00*
Control Group 21 8.95 1.96
References Dillenbourg, P. (1999). Instruction: What do you mean by "collaborative learning"? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1-19). New York: Pergamon. Ellis, S., & Siegler, R.S. (1994). Development of problem solving. In R.J. Sternberg (Ed.), Thinking and problem solving (pp. 333-367). San Diego, CA: Academic Press. Gagne, R.M. (1980). The conditions of learning (3rd ed.). New York: Holt, Rinehart, & Winston. Hayes, J.R. (1989). The complete problem solver (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. Jacobson, M.J. (1994). Issues in hypertext and hypermedia research: Toward a framework for linking theory-to-design. Journal of Educational Multimedia and Hypermedia, 3(2), 141-145. Jonassen, D.H. (2000) Toward a meta-theory of problem solving. Educational Technology: Research and Development, 48(4), 63-85. Jonassen, D.H. (2002). Learning to solve problems online. In C. Vrasidas & G. Glass (Eds.), Distance education and distance learning (pp. 75-98). Greenwich, CT: Information Age Publishing. KERIS (2001). The ways of making use of ICT for subject-matter learning. Development of online project learning and maintaining learning community. Seoul, South Korea: KERIS. Littleton, K., & Hakkinen, P. (1999). Learning together: understanding the process of computer based collaborative learning. In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches. New York: Pergamon. Mayo, P., Donnelly, M.B., Nash, P.P., & Schwartz, R.W. (1993). Student perceptions of tutor effectiveness in problem based surgery clerkship. Teaching and Learning in Medicine, 5(4), 227-233. Miao, Y. (2000). Design and implementation of a collaborative virtual problem-based learning environment. Retrieved May 11, 2005, from http://elib.tu-darmstadt.de/diss/000086/thesis.miao.PDF Newell, A., & Simon, H. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice Hall. O'Neil, HF. Jr., & Abedi, J. (1996). Reliability and validity of state metacognitive inventory: Potential for alternative assessment. Journal of Educational Research, 89, 234-245. Park, J., & Woo, O. (1999). The Effects of PBL (problem-based learning) on the problem solving process of students by their meta-cognitive levels. Korean Journal of Educational Technology, 15(3), 55-81. Roschelle, J., & Teasley, S. (1995). The construction of shared knowledge in collaborative problem solving. In C.E. O' Malley (Ed.), Computer-supported collaborative learning. Heidelberg, Springer-Verlag. Savery, J.R., & Duffy T.M. (1996). Problem-based learning: An instructional model and its constructivist framework. In B. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design. Englewood Cliffs, NJ: Educational Technology Publications. Schank, R.C. (1992). Goal-based scenarios (Technical Report No. 36). Evanston, IL: Institute for the Learning Sciences, Northwestern University. Stahl, G. (1999). Perspectives on collaborative knowledge-building environment: Toward a cognitive theory of computer support for learning. Retrieved May 11, 2005, from http://d3e.open.ac.uk/cscl99/Stahl/Stahl-paper.html Stahl, G. (2000). Collaborative information environments to support knowledge construction by communities. Al & Society, 14, 1-27. Stahl, G. (2002). Contributions to a theoretical framework for CSCL. In Proceedings of Computer Supported Collaborative Learning (CSCL 2002), Boulder, CO, (pp. 62-71). Retrieved May 11, 2005, from http://www.cis.drexel.edu/faculty/gerry/cscl/papers/ch15.pdf Suthers, D. (2000, November). Initial evidence for representational guidance of learning discourse. Proceedings of International Conference on Computers in Education, Taipei, Taiwan. Vygotsky, L. (1978). Mind in society. Cambridge, MA: Harvard University Press. Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21(2), 179-217. MIYOUNG LEE Florida State University, Tallahassee, FL USA my103@garnet.acns.fsu.edu DONG-SIK KIM Hanyang University, Seoul, South Korea kimdsik@hanyang.ac.kr |
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