Technology–mediated Problem–centered Learning Environments

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Technology–mediated Problem–centered Learning Environments

The Nature of Science and Implications for Science Learning
Conditions for Science Learning
Examining the Role of Technology in Problem-centered Learning Environments
Framework for CSCL-mediated Problem-centered Science Learning

Jennifer Yeo
David Hung


In recent years, the goals of science education in Singapore have been shifted to reflect the dynamism in the construction of science knowledge. As a result, there has been growing interest among educators to integrate problem solving into science learning. In problem-centered approaches, authenticity is fundamental, as it reflects the context in which knowledge is to be constructed. To reconstruct the meaning of science knowledge is to work within the context in which the knowledge is constructed. This perspective is espoused by the theories of constructivism and situated cognition.

There has been increasing interest in anchoring science learning in authentic problems. Examples of such pedagogical approaches include problem-based learning and knowledge building. These approaches, in varying degrees, emphasize context, experience, and interaction—conditions that are favored by science educators as the processes involved resemble the inquiry practice of scientists. However, these problem-centered approaches are a radical departure from the traditional form of schooling, where students solve clearly directed, well-structured problems as opposed to the open-ended and ill-structured authentic problems. Hence, when such pedagogies are introduced into the traditional classroom, teachers struggle to maintain a balance between the orderliness of a well-structured curriculum and the messiness of solving authentic problems. To overcome the challenge, we could use technology to support the processes of problem solving.

This chapter looks at three problem-centered pedagogies— namely problem-based learning, CoVis, and knowledge building— identifies their strengths and challenges in using technology support for science learning, and finally proposes a framework in which science learning can be made more effective and meaningful through a problem-centered approach supported by technology. But first we derive the conditions for science learning based on the theories of constructivism and situated cognition. These conditions will form the basis on which we examine the three pedagogical approaches.

The Nature of Science and Implications for Science Learning

Over the course of human history, people have developed many interconnected and validated ideas about the physical, biological, psychological, and social worlds which have enabled successive generations to achieve an increasingly comprehensive and reliable understanding of the human species and its environment. The means employed to develop these ideas are the particular ways of observing, thinking, experimenting, and validating. This is what is known as science (Rutherford & Ahlgren, 1990).

Traditionally, scientists were thought to make use of the orderly processes of the scientific method to seek objective “truths” in the world (Barab & Hay, 2001). However, the work of scientists is fundamentally situated (Latour, 1987, 1993; Traweek, 1988). The practices and knowledge of science emerge from a dynamic process of construction, its meaning embodied in artifacts, inseparable from the context in which the artifacts are created. This viewpoint highlights the importance of the context in which science knowledge is constructed and within which meaning is mutually constitutive.

Science knowledge is symbolic, its meaning abstracted from the physical world (Hayakawa & Hayakawa, 1990). This perspective is also shared by research findings from neuropsychology, which point toward the close coupling between perception and conception, and shaped by experiences (Lakoff & Johnson, 1999). To make sense of science and its artifacts is to be able to relate these otherwise meaningless symbols to the physical world.

Science is a complex social activity. It is through social acts that scientists interact in distinctive ways with society and culture to create something for some purpose. The community helps interpret and codify our emotional patterns. It is in interacting that meaning is made and embodied in artifacts. These artifacts provide the indispensable means for communication and become our shared cultural modes of experiences, which help determine the nature of our meaningful, coherent understanding of the world.

In short, scientific knowledge is the man-made explanation of how the world works. Science concepts are culturally based and need-based explanations of natural phenomena that are applied to our everyday activities. Hence, the production of science is linked to the use of and the need for scientific knowledge. In this view, knowing and doing science is historically and socially a situated process (Fusco & Barton, 2001). This perspective of science highlights the importance of context, experience, and interaction in science learning.

Conditions for Science Learning

Context: Authenticity in Science Learning

Traditional classroom experiences are very different from the type of learning and context that people experience outside of the classroom setting. Concepts are usually abstracted from the situations in which they are constructed and of value to (Barab et al., 1999; Young, 1993; Brown et al., 1989). Students are often learning about science, resulting in an accumulation of factual information (Brown & Duguid, 2000). However, to be able to apply science concepts meaningfully, students must learn to be scientists, appropriating the cultural practices of scientists going about solving problems, as well as the philosophy, motivations, influences, and frameworks behind science. Hence, the teaching of science should deal with the authenticity of doing science. It should provide students with the environment in which they engage in learning activities consistent with the way scientists work, whereby students are the users and producers of science (Fusco & Barton, 2001; Barab & Hay, 2001). According to MaKinster and associates (2001), authenticity should also be defined in terms of the life-world of the student, besides his or her target professional domain. In this chapter, we define a learning environment of authenticity as one in which learning outcomes have relevance and meaning to students as well as to some real-world practitioners. The goal of immersing students in authentic activities for science learning is to mold them into active learners who acquire scientific knowledge in a meaningful context and develop various styles of scientific thinking and communication (Edelson, 1997).

Although authenticity is addressed by using real-world problems (Edelson et al., 1999), it is an essential but not sufficient condition for authentic science learning. Authentic problems should have the potential to engage students’ curiosity, causing them to question their prior and at times naive understanding of natural phenomena (Reiner et al., 2000). This implies the need to focus attention on the process of science learning rather than the product.

Experience: Science Learning as an Inquiry Process

Science learning should reflect the scientific inquiry process in which scientific knowledge is constructed (Lee & Songer, 2003). Scientific inquiry has been defined as the “diverse ways in which scientists study the natural world and propose explanations based on evidence derived from their work” (NRC, 1996). In scientific inquiry, scientists are typically involved in activities such as questioning, investigating, analyzing, exploring, communicating, and reflecting (Yap et al., 2002). These inquiry processes are mediated by tools for analysis, investigation, experimentation, and other scientific tasks. Hence, by being engaged in the inquiry process, students undergo the same process of knowledge construction as scientists, appropriating similar habits of action, tools, and signs as used by scientists (Singer et al., 2000). Besides, in the process of inquiry, students are involved in theory building, theory revision, and evidence generation (Kuhn, 1993). This would entail combining scientific processes and knowledge as students use reasoning and critical thinking to develop a rich understanding of science (NRC, 1996).

As students work through the inquiry process, they also develop ways of communicating with their peers and team mates, developing similar skills that scientists possess, such as observation, inference, critical thinking, experimentation, reasoning, and argumentation (Kuhn, 1993; NRC, 1996; Singer et al., 2000). The inquiry process should be mediated by the cultural tools that scientists use, such as visualization programs, spreadsheets, and laboratory apparatus. These tools help students acquire the techniques, signs, and symbols that are associated with scientific practices.

Interaction: Science Learning as Participation in a Community

From a situative perspective, all human thoughts develop in a fundamentally social context (Clancey, 1997). In a community of scientists, scientific knowledge is created through a fundamentally social activity that occurs between persons, not just within them (Kuhn, 1993). As a result, scientists develop a common way of responding to patterns and features in the scientific context which Gee (1997) calls discourse. Such customary forms of communication and disciplinary practices arise through constant negotiation among practitioners (Bazerman, 1988; Miller, 1994; O’Neill, 2001).

In order to authenticate the learning of science, science educators should foster discipline-specific literacy by enculturating students into disciplinary practice and communication (O’Neill, 2001). Hence, science learning should take place in a learning community that emphasizes collaborative science learning and the specific ways of communication in the science community, such as open communication. Such collaborative learning encourages learning, as “any higher mental function necessarily goes through a social plane before it is internalized” (Vygotsky, 1978). It is in interacting that meaning is constructed of scientific concepts, through the use of language, signs, symbols, tools, and techniques developed by scientists. Such action encourages the appropriation of the culture and practices of the science community (Brown et al., 1989). In the learning community, it may involve students interacting with peers in small groups or as part of a large class discussion or students interacting with more knowledgeable community members (Barab & Hay, 2001; O’Neill, 2001; Edelson, 1997).

In summary, science learning from a situative perspective should be anchored in authentic science tasks, with the aim of building students into active learners who appropriate scientific knowledge in a meaningful context and develop different styles of scientific thinking and communication. As such, an authentic science learning environment should possess the following attributes:

  • Context: Students should be engaged in ill-structured authentic science problems or issues.
  • Experience: The inquiry approach should be the key strategy in the teaching and learning of science in a situated science learning environment.
  • Interaction: The learning environment should engage students in discourse as they work collaboratively in a science learning community.

Scaffolding in Science Learning

The scientific inquiry process differs for scientists and students (O’Neill, 2001; Kozma, 2003). The key differences lie in the inquirer’s knowledge, experience, attitude, and scientific thinking, the inquiry context, as well as the constraint of time and resources for students’ inquiry (Bransford et al., 1999; Edelson et al., 1999). Scientists have well-developed knowledge in their domain of expertise (Chi et al., 1988), possess the ability to see patterns that novices fail to see (Lesgold et al., 1988), and have fundamentally different problem-solving strategies and different ways of representing information (Dunbar, 1995; Chi et al., 1981). Students, on the other hand, often lack content knowledge as well as metacognitive skills to be able to think about their own thoughts (Kuhn, 1993). Furthermore, they lack the ability to utilize similar signs, symbols, tools, and techniques as scientists do in the inquiry process when left on their own (Kozma, 2003). As a result, unlike scientists’ inquiry, students’ inquiry requires considerable guidance. This notion of scaffolding is based on Vygotsky’s concept of the zone of proximal development (ZPD). ZPD refers to the distance between the actual developmental level, as determined by independent problem solving, and the level of potential development, as determined through problem solving under adult guidance or in collaboration with more capable peers (Vygotsky, 1978).

The implication of the concept of ZPD for students’ scientific inquiry process is that scaffolding must be provided to address students’ lack of subject matter knowledge, sophisticated strategies, and self-monitoring skills (Bransford et al., 1989; Chi et al., 1989; Clement, 1991; Lewis & Linn, 1994). The scaffolding can be provided in the form of interaction with more knowledgeable others, such as mentors (like scientists or expert teachers), or in the form of similar technological tools and techniques that scientists use in scientific inquiry. Examples of these technological tools are phenomenaria (see, e.g., White, 1984; White & Horwitz, 1987)—which are areas designated for the specific purpose of presenting phenomena and making them accessible to scrutiny and manipulation (Perkins, 1992)—and cognitive and social tools for supporting science practices (Kozma, 2003), such as the theory-building scaffolds in Knowledge Forum (Scardamalia & Bereiter, 1999).

In short, scaffolding is essential in authentic science learning in order to bridge the gap between students’ knowledge and skills and those of scientists. In a classroom, the support naturally comes from the teacher. However, it is really a challenge for the teacher to split his or her time among so many groups, especially when the class is large. Hence, there has been considerable interest among researchers and educators in exploring the use of technology to provide support for problem solving.

Examining the Role of Technology in Problem-centered Learning Environments

We will examine three problem-centered learning approaches commonly adopted in science learning: problem-based learning (PBL) developed by Barrows, CoVis (Learning through Collaborative Visualization) developed by Northwestern University, and knowledge building developed by Scardamalia and Bereiter. We will consider their strengths and challenges in the adoption of technology with respect to the three conditions of science learning identified earlier.

Problem-based Learning

PBL is an approach that was originally developed for medical schools by Barrows (1986). It is a robust constructivist process shaped and directed primarily by the student, with metacognitive coaching from the teacher. The key features of PBL are initiating learning with a problem, exclusive use of ill-defined problems, and teacher as metacognitive coach. PBL advocates a ten-step inquiry process in which students work collaboratively to solve authentic problems, with the teacher facilitating, as follows (Savery & Duffy, 1995):

  1. Problem presentation
  2. Hypothesis and idea generation
  3. Identification of relevant facts known and of learning issues
  4. Investigation and gathering of information
  5. Analysis of results and information
  6. Presentation of information and analysis to team members
  7. Negotiation and revision of learning issues
  8. Repeated information search and gathering, data analysis, and result presentation
  9. Generation of solutions
  10. Reflection and evaluation

These ten steps in the problem-solving process resemble the inquiry process of authentic science learning. As such, although PBL was not originally developed for secondary school science learning, it has since been widely adopted and adapted for this purpose (see, e.g., Gallagher et al., 1995; Greenwald, 2000; Chin & Chia, 2000).

In a case example cited by Gallagher and colleagues (1995) from their Science Problem-based Learning Experience project, students were assigned an ill-structured science problem on corrosive chemical spill presented in the form of a narrative story. The students analyzed the problem statement and established a learning agenda. This activity was scaffolded with questions which helped organize discussion, such as: What do you know? What do you need to know? How can you find out what you need to know? This process of identifying the learning issues was facilitated by a “Need to Know” board on which students recorded their progress as they worked through the problem. Open-ended questions were also given to prompt students to inquire deeply into their understanding of the problem. Experiments using a wide variety of appropriate materials to model a real-life chemical spill provided the means through which students could find the answers to their questions. The students recorded all these activities in their problem log, which was in the form of a journal modeled after the traditional science laboratory notebook. Similar scaffolds were provided in other PBL science projects reported, such as Greenwald’s (2000). Besides these scaffolding structures, the main support was the teacher who facilitated the problem-solving and metacognitive processes.


The CoVis project, launched in 1992, was an educational networking testbed funded by the National Science Foundation that established a scientific learning collaboration involving students, teachers, scientists, informal science educators, and educational researchers. It was developed to promote scientific understanding through the use of scientific visualization tools in a collaborative context (Pea et al., 1994; Edelson et al., 1995b; Edelson et al., 1997). Its aim was to transform science learning to better resemble the authentic practice of science.

In the CoVis learning environment, groups of students work collaboratively on authentic science projects using local phenomena such as weather, climate, and global warming as anchors. In small groups, students identify research tasks related to these themes, such as conducting weather “nowcasts” and forecasts, studying the effect of coastlines on local temperatures, and investigating the possibility of global warming (Edelson et al., 1995b; Edelson, 1997).

The key feature of CoVis is the use of scientific visualization— a technique employed by scientists for data analysis—for knowledge construction. With the aid of visualization tools, students engage in scientific investigations like scientists do, taking advantage of the strengths of the human visual system to help them in making interpretations and in data analysis. The tools provide the springboard for students to pose challenging research questions, investigate the questions through direct manipulation of data, and create their own graphical images to help them generate as well as demonstrate conclusions (Edelson et al., 1995b). Examples of these visualization tools are Weather Visualizer (Fishman & D’Amico, 1994) and Climate Visualizer (Gordin et al., 1996). Weather Visualizer, for instance, supplemented with weather graphics tools, enables students to examine current weather conditions and to view a range of images displaying the weather conditions for the most recent hour. The Weather Graphics tools enable students to draw their own weather maps with traditional weather symbols to make predictions and explain their understanding of the weather to others. These tools support students in the inquiry process, allowing them to make predictions and demonstrate to others what they have learned.

Scaffolding tools are built into these visualization programs to bridge the gap in expert knowledge on the part of students. Often, scientists approach these tools already possessing a wealth of expert knowledge. Students need to have this knowledge before they are able to make meaningful interpretations of the visualizations they see. Hence, the interface of the visualization tools is adapted to provide support in the form of access to data that can be viewed and manipulated. For example, in the Climate Watcher program (Edelson et al., 1997), contextual information about geography, units of measurement, and mapping of numerical values to colors is provided to support students in the inquiry. Other forms of supporting tools include books, the Internet, and scaffolding provided by teachers and scientist mentors through verbal support, the design of activities, and the selection of useful data and information for students.

Another tool that scaffolds students’ inquiry is the Progress Portfolio, which engages students in reflective inquiry as they work with complex data sets (Loh et al., 1998). It helps students combine data and interpretations gathered from various sources, such as the visualizations and the Internet, evaluate and reflect their progress, coordinate shared understanding among team members, and replan their inquiry.

Another significant technological tool that is provided is the Collaboratory Notebook. Modeled closely after the scientists’ notebook, the Collaboratory Notebook facilitates collaboration and communication among students, allowing them to create shared work spaces, author pages in the notebook individually or in groups, and read pages authored by others. It provides a mechanism for students to record their activities, store artifacts, and share the work processes with team mates. There is an individual function that acts like an individual notebook for students to record information for their own use. There is also a group notebook function that allows access to students in the same group so as to encourage collaboration, and students can contribute ideas that they wish to share with each other, make comments, or ask questions. The notebook pages may be linked together through hyperlinks, indicating the semantic relationship between them. The Collaboratory Notebook also includes a number of inquiry and metacognitive supporting features such as predefined page and link types. The page types include questions, conjectures, evidence for, evidence against, plans, steps in plans, and commentaries. These features provide students with a framework for conducting and communicating about the inquiry process and encourage them to be systematic and reflective.

Thus far, this learning environment has been used by 50 schools in the United States, and hundreds of schools have utilized the project’s geosciences web server for curriculum support and to access project and activity ideas and analytical tools. Although this project was completed in 1998, research is being continued under the auspices of the Center for Learning Technologies in Urban Schools and a number of other research projects in the Learning Sciences Program at Northwestern University.

Knowledge Building

Knowledge building (KB) is a constructivist approach which focuses on the production and improvement of ideas of value to the community through acts of collaboration such that the accomplishment is greater than the sum of the individual contributions and part of a broader cultural effort (Scardamalia & Bereiter, 2003). It goes beyond the development of skills and changes in beliefs and attitudes, treating learning as a byproduct. Its thrust is to enculturate students into the “way of practice” in which knowledge is advanced, which it believes is an essential skill that is needed in the knowledge society. Its emphasis on advancing the frontiers of knowledge of the collective is favored by science educators, as its process resembles the practices of scientists in theory building. It shares many characteristics of authentic science learning, such as advancing the community’s knowledge as well as emphasizing collaboration and communication, with its key features being the provision of supports for knowledge construction, collaboration, and progressive inquiry. These supports are provided through technological forms of mediation, in particular the computer-supported collaborative learning (CSCL) system Knowledge Forum, in the following ways:

  • Knowledge construction supports that allow students to present their ideas (as notes) in the system’s database, make connections between related notes, and view information from different perspectives. These supports thus make learning a tangible and intentional activity.
  • Collaboration supports which promote user interaction through the public nature of the database of messages (notes) as well as facilities such as “build on” to encourage collaboration.
  • Progressive inquiry supports such as theory-building scaffolds which lead students toward activities that focus them on cognitive goals.

In the KB environment, students work on problems that are principle based, such as: Why will a child resemble one parent in some respects, the other in others, and some more distant relative in yet other respects? How do cameras work? Why do leaves change color in autumn? (Scardamalia et al., 1994; Scardamalia, 2002). While these problems may not seem “authentic,” the authenticity stems from their relevancy to students, as they are generated by the students themselves. Besides, authenticity in this case comes from the real practice of theory building in science. Students post on Knowledge Forum the problems they identify and then build theories to explain the problems by posing questions, hypothesizing, consulting reference sources, explaining, and critiquing.

Scaffolding this theory-building activity are scaffolds that take students through the steps of collaboratively building and verifying a theory (Bereiter et al., 1997). The scaffolds are sentence openers which help students articulate their intentions to others, such as “I Need to Understand” (INTU), “My Theory” (MT), “New Information” (NI), “Problem” (P), “Comment” (C), and “What We Have Learned” (WWHL). These scaffolds can be customized to match the activity that students are engaged in, whether it is theory building or problem solving.

Besides these scaffolds, six facilities supporting collaboration are built into Knowledge Forum, which are build on, quoting, annotation, shared authorship, published status, and rise above. For example, students could use the build-on facility to extend, question, or comment on their peers’ ideas, the quoting function to reference peers’ work, the shared authorship function to create shared notes among themselves, or the rise-above function to gather theories and ideas that have been presented and synthesize them into new understandings. Knowledge Forum also supports multiple modes of representation, such as drawing, further mediating the knowledge-building process.

Since its beginning in 1986, Knowledge Forum has been expanded for use in various learning situations, such as in workplaces and in educational settings, ranging from primary grades to graduate school in a variety of locations across Canada, the United States, Japan, Finland, and the Netherlands. It is an integral part of the Schools for Thought program in the United States and also one of four beacon technologies being developed for the TeleLearning Network of Centers of Excellence. Since then, other CSCL systems have been developed to support similar knowledge-building approaches.

Comparison of the Three Problem-centered Approaches

All three learning environments are centered on authentic problems. However, there are differences in the design of the problem situations and their representations. In PBL, the problems are real-life problems that require solution. In order to ensure relevancy to the syllabus, the problems are often canned. The design of the problem and its representation is highly dependent on the creativity of teachers. Any use of technology is most probably for the purpose of presentation.

In the CoVis environment, the visualization program provides the authentic context in which the problem arises. These authentic visualization programs, which are modeled after those that scientists use to solve weather and climate problems, provide students the starting point for posing challenging questions for research. Hence, the use of technology can be the context in which students work.

KB problems are described as problems of understanding. The problems are identified and generated by students. In this learning environment, the use of technology for setting the context is not the focus. The problem generation arises mainly from students’ interaction with their surroundings and from their own experiences. This is, however, only possible for elementary science. In higher-level science, students may not have direct experience with the phenomenon that is being studied, such as space. In this situation, technology may be useful for setting the context and providing students with the kinds of experiences that scientists have accumulated.

We conclude from the above that the affordances of technology should be tapped to provide the context in which science is appropriated. Besides being used as a tool to present the situation, technology could also be used to present the situation within which scientific practices arise and which scientists have experienced.

Experiential learning is important. It provides the basis on which meaning arises. Hence, students should have access to the inquiry process which scientists employ to solve problems and build theories. The problem-solving process of PBL resembles closely scientists’ inquiry process. However, this arduous process of inquiry needs to be supported in order to help students make sense of the messy and unstructured problems. This mediation is often left to the discretion of teachers, who have to find the balance between giving too much support that it compromises intersubjectivity and insufficient support that leaves students frustrated.

In the CoVis environment, support for inquiry is provided through the use of visualization tools that the scientific community deploys. These tools provide the support to help students generate problems, develop their own plans for identifying and exploring appropriate data, and create their own artifacts to generate and demonstrate results. Such systems provide the necessary experiences for meaningful science learning to take place while scaffolding the process of inquiry.

In KB, the inquiry process focuses on talk. In Knowledge Forum, scaffolds are provided to guide students in the ways of thinking in theory building and, hence, to support the process of theory building. However, lacking in KB is the hands-on experience that is necessary for meaningful knowledge to be built.

In conclusion, technology could provide the affordances in experiential learning by way of authentic tools that scientists use, or it could support the cognitive process by which scientists solve problems.

Interaction is key to learning and problem solving. It is through interaction that meaning and knowledge are constructed. It is on the social plane that ideas are first encountered before being internalized. Technology can be used to provide the support for interaction in two ways: providing the physical presence of the object of inquiry and supporting the collaborative talk that takes place in problem solving.

In PBL, interaction plays an important role throughout students’ problem-solving process—from hypothesis generation to reflection and evaluation. To facilitate interaction, there must be a common ground on which students work. The anchor problem provides this common ground. However, the common ground may be abstract in cases where there is no physical object of inquiry for students to work with. Hence, technology may provide the common physical environment in which students can perceive and work together. In PBL, while interaction is one of the key features, there is no particular tool used to support interaction. It depends heavily on the teacher’s ability to provide the facilities. Where interaction occurs face to face, ideas are usually lost because of the transient nature of talk. Furthermore, these face-to-face discussions are usually dominated by the more capable or “louder” students in the group. Some PBL environments may make use of technology such as synchronous chat or asynchronous discussion boards to solve this problem. However, the synchronous chat facility is messy and it is difficult to follow the linear utterances in a nonlinear discussion. Hence, when students look back at their discussion, they may have difficulty making sense of it.

In the CoVis environment, the facility for interaction is built into the learning environment. The visualization tool anchors the problem-solving process, and hence its images are used as a basis for discussion between members in the community. Moreover, the Collaboratory Notebook allows students to share information, record activities, and store artifacts, thus making inquiry explicit. Hence, the system supports the social construction of knowledge.

Like CoVis, KB has a collaborative facility, called Knowledge Forum. Of the three approaches, KB places the most emphasis on the support of technology for collaborative learning. Knowledge Forum provides a public space for students to post notes (ideas). This space can be seen by all community members, and all members can build on the notes posted. Scaffolds provided by teachers guide students in their response to their team members so that the discussion can be more fruitful. Being asynchronous, the facility allows students to think and reflect on others’ ideas before building on them. Since all notes are displayed on the discussion forum, it is less likely that any student would dominate the discussion. Furthermore, the less verbal students have more time to formulate their utterances. The chances of off-task talk are also lessened.

In short, technology can provide the affordances that support interaction in the form of the physical object of inquiry and the communication process.

Framework for CSCL-mediated Problem-centered Science Learning

From the examination of the three learning environments, we have identified the strengths and challenges of each of the pedagogies in their use of technology to support problem-centered science learning.

Of the three, PBL has a good and structured problem-solving process. However, its main challenge is the lack of technology supports to mediate the process. It is often left to the creativity of teachers in providing these supports. By contrast, the other two learning environments have good technological supports. However, in these two environments the problem-solving process is either not clear (as in CoVis) or problem solving is not the key focus (as in KB, where the focus is on knowledge building). We propose that the strengths of these two approaches could be adopted for PBL. For instance, in problem presentation, technology could be deployed to provide the context. In this case, we are referring to something more than the mere use of technology as a presentation tool for the problem scenario; we are talking about the use of technology as the context in which the problem situation arises, as in CoVis.

In terms of the problem-solving process, the strength of CoVis and KB lies in the use of technology to support the process. PBL is often criticized for its strong focus on the task (i.e., solving problem), which leads to shallow constructivism as students are not motivated to inquire deeply into the concepts unless required to do so by the task. In this respect, the focus on knowledge building in the KB approach helps nudge students to inquire deeply into their understanding with the aid of theory-building scaffolds, which are the key feature of Knowledge Forum. In identifying and exploring learning issues, students could use a KB system to guide them in deepening their understanding before they work on solving the problem. Such CSCL systems could mediate the enculturation of students into the practices by which scientists build their knowledge in order to solve problems.

Another key consideration in providing technology support to problem solving is the utilization of authentic tools modeled after the real tools that scientists use, such as the visualization tools in CoVis, so as to provide the experiences that students need in making meaning of scientific artifacts.

While all three learning environments focus on interaction in the learning process, the support provided for interaction varies. In PBL, there is no one specific technology that supports interaction, and it is often up to the teachers to provide a tool suited to the purpose of problem solving. A suitable tool could be adopted from CoVis or KB, such as the Collaboratory Notebook in CoVis or the Knowledge Forum of KB.

To sum up this discussion, we propose that technology can be used to support problem-centered learning environments in the following ways:

  • Context: Technology can provide the context which embodies the scientific knowledge and practices. In this aspect, technology is not just the carrier of the context but also the context in which the problem arises.
  • Experience: Technology can provide authentic tools for scientific inquiry. It can also provide the scaffolding for the practices of inquiry.
  • Interaction: Technology can provide the common ground on which group members can discuss the problem. It can also provide the public space in which students collaborate, thereby supporting intersubjectivity. It should provide scaffolds that appropriately guide students in the pattern of communication at the different stages of the inquiry process (for knowledge building or problem solving).

To summarize, in this chapter we have discussed the conditions for science learning and the role of problem solving in science learning. We have also explored three popular problem-centered science learning environments and their use of technology to support science learning. We recognize that, while PBL has a structured process that supports students in solving problems, the use of technology to mediate the process is lacking. Hence, we propose adopting some of the uses of technology in CoVis and KB to provide the context and support interaction in PBL. We propose a framework in which technology can be used to support problem solving based on the three conditions for science learning: context, experience, and interaction. What might be needed now is to provide empirical evidence to support this framework and to further refine it.


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