20.4 Tools for knowledge-building communities

In an article on the design of collaborative learning environments, Pea (1994) describes three metaphors of communication:

1. Communication as transmission of information. This is the dominant idea that communication conveys a message over time and distance from one person to another.
2. Communication as ritual. This refers to the participation and fellowship involved in the sharing of certain forms of expression. Participation in the performing arts such as dance, theater, and music, either as a performer or as an audience member, involves ritualistic aspects of communication. The content of the message is often less important than the medium and style of expression, informing the audience and strengthening the common bond of group membership. Ritual communication emphasizes the sharing and communal functions of communications, allowing groups to maintain a sense of identity and coherence.
3. Communication as transformation. Both the "sender" and "receiver" of information are transformed as they share a goal of learning and knowledge generation. Participants in transformative communication open themselves up and expect change to occur as part of the process. Communication thus serves as a stimulus to inquiry, observation, and reflection, Transformative communication combines aspects of knowledge sharing and group collaboration, with an emphasis on new experience and learning (Pea, 1994, pp. 287-88).

Transformative styles of communication are characteristic of learning communities, whether in schools, classrooms, workgroups, or families. Pea (1994, p. 289) notes that a number of researchers are presently moving from a cognitive-science base toward a social-cognition framework in their attempt to understand the symbols and discourses of learning communities. Cognitive apprenticeships (see 7.4.4) are an example, as are Brown's (1994) communities of learning and Scardamalia and Bereiter's (1994) knowledge-building communities. The common notion is that groups of people share a goal of building meaningful knowledge representations through activities, projects, and discussion.

Transformative communication seems not to be emphasized in Sherlock or Schank's case-based scenarios. The goal is not mutual change between communicating parties, but more computer-directed change in the student. Similarly, the PBL model expects the students to be transformed, playing roles of both senders and receivers, but the tutor is expected to remain basically detached, monitoring, coaching, and externalizing higher-order thinking. A transformative or learning-community view would suggest that the instructor is a part of the learning community and should be an active, learning participant in the community.

The models described below are designed as tools or helps to support knowledge-building communities.

20.4.1 Epistemic Games

What do learning communities do? Collins and colleagues (Collins & Ferguson, 1993; Morrison & Collins, 1996) would respond that learning communities generate new knowledge by participating in certain defined cultural patterns or forms. The products of this work they call epistemic forms and adhere to defined structures accepted by the community. Epistemic forms contain new knowledge. Working together to generate these forms is called participating in epistemic games. The game is the set of rules or conventions that can be followed in generating a given epistemic form.

Collins and Ferguson (1993) suggest three important types of epistemic games, along with several subcategories shown in Table 20-2:

1. Structural analysis games. What are the components or elements of a system?
2. Functional analysis games. How are the elements in a system related to each other?
3. Process analysis games. How does the system behave?

Each of these general game types is found in every subject matter. Additional knowledge-building games and activities are found in Collins and Ferguson (1993) and in Jonassen, Bessner, and Yacci (1993). Domain-specific games take on very specific forms, for example, designing a research study or developing a time-line for a project. As games become more domain-specific, they typically become more valuable to participants of that work area.

Morrison and Collins (1995) argue the following:

1. Our culture supports numerous ways of constructing knowledge-some domain-specific, and some more general.
2. These different ways of constructing knowledge, which we call epistemic games, are culturally patterned.
3. Different contexts (communities of practice) support different ways of knowing, and therefore different kinds of epistemic games. People are more or less fluent epistemically, depending largely on their contextual experiences, i.e., the sorts of subcultures and communities of practice in which they have participated.
4. An important goal of school is to help people become epistemically fluent, i.e., be able to use and recognize a relatively large number of epistemic games.
5. A key question to ask about particular environments is whether they tend to foster (or inhibit) epistemic fluency ... (Morrison & Collins, 1995).

The epistemic-game framework can serve as a language for describing learning activities within constructivist learning environments (see 23.3, 23.4) (Wilson, 1996).

According to Collins and Ferguson (1993, pp. 27-28), the playing of epistemic games exhibits the following characteristics:

1. There are constraints to playing. In playing a list game, for example, the items listed should be similar (that is, on the same scale or level) and yet distinct from one another. The lists should be comprehensive in their coverage (that is, leaving nothing important out), yet brief and succinct. These constraints can serve as the rules or criteria we use to judge the quality or appropriateness of a new list.
2. There are entry conditions that define when and where game playing is appropriate and worthwhile. The list game, for example, becomes appropriate in response to a question such as "What is involved in XT' or "What is the nature of XT' where X can be decomposed or analyzed in simple fashion.
3. Allowable moves are the actions appropriate during the course of the game. List moves include adding a new item, consolidating two items, and rejecting or removing an item from consideration.
4. Players occasionally may transfer from one game to another. For example, a list game may shift to a hierarchy game when the structure of list elements begins to assume a form containing subcategories.
5. Game playing results in the generation of a defined epistemic form, e.g., lists, hierarchies, processes, etc.

The Collins framework of epistemic games and forms provides a structure and language to articulate what teaming communities do when they work together to generate new knowledge. Such a framework can become useful to understanding classroom and workgroup processes, but it also can serve a prescriptive or heuristic role for teachers and designers. Many teachers complain that they want to teach critical thinking, but they have failed to find a suitable set of strategies.

Epistemic games can be useful to teachers in either of two ways:

1. Using the framework as a diagnostic or interpretive device. Existing learning activities can be interpreted from an epistemic-game perspective, providing valuable insights into processes and interactions.
2. Targeting game playing as a learning objective. Our students (Sherry & Trigg, 1996) are presently developing learning materials aimed at teachers, encouraging them to engage students directly in epistemic games.

While empirical research in this area is only in beginning stages, epistemic game playing seems a promising way to think about knowledge-generating activities. It provides a needed link between cultural forms and cognitive-epistemic points of view. Research must address many questions, such as the extent to which the games encourage knowledge generation rather than rote learning, and the types and amount of scaffolding that are desirable in various learning situations. One could imagine students mindlessly developing a list or guessing at causes where no new knowledge was generated. Rules need to be developed for playing games in a way that is conducive to knowledge generation.

20.4.2 Tabletop

Tabletop (Hancock & Kaput, 1990a; Hancock & Kaput, 1990 b; Hancock, Kaput & Goldsmith, 1992; Kaput & Hancock, 1991) is a computer-based tool that allows users to manipulate numerical data sets. By combining features of what Perkins (1992a) calls symbol pads and construction kits, Tabletop provides a "general purpose environment for building, exploring, and analyzing databases" (Hancock et al., 1992, p. 340).

The program allows the user to construct a conventional row-and-column database (see 24.9) and then to manipulate the data by imposing constraints on the data with animated icons. Double clicking on an icon displays the complete record for that icon. Summary computations can be represented in a variety of formats, including scatter plots, histograms, cross tabulations, Venn diagrams, and other graphs.

Tabletop is a product of two major design goals: intelligibility and informativeness. Hancock et al. (1992) compare the role of the individual icons, which allow the learner to identify with them physically, to the role of the Turtle in Papert's Logo programming, language. They theorize that the icons provide a "pivotal representation in which kinesthetic/individual understanding can ... be enlisted as a foundation for developing visual/aggregate-understanding" (p. 346).

Intelligibility and accessibility are also supported by other aspects of the program. For example, the user constructs and can modify graphs through a series of reversible steps and always has the full database in view. Thus, the user can observe the effect each new constraint has on each member of the database (a feature that also contributes to the program's informativeness).

The intelligibility and informativeness of the program support the learner in negotiating meaning in a real-world iterative process of construction, question asking, and interpretation. Hancock et al. (1992) describe a case in which a student used Tabletop to graph a hypothesis about data that had not yet been entered in the database.

Tabletop was initially piloted on students aged 8 to 15, and with students aged 11 to 18. The pilot studies provided insight into the kinds of questions, problems, and thinking processes that students engage in during all phases of data modeling and confirmed Hancock et al.'s (1992) belief that data creation and data analysis are inextricably intertwined. The description of the thinking students engaged in clearly reveals that in the "data definition phase" the students were drawing on the "raw data" of their individual experiences.

Tabletop was clinically tested on an eighth-grade class and a combined fifth- and sixth-grade class in six units during one school year. Clinical observation clearly demonstrated that Tabletop can help students develop their understanding of many kinds of graphs. However, students were less successful in:

a. Using that graph to characterize group trends

b. Constructing the graph in order to generate, confirm, or disconfirm a hypothesis

c. Connecting the graph with the data structures necessary to produce it

d. Embedding the graph in the context of a purposeful, convergent project (pp. 361-62)

Tabletop is not designed to be a self-contained program for developing skills and concepts in data modeling. Indeed, the developers envision it as a tool in a collaborative learning environment (see 7.4.9, 23.4.4), with students helping each other and receiving appropriate scaffolding and coaching from the teacher, as in a cognitive apprenticeship model (7.4.4, 20.3.1). In the pilot and clinical tests of the program, students sometimes were unable to perceive - even with some coaching and scaffolding - that they could not create particular graphs because they had not coded the data in a relevant way. Because of time constraints, the teacher sometimes scaffolded learning by adding a relevant data field "between sessions" (Hancock, Kaput & Goldsmith, 1992, p. 350). Although the researchers imply that it would have been preferable for the students to discover the solution for themselves, research must still address the issue of whether, when, and how much scaffolding of this sort is beneficial.

As noted above, while Tabletop was generally effective in helping students understand a variety of graphs, it was less effective in helping students use the graphs to support general conclusions. Like Duffy and Roehler (1989), Hancock, Kaput, and Goldsmith (1992) found that learning and incorporating new strategies into one's repertoire requires much time. They concluded that I year was insufficient time for students to develop "authentic, well-reasoned data-modeling activities" (p. 353). Even after a year, students' projects lacked coherence and purpose, beginning "without clear questions, and end[ing] without clear answers" (p. 358).

Two lessons can be learned from Tabletop. First, it is an excellent example of a tool that allows ideas and content elements to be manipulated, tested, explored, and reflected upon. Students working with Tabletop have a qualitatively different experience than they would completing exercises at the back of the chapter. Second, students using these kinds of tools need well-designed supports, meaningful goals and projects, and carefully attending teachers to realize the tool's potential. Even when conditions are favorable and care is given to design and support, students cannot be expected to reach higher levels of schema acquisition and problem-solving skill simply by having experience with the tool. Learning environments that allow projects, data manipulation, and exploration require continuing attention to design in order for students to achieve learning gains (See Jonassen, 1996, for a discussion of other tools useful to learning communities.)