As opportunities for distance learning or computer-mediated support of group model building efforts increase, it is important for educators, managers, and practitioners to know how they can use computer-mediated technology to promote effective interaction. A discussion of interaction based on type of task and "richness of media" (Daft & Lengel, 1987) can provide a useful framework for considering how and when to utilize specific types of technology support for group processes (McGrath & Hollingshead, 1994).
This paper summarizes significant research on brainstorming in both computer-mediated and non-mediated forms, as well as limitations of the current research. Recommendations for the most effective use of brainstorming will be presented, including directions for future research.
Findings are of interest to managers and developers
making media choice decisions for using network-based groupware
or CSCW tools, as well as educators interested in promoting optimal
creativity enhancement with individuals or groups.
Recent research in system dynamics has focused on the increasingly important role of small groups in model-building as an aspect of team learning (Vennix, 1996), groupware applications (Gary & Charyk, 1996), and policy development (Huz, Andersen, Richardson, Boothroyd, 1996). This research reflects the broader trend of burgeoning interest in effective small group processes in teams and work groupsóboth with and without technological supportóin various fields. Concomitantly, there is an increasing emphasis on developing appropriate thinking and problem-solving skills for the twenty-first century. Systems thinking and system dynamics represent important cognitive skills (Richmond, 1993, 1994), whose development is a major concern at all levels of formal education and professional level training.
In addition to research on domain-specific approaches to problem-solving, and the specific cognitive skills proposed by Richmond (1993), an important need exists for developing the successful creative thinking skills of individuals and groups engaged in generative tasksóof which idea generation is oneóthat are part of a problem-solving or decision-making process (Hollingshead & McGrath, 1995). For example, Vennix (1996) cites at least one task typeógenerating variables to include in the modelóin which brainstorming techniques can be utilized by individuals to facilitate group input into the process of building a system dynamics model.
Although there are many specific tasks involved
in group modeling efforts, for the purpose of this paper, they
can be divided into two major types: a) generating information
and b) evaluative tasks (Vennix, 1996). Similarly, although both
types of cognitive tasks are important, only generative tasks
will be considered here, focusing on ways of optimizing idea or
information generation tasks for group model-building. In addition,
while there are many other structured techniques for promoting
generative task performance, only brainstorming research will
be considered here, in terms of comparing interacting and nominal
groups (individuals working alone whose input is later pooled,
then corrected for redundancy).
Why Study Brainstorming?
Although the group brainstorming technique was used in industry during the 1930s and 1940s (For a historical review, see Mayer, 1983), research interest in brainstorming was initiated mainly by Osborn's claim (1957) that groups using the technique would generate nearly twice as many ideas as an equal number of individuals.
Brainstorming research provides the largest body of empirical research on any idea generation technique, thereby providing the richest source of historical data. Research related to brainstorming can be summarized into two phases: a) Traditional brainstorming research, including early field studies and experimental research comparing traditional brainstorming groups with face- to-face and nominal groups; and b) electronic brainstorming research, beginning in the early 1980s, and conducted within the research agendas of Group Decision Support Systems (GDSS).
Results from Traditional Brainstorming Research
Since the first laboratory study comparing brainstorming in the nominal and interacting group conditions (Taylor, Block, & Berry, 1958), findings have generally disconfirmed Osborn's claim. When compared on quantity of pooled ideas, individuals have outperformed verbally-interacting, or face-to-face groups (Diehl & Strobe, 1987). This result has been widely replicated. In a review of 22 studies, 18 found that nominal groups outperformed face-to-face verbal brainstorming groups based on quantity of ideas generated. Only four, all of which were conducted with groups of two (dyads), found no difference (Diehl & Strobe, 1987, p. 497-498).
There have been two consistent findings in the brainstorming research: 1) In nearly all cases, nominal groups of equal size produced significantly more ideas than face-to-face groups; and 2) Face-to-face groups do not generally experience the increases in number of ideas that accompany increases in nominal group size (Valacich, Dennis, & Nunamaker, 1992).
Three Major Theories for Explaining Group Decrements
Research conducted to investigate mechanisms underlying the productivity losses associated with verbally interacting groups has focused on three main theories:
a) social loafing or free-riding (Latané, Williams, & Harkins, 1979), which has not received much support, since brainstorming is a considered a relatively low cognitive demand task, and therefore isn't thought to encourage social loafing (Diehl & Strobe, 1987);
b) evaluation apprehension, (Collaros & Anderson, 1969; Lamm & Trommsdorf, 1973) which refers to participants' unwillingness to contribute to the group for fear of negative evaluation of their contribution, which has received some research support (Diehl & Strobe, 1987); and
c) production blocking, which refers to the phenomenon that unless some form of structured turn-taking is observed in face-to-face groups, with only one person talking at a time, communication breaks down. Production-blocking theory (Lamm & Trommsdorf, 1973) has received the most empirical support for factors underlying group process losses in brainstorming research, and is generally accepted as the strongest explanatory factor for decrements in group brainstorming performance in terms of numbers of ideas generated (Diehl & Strobe, 1987).
Research Into Electronic Brainstorming - GDSS Research
In the early 1990s, a second round of research interest was initiated when studies within the field of Group Decision Support Systems (GDSS) began comparing electronic brainstorming groups to nominal groups and face-to-face interacting groups. In this stream of research, electronic brainstorming groups have frequently outperformed both other brainstorming conditions (e.g., Dennis and Valacich, in 1994; Gallupe, Bastianutti, and Cooper, 1991; Valacich, Dennis, & Connolly, 1994). However, the results have not been as unequivocal as earlier results with non-computer mediated brainstorming. In the Hollingshead and McGrath (1995) review of eight (8) idea generation studies, electronically interacting groups outperformed face-to-face groups on number of ideas in four (4) studies and four (4) showed no difference on quantity measures.
Limitations of Generalizing from Electronic Brainstorming Research
Many issues factor into discussions of GSS support, including media type, task type, synchronous/asynchronous combinations of time and place, and many individual or group variables. In general, comparisons between the use of GSS versus non-GSS treatments in electronic brainstorming are subject to the limitations of confounding variables often found with "black box" approaches, that compare a technology versus non-technology condition. Additional difficulties in comparing results can be attributed to the different research agendas and technology designs associated with the institutions conducting the GDSS research (Bostrom, 1992).
Limitations of Quantity and Quality Measures
Both in early brainstorming, as well as more recent GSS studies, the most common performance measure has been the quantity of ideas generated. Most studies have used a measure of total quantity of ideas. When studies are compared on performance measures of quality, the conclusions are not so clearly drawn. Total quality is among the most common quality measurements. However, in 1972, Bouchard showed that, when many ideas was generated, the pool was likely to contain more ideas of high quality as well. Since the total quality measure correlates positively with the quantity of ideas generated, the current quality measures provide little additional value in generalizing about idea quality, since many studies contain either no quality measures at all, or are highly specific types of problem.
Task/Media Richness Fit
Media can be classified along a continuum of information or media "richness," with face-to-face interaction as the richest form, then video and audio modalities, to text-only media. (Daft, Lengel & Trevino, 1987). McGrath & Hollingshead (1994) provide some guidelines for applying specific media technology within the context of specific task and media variables, using research based on the fit between task type and media richness. Based on best evidence available, groups should reserve limited face-to-face meeting times for evaluative tasks, for which the "richness" of the medium offers a better fit.
Specifically, to promote the most effective idea generation, groups should use a combination of either a) nominal groups or b) text-based systems that allows simultaneous input by group members; Groups can then meet for later evaluation using face-to-face structured turn-taking interaction, such as a "round-robin." If face-to-face interaction is not possible, rich media like video conferencing would be the next best alternative. Since limited controlled research has been done comparing the various of combinations "rich" forms of mediated interaction like video conferencing, it is not possible to generalize conclusively. As a rule of thumb, however, the richer the medium of interaction, the better the fit for more evaluative or negotiated tasks.
Directions for Future Research
Generative techniques can be used at any point in a group process (creative problem-solving or decision-making) when it becomes apparent that there is a need for more possibilities than are currently under consideration, such as a group impasse in reaching consensus. These techniques can be used for planning tasks, for generating possible courses of action and consequences of proposed actions, as well as generating possible models to build and variables to include. Brainstorming for generative tasks is best supported by nominal groups or the use of simultaneous text-based computer interaction .
Dissatisfaction with the limitations of current outcome measures and research focus have been expressed (e.g., Nagasundaram & Bostrom, 1993). Some researchers have focused on the capacity of GDSS software to increase individual creativity (e.g., MacCrimmon & Wagner, 1994) or the analysis of the types of ideas generated using different types of idea generation techniques in addition to brainstorming, or other improvements in research methodology (Nagasundaram & Bostrom, 1993; Massetti, B, 1996).
Research into distributed media that support the use of shared representation spacesómuch from the field of Computer-supported Cooperative Work (CSCW)ó suggests it may be well suited to other phases of system dynamics modeling tasks. Since technological advances for sharing and viewing models over the World Wide Web will continue to develop, more fully interactive shared media spaces will be even more cost effective and readily available. The goal, of course, will still be to make group interaction and instructional decisions based on the best available information from research and practice, instead of allowing available bandwidth to drive the use of rich media in situations in which it may be unnecessary, or even counter-productive to the interaction goal and task type.
Bostrom, R. P., Watson, R. T., & Kinney, S. T. (Eds.). (1992). Computer augmented teamwork: A guided tour. New York: Van Nostrand Reinhold.
Collaros, P. A. & Anderson, L. R. (1969). Effect of perceived expertness on creativity of members of brainstorming groups. Journal of Applied Psychology, 53, 159-163.
Daft, R. L. & Lengel, R. H., & Trevino, L. (1987). Message equivocality, media selection, and manager performance: Implications for information systems. MIS Quarterly, 11, 355-366.
Dennis, A. R. and Valacich, J. S. (1994). Group, sub-group, and nominal group idea generation: New rules for a new media? Journal of Management. (20) 4, 723-737.
Diehl, M. and Stroebe, W. (1987). Productivity Loss in Brainstorming Groups: Toward the Solution of a Riddle. Journal of Personality and Social Psychology, 53 (3), 497-509.
Gallupe, R. B., Bastianutti, L. M. and Cooper, W. H. (1991). Unblocking brainstorms. Journal of Applied Psychology, 76(1), 137-142.
Gary, M.S. & Charyk, C. (1996). Using groupware technology to facilitate team model building and learning. Proceedings of the 1996 International System Dynamics Society Conference. Vol. I, 170-173.
Hollingshead, A. B. & McGrath, J. E. (1995). Computer-assisted groups: A critical review of the empirical research. In R. A. Guzzo, E. Salas & Associates. Team effectiveness and decision-making in organizations, (pp. 46-78), San Francisio: Jossey-Bass Publishers.
Huz, S., Andersen, D., F., Richardson, G. P., and R. Boothroyd. (1996). Evaluating Group model building in mental health and vocational rehabilitation service delivery. Proceedings of the 1996 International System Dynamics Society Conference. Vol. I, 233-236.
Latané, B., Williams, K., & Harkins, S. (1979). Many hands make light work: The causes and consequences of social loafing. Journal of Personality and Social Psychology, 37, 822-832.
Lamm, H., and Trommsdorff, G. (1973). Group versus individual performance on tasks requiring ideational proficiency (Brainstorming): A review. European Journal of Social Psychology, 3, 361-387.
MacCrimmon, K. R. & Wagner, C. (November 1994). Stimulating ideas through creativity software. Management Science, 40(11), 1514-1532.
Massetti, B. (1996). An empirical examination of the value of creativity support systems on idea generation. MIS Quarterly, 20(1), 83-97.
Mayer, R. E. (1983). Thinking, problem solving, cognition. New York: W. H. Freeman & Co.
McGrath, J. E. & Hollingshead, A. B. (1994). Groups interacting with technology. Newbury Park, CA: Sage.
Nagasundaram, M. & Bostrom, R. (1993). The structuring of creative processes using GSS: A framework for research. (Unpublished paper).
Osborn, A. F. (1957). Applied imagination: Principles and procedures of creative thinking (2nd ed.). New York: Scribners.
Richmond, B. (1993). Systems thinking: Critical thinking skills for the 1990s and beyond. System Dynamics Review, 9(2), 113-133.
Richmond, B. (1994). Systems thinking/system dynamics: Let's just get on with it. System Dynamics Review, 10(2-3), 135-157.
Siau, K. I. (1995). Group creativity and technology. Journal of Creative Behavior, 29(3), 201-216..
Taylor, D. W., Berry, P. C., & Block, C. H. (1958). Does group participation when using brainstorming facilitate or inhibit creative thinking? Administrative Science Quarterly, 3, 23-47.
Valacich, J. S., Dennis, A. R., and Connolly, T. (March 1994). Group versus individual brainstorming: A new ending to an old story. Organizational Behavior and Human Decision Processes, 57(3), 448-
Valacich, J. S., Dennis, A. R., and Nunamaker, J. F. (1992). Group size and anonymity effects on computer-mediated idea generation. Small Group Research, 23 (1), 49-73.
Vennix, J. A. M. (1996). Group model building: Facilitating team learning using system dynamics. Chichester, England: John Wiley & Sons.
Vennix, J. A. M., Akkermans, H.A., & Rouwette, E.A.J. A. (1996). "Group model building to facilitate organizational change: an exploratory study. "System Dynamics Review, 12(1), 39-58.
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