(PDF) Cognitive stimulation and problem presentation in idea-generating groups

In the literature, there has been a focus on the effectiveness of larger sized electronic brainstorming groups; however, mechanisms for its effectiveness still remain open to question and some methodological concerns (e.g., the evaluation of ideas and the typing speed, and the use of different formats) continue to be important problems. To overcome such problems, a series of experiments were conducted. All subjects were exposed to the two-minute typing speed test which was overlooked in the previous studies in electronic brainstorming. In the first experiment the effect of the group size (4, 6, and 8 person groups); in the 2nd experiment that of group size (4, 6, 8, 10, and 12 person groups) with the memory instruction, and in the 3rd experiment that of group size (4 and 10 person groups) with two lengths of brainstorming session (15 and 25 minutes) were investigated on the brainstorming performance. Results showed that unique and original ideas increased as the group size increased. However, the group size did not affect the performance of one individual within these groups. Memory instruction inhibited performance in the shorter session (15 minutes) of brainstorming but enhanced it in the longer session (25 minutes) of brainstorming. Typing speed affected the total number and unique ideas but not the originality and feasibility of these ideas. In conclusion, these findings demonstrated that group size enhanced creative ideas (unique, original, and feasible ideas). Consistent with the literature, the beneficial effect of memory instruction could be evident in the longer session of brainstorming rather than the shorter one. These findings were discussed in light of the relevant brainstorming literature and their implications on educational, health and organizational settings.

Abstract The effects of idea sharing on cognitive processes and performance were assessed in an idea exposure paradigm. Participants generated ideas while being exposed to stimulus ideas that were semantically homogeneous or diverse, and were offered in an organized or a random sequence. As compared to a control condition, participants generated more diverse ideas when exposed to ideas from a wide range of semantic categories, and they generated more ideas per category when exposed to many ideas from only a few categories. The semantic organization of ideas was higher when participants were exposed to ideas that were organized in semantic clusters than when participants were exposed to unorganized ideas. Idea exposure had positive effects in general, because it reduced response latencies for category changes. Implications for information processing in groups are discussed.

Ideas exchange must needed in order to get the novel and creative solution for problems and also to implement it for future innovations. Ideas exchange will be met in many meetings, work session, discussion in a group of people to achieve the solution. There is a brainstorming method to create and generate ideas in order to exchange it with freewheeling and as flexible as they can or in another words with free-flowing burst of ideas (Osborn, 1957). This brainstorming involves the interconnected influences of cognitive, social, and motivational process from each contributor. The expressing of their ideas are affected by this model, in cognitive aspect the members have basic knowledge that can be used for idea generation. The second aspect is social that can influence because of the comment or judgment by another members that can block their mental. The last aspect is motivational process because each of members must know what the benefit and urgency of this group idea generation. Figure 1. A Cognitive-Social-Motivational Model of Group Ideation

Group Dynamics: Theory, Research, and Practice 2000, Vol. 4, No. 4, 307-329 Copyright 2000 by the Educational Publishing Foundation 1O89-269WO0/S5.0O DOI: 10.1O37//1089-2699.4.4.3O7 Cognitive Stimulation and Problem Presentation in Idea-Generating Groups Hamit Coskun and Paul B. Paulus Vincent Brown University of Texas at Arlington Clarkson University This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Jeffrey J. Sherwood Washington State University One technique that may facilitate group brainstorming is decomposition of the task so that categories of the problem are considered one at a time rather than simultaneously (A. R. Dennis, J. S. Valacich, T. Connolly, & B. E. Wynne, 1996). Two studies examined this possibility for both solitary and interactive brainstorming in which major categories of a brainstorming problem were presented simultaneously or sequentially. In the 1st study, participants in the sequential presentation condition generated more ideas than did those in the simultaneous condition in both the individual and the group conditions. In the 2nd study, individuals exposed to either a high number or low number of idea categories demonstrated enhanced performance. Simulations of the data demonstrated that the results were consistent with an associative memory model of the idea generation process. In many contexts, it is important to generate new ideas. These ideas can be the basis for innovations in organizations and industry (Paulus, 2000; West, 1997). In an influential book, Osborn (1957) suggested that brainstorming could considerably increase the quality and quantity of ideas produced by group members. Osborn provided four rules for improving the effectiveness of brainstorming groups: (a) Criticism is ruled out, (b) freewheeling is welcome, (c) quantity is wanted, and (d) combination and improvement are sought. Osborn (1957) claimed that a group that adopted these rules could generate twice as many ideas as similar Hamit Coskun and Paul B. Paulus, Department of Psychology, University of Texas at Arlington; Vincent Brown, Department of Psychology, Clarkson University; Jeffrey J. Sherwood, Department of Psychology, Washington State University. Hamit Coskun is now at the Department of Psychology, Abant Izzet Baysal University, Bolu, Turkey. Vincent Brown is now at the Department of Psychology, University of Richmond. The research presented in this article is based partly on thesis projects by Hamit Coskun and Jeffrey J. Sherwood. Correspondence concerning this article should be addressed to Paul B. Paulus, Department of Psychology, University of Texas, P.O. Box 19528, Arlington, Texas 760190528. Electronic mail may be sent to paulus@uta.edu. numbers of individuals working alone (nominal groups). In contrast to initial expectations, nearly all recent laboratory studies have found that group brainstorming leads to the generation of fewer ideas than comparable numbers of solitary brainstormers (Diehl & Stroebe, 1987; Mullen, Johnson, & Solas, 1991). There have been a number of interpretations of this productivity loss observed in interactive brainstorming groups. The most common explanations are evaluation apprehension, free riding, production blocking, and matching. Evaluation apprehension results when group members are concerned that others in the group will be critical of their suggestions, in spite of instructions designed to minimize such concerns (Collaros & Anderson, 1969; Diehl & Stroebe, 1987; Harari & Graham, 1975). Free riding occurs when individuals reduce their efforts when others in their group are performing at high levels (Borgatta & Bales, 1953; Diehl & Stroebe, 1987). Blocking may inhibit the generation of ideas in various ways. Obviously, only one person at a time can talk effectively in a group. Individuals may forget ideas while waiting for others to state theirs or may decide not to state ideas similar to those of others. Diehl and Stroebe (1987, 1991) have concluded 307 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 308 COSKUN, PAULUS, BROWN, AND SHERWOOD that blocking is the major factor responsible for productivity loss in brainstorming groups. Paulus and colleagues have suggested that performance matching plays an important role in group brainstorming performance (e.g., Paulus & Dzindolet, 1993; Paulus, Dzindolet, Poletes, & Camacho, 1993). Individual group members may either decrease or increase their performance to match the performance of others (Paulus, Larey, Putnam, Leggett, & Roland, 1996). Paulus and Dzindolet (1993) have hypothesized that blocking and matching are in fact jointly responsible for the group productivity loss (see also Camacho & Paulus, 1995). Blocking creates an initially low level of group performance that later becomes normative or entrained as the group members continue to match this low performance (Kelly & Karau, 1993). In addition, downward matching may be more likely than upward matching, in that low performers in the group may have more influence on the overall performance than other group members. Recently research has focused on ways of overcoming the production loss in groups, such as the use of facilitators (Offner, Kramer, & Winter, 1996; Oxley, Dzindolet, & Paulus, 1996; Putnam, Paulus, Dugosh, & Coskun, 1999), special training techniques (Paulus, Larey, & Dzindolet, 2000), and setting high goals or standards (Paulus & Dzindolet, 1993). Cognitive factors also have the potential to improve group brain storming. The studies presented here focus on task decomposition as a means of facilitating brainstorming. Task decomposition involves breaking a problem or task down to its component pieces (such as subcategories) and instructing the group or individual to brainstorm on the components separately. This approach has been advocated by Osborn (1963) and others (e.g., Armstrong, Denniston, & Gordon, 1975; Pitz, Sachs, & Heerboth, 1980; Samson, 1988): "It would have been better if each of four or five sub-problems had been brainstormed separately. Although this would have taken more time, the results would have been relatively superior" (Osborn, 1963, p. 174). Dennis, Valacich, Connolly, and Wynne (1996) have examined the impact of problem decomposition on electronic brainstorming. In electronic brainstorming, individuals can generate ideas on one part of the computer screen while having access to ideas from group members on another part of the screen (Nunamaker, Briggs, & Mittleman, 1995). Sharing ideas electronically does not lead to the production loss often observed in conventional groups (Gallupe, Bastianutti, & Cooper, 1991), This may be in part because group members can work in parallel and thus do not experience production blocking (Valacich, Dennis, & Connolly, 1994). In their study of problem decomposition, Dennis, Valacich, et al. (1996) found that having groups focus on three components of a problem one at a time instead of dealing with all three components simultaneously increased idea generation by more than 60%. In a subsequent study Dennis, Aronson, Heninger, and Walker (1996) examined the role of time segmentation independent of problem structuring. Participants worked in groups of 10 in the electronic brainstorming paradigm for 30 min. As in the Dennis, Aronson, et al. (1996) study, participants were presented with a single question or with three questions. The 30 min were structured either as a single time period or as three 10-min segments. Decomposing the problem again had a strong positive effect on performance, but time segmentation alone did not. Although problem decomposition is beneficial in electronic brainstorming, it remains to be seen whether it facilitates productivity in conventional face-to-face group and individual brainstorming. So far, the positive effects of task decomposition have been demonstrated only in electronic groups using three subcategories. We conducted two experiments to assess the generality of the decomposition effect and made predictions based on various interpretations of the source of the decomposition effect. Our analysis was supplemented by computer simulations of the model developed by Brown, Tumeo, Larey, and Paulus (1998), which represents brainstorming in an associative memory framework. In the first experiment, we examined task decomposition by presenting participants alone or in groups with single words or short phrases describing categories of solutions to the brainstorming task via audiotape. In the sequential condition, the relevant categories were presented one at a time (1 every 3 min). In the simultaneous condition, all categories were presented together at the start of the session. Participants brainstormed by speaking into microphones. In the second experiment, we exam- This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION ined the impact of visually presenting either a small (2) or a large (10) number of categories in a simultaneous or sequential fashion. However, in this case, the categories were presented every 3 min in both the simultaneous and sequential conditions. All of the participants performed individually and responded in a written format. Why might task decomposition facilitate group brainstorming? One possibility is that decomposition may change the task orientation. For example, decomposition may increase the pace of brainstorming because it generally involves dividing the task into smaller time periods. The shorter time periods could encourage participants to work at a faster pace than longer time periods (Kelly & Karau, 1993). However, this did not appear to be a factor with Dennis, Aronson, et al.'s (1996) electronic brainstorming groups. It seems more likely that task decomposition facilitates the cognitive processing involved in brainstorming. There are a number of ways this could occur. One possibility is that decomposition into multiple components or categories may decrease the tendency of groups to converge on a small number of dominant categories (Bouchard, Drauden, & Barsaloux, 1974; Lamm & Trommsdorff, 1973; Larey & Paulus, 1999; Taylor, Berry, & Block, 1958; Vroom, Grant, & Cotton, 1969). Groups may tap only a small number of the available possibilities (Connolly, Routhieaux, & Schneider, 1993; Gettys, Pliske, Manning, & Casey, 1987). Task decomposition may provide a structure that motivates and enables groups to more fully tap ideas from a broad range of categories (Larey & Paulus, 1999). If task decomposition helps increase the focus on a wide range of categories, it may be especially beneficial for group brainstorming because interactive groups tend to converge on a smaller number of categories than nominal groups. Second, task decomposition may reduce the cognitive load resulting from the demands of group interaction. Being in a group requires individuals to monitor a number of situational factors, such as turn taking and assessing the knowledge and contributions of others. Exposure to a high number of diverse stimuli in the form of ideas may also contribute to the cognitive processing load. The limited capacity of short-term memory may prevent group brainstormers from optimally concentrating on idea 309 generation while processing the additional information associated with group interaction. As a result, brainstormers may reduce the attentional resources allocated to processing the ideas from others as well as to their own internal idea-generation process. Task decomposition may reduce this overload by organizing the stimuli into meaningful subsets (Nagasundaram & Dennis, 1993), enabling group members to more easily focus on one piece of the problem at a time. Decomposition into categories has proven effective in overcoming collaborative inhibition in group recall (B. H. Basden, Basden, Bryner, & Thomas, 1997). If sequential presentation aids in reducing information overload in groups, groups might again show more benefit of problem decomposition than individuals. Third, focusing on a single aspect of a problem may allow for greater stimulation of related ideas. Because a major determinant of responsiveness to stimuli is the degree of similarity to one's present cognitive state (Mednick, 1962), exposure to other group members' ideas should be most beneficial if the ideas share some degree of similarity with concepts or categories that are currently being considered. From this perspective, cognitive facilitation takes place when one brainstormer's idea serves to activate related ideas in the mind of his or her listeners. These newly activated lines of thought serve, in turn, when communicated to the group, to activate still more ideas in the minds of the group members. The effects of this type of spreading activation, or semantic priming, are well studied by memory researchers (e.g., Neely, 1991).* Having groups or individuals focus on one aspect of the problem at a time is one way to facilitate this type of relatedness. It is possible that individual brainstormers might benefit even more than group brainstormers, because in a group the probability is higher that one member might produce an idea from a different category, thus disrupting the group's focus on the current category. On the other hand, assigning a 1 Spreading activation usually refers to the process of one concept activating another related concept within the mind of a person. We use the term here to refer to such cognitive facilitation between people as well. COSKUN, PAULUS, BROWN, AND SHERWOOD 310 Table 1 Matrix of Category Associations Used to Simulate Experiment 1 and Experiment 2 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Next category category 1 2 3 4 5 6 7 8 9 10 11 Null 1 2 3 4 5 6 7 8 9 10 11 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .90 0 0 0 0 0 0 0 0 0 0 0 .01 .01 .01 .01 .01 .90 .01 .01 .01 .01 .01 Note. Entries in the matrix are probabilities of generating an idea from the next category given an idea in the current category as brainstorming begins. Diagonal entries represent the probability of generating a new idea from the same category. Off-diagonal entries represent the probability of generating an idea from a different category. The last column, labeled the null category, represents the probability of coming up with no new idea during the current time interval. As a brainstorming session progresses, the probabilities in the null category increase. specific category may reduce the occurrence of such stray ideas.2 Thus, there are a number of reasons to expect that task decomposition will facilitate idea generation in both individuals and groups. Although there is a basis for expecting that task decomposition should be more beneficial for groups than individuals, the distractions associated with group interaction may conspire to reduce the benefits of decomposition for groups. A Model of Cognitive Processing in Interactive Brainstorming Many of the potential advantages of group brainstorming and task organization being discussed here can be described using the associative memory framework from cognitive psychology. Concepts and ideas in the mind of an individual are assumed to be organized in an associative structure called a semantic network (Collins & Loftus, 1975). Similar or related concepts are assumed to be more strongly connected to each other than less similar concepts (e.g., "tree" is more strongly connected to "leaf" than it is to "grass" or "automobile"). Concepts can be activated through external means, by presenting written or spoken primes, or through internal means, when the ideas that one is considering activate other ideas, which then become the focus of one's attention. When a particular concept is activated, the concepts to which it is connected also become active to a greater or lesser degree, depending on the strength of the connections. Short-term memory is often defined as the set of currently active concepts (e.g., Cowan, 1995). Brown et al. (1998); Paulus, Brown, and Ortega (1999); and Sherwood, Dugosh, Brown, and Paulus (2000) have developed a computersimulation model of the cognitive factors in group brainstorming based on the associative memory framework. The basic representation used by the model is a matrix of associations between categories of ideas: Each entry in the matrix represents the probability of generating an idea from a particular category, given that the brainstormer is currently generating ideas from another (or the same) category. Table 1 illustrates the matrix used in the simulations reported here. The matrix format conveniently captures many of the features of individuals' idea representation and organization relevant to group brainstorming. The sum of the row probabilities represents the total knowledge a brainstormer has about a particular category: the fluency (Mednick, 1962). The last column in the matrix 2 On the other hand, unique or seamingly unrelated ideas may be the more creative ones. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION (called the null category) is the complement of the fluency and represents the probability of coming up with no idea. As a brainstorming session progresses and ideas are used up, the probabilities accumulate in the null category to represent the fact that fluency effectively decreases during a session. The sum of the offdiagonal column probabilities represents the probability of considering ideas from a particular category during the current session. This is called the accessibility of the category. Lowaccessible categories will contain ideas that an individual may not think of on her or his own but may be primed to consider by other group members. The presence of low-accessible but high-fluency categories is one factor that should make brainstorming with other people quite useful. For example, an individual seeking counseling might not be immediately aware of all of the underlying factors that motivated him or her to seek counseling but may be led to consider more of them after listening to other people, perhaps a therapist or individuals in a group therapy session. The matrix representation also captures differences in individual cognitive styles, with convergent thinkers having relatively high within-category transition probabilities, and therefore being likely to continue with the current category, and divergent thinkers being relatively more likely to move between categories. (Thus, the matrix depicted in Table 1 represents a relatively convergent knowledge structure.) Also, many of the other possible similarities and differences between individual brainstormers' knowledge about a task or problem can be represented in the matrix model by varying the category association strengths in each brainstormer's matrix. Effective cognitive facilitation in groups is assumed to depend on the two related processes of attention and short-term memory. Clearly, the amount of attention that group members pay to each other as they are brainstorming will determine the effectiveness of the group interaction. Similarly, the extent to which the ideas that other members have presented remain active in the mind of an individual group member will determine how much influence these ideas have on that individual. The amount of attention and short-term memory capacity available during a group brainstorming session varies from individual to individual and depends on the 311 social and cognitive demands of the situation. The more cognitive resources devoted to other factors, the less will be available to concentrate on the task of brainstorming itself. In our model, attention and short-term memory are represented as weights between 0 and 1.3 Attention is represented as the probability of an individual group member switching from considering her or his own category of ideas to the category presented by the current speaker in the group. For example, an attention weight of 0 means that the listener never switches to the speaker's category, that is, the listener is not paying attention at all. An attention weight of 1 means that the listener always switches to the speaker's category. This is probably unrealistic, and a value of 0.5 is used in the simulations reported here. The short-term memory weight multiplies the most recently generated category and functions as a decay rate. A short-term memory weight of 0 means that only the current category is considered. A short-term memory weight of 1 means that all previously generated categories are equally likely to be the source of the next idea. This type of perfect memory is, of course, unrealistic. The role of attention and short-term memory in brainstorming is examined in detail in the simulations of the two experiments and in the General Discussion. A simulated group brainstorming session begins with a category being chosen randomly from each brainstormer's matrix, with the most accessible categories being most likely to be chosen and the least accessible categories being least likely to be chosen. Once a category is activated, an idea is assumed to be generated from that category according the probabilities in the row of the matrix representing that category. These ideas represent those generated internally by each group member. There will be time intervals, especially later in the session, when no internal ideas are generated by some (or even all) of the brainstormers. Next, a speaker is chosen from among the group members who have generated an idea. The model has the flexibility to incorporate a number of the factors that determine a given individual's likelihood of 3 Fora description of the details of the model's representation of attention, see Brown et al. (1998). For the details of the implementation of short-term memory, see Sherwood, Dugosh, Brown, and Paulus (2000). This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 312 COSKUN, PAULUS, BROWN, AND SHERWOOD stating her or his ideas during a group brainstorming session, including individual differences in sensitivity to blocking (which is perhaps a function of the personality trait of introversion-extraversion) and the tendency to match the performance of others (Brown & Paulus, 1996; Sherwood, 1998). In the simulations reported here, all group members were assumed to have equal probabilities of stating their ideas. The spoken idea becomes available to each individual brainstormer as the source of their next idea. A group member who is attending to the speaker uses that idea to continue brainstorming. A group member who happens not to attend to the speaker in a given time interval continues generating ideas on the basis of the current contents of his or her short-term memory. Whether a person attends to the speaker's idea during a given time interval is randomly determined by the attention weight. Each new idea generated by a brainstormer is added to short-term memory, after the current contents of short-term memory are decreased by being multiplied by the short-term memory weight. The updated contents of short-term memory determine the category of the next internally generated idea. In addition to categories being selected from the contents of short-term memory or determined by attending to the current speaker, categories can be externally primed in the model by activating the desired category (or categories) at various intervals throughout the simulated session. This feature of the model allows us to simulate the effects of task decomposition, which was implemented in the following experiments by presenting participants with category labels at the appropriate times during the brainstorming session. Experiment 1 In the first experiment, we examined the effects of task decomposition by comparing sequential to simultaneous idea presentation in both nominal and interactive groups. In both the simultaneous and sequential conditions, the participants were presented with 10 categories of a problem via audiotape. In the simultaneous condition, all 10 categories were presented at the start of the session. In the sequential condition, the categories were presented 1 every 3 min. The number of nonrepetitive ideas generated was the main dependent variable. We examined the time course of idea generation over the 30-min brainstorming period (ten 3-min intervals) and the extent to which participants focused on a few categories of the problem or many categories during each 3-min interval. We predicted that nominal groups would outperform interactive groups and that sequential problem presentation would enhance performance for both. If the benefits of sequential problem presentation were due largely to pacing, then the benefits would be similar for nominal and interactive groups. If sequential problem presentation reduced convergent thinking, interactive groups might show more benefit because they were more prone to convergent thinking. Convergent thinking would be reduced if groups were led to change their focus to each new category as it was presented: This would be evident in the analysis of category use over the ten 3-min time periods. If associative memory organization factors underlay the positive effects of sequential presentation, beneficial effects might be more pronounced with nominal groups, because interacting participants were more likely to be exposed to ideas from others that did not fit within the category that was being considered. Associative memory factors would also lead participants to focus their idea generation primarily on the presented category. Such a pattern was not predicted from a strict pacing perspective because this would produce a general increase in idea generation regardless of the particular categories used to set the pace. Method Participants. In exchange for experimental credit, 156 students enrolled in introductory psychology classes participated in the study. Each treatment condition involved 13 groups, each with 3 participants. Most studies have indicated that production losses occur for groups of size 3 or larger but not for dyads (Diehl & Stroebe, 1987). One of the groups in the simultaneous condition was excluded from the data analysis because its members did not follow the instructions. Procedure. After all participants had signed the informed-consent form, the experimenter gave them a second page, which included detailed instructions about both the brainstorming procedure and the brainstorming problem. The This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION experimenter read the instructions aloud to the participants as they followed along. We used The University Problem, which requires students to generate suggestions for improving their university. Previous research has shown that the responses to the University Problem consist of categories such as classes, campus, activities, and parking (Larey, 1994). Each of these categories has subcategories. For example, the category of parking problems consists of subcategories such as tickets and towing. In the present study, categories related to the University Problem were selected on the basis of the number of their subcategories, as determined from the Larey data set. Each selected category had 15 or more subcategories. The categories of the problem were presented to brainstormers in decreasing order of number of subcategories: classes, campus life, building, student life, academic policies, activities, instruction, parking, dorms/housing, and athletic teams. In each presentation condition, all participants were instructed by means of a standardized audiotape. In the sequential-problempresentation condition, the tape instructed the participants to begin generating ideas on a new category every 3 min. In the simultaneous-problem-presentation condition, the tape instructed the participants to generate ideas on the 10 categories of the University Problem by presenting all of the categories at the start of the session. The participants in the simultaneouspresentation condition also were provided a sheet that included 10 categories of the problem. The participants in both the simultaneous and sequential conditions were instructed to generate ideas on any aspect of me problem that came to mind, whether or not these ideas fit the categories. In the nominal condition, participants were recruited in groups of 3, but each participant was led to a separate room that contained a desk and two tape recorders. One of the tapes was used for the presentation of the relevant problem and the other for recording the ideas generated by each individual. In the interactive condition, all participants remained in the experimental room seated around a circular table that contained one tape recorder with a microphone and a second recorder for the presentation of the relevant categories. In this way, the participants' ideas were recorded on a common 313 tape. In both conditions, after answering questions regarding the brainstorming problem, the experimenter started both tapes at the same time and left the room. At the end of 30 min, the speaker on the tapes instructed participants to stop generating ideas. At that point, the experimenter returned and stopped the tapes. At the end of the brainstorming session, participants were also asked to rate the number and quality of ideas they had generated on a 9-point scale ranging from very few or very low to very many or very high. As a way to assess whether the participants were attending to the tape, all participants were asked to list the categories (10 categories of the University Problem) to which they were exposed during the brainstorming session. Results Experimental data. Each individual's and group's audiotape was transcribed, and each transcript was coded by one rater for unique ideas. In the case of the solitary performers, the rater obtained a raw group total by aggregating the 3 members' individual totals to form a nominal group total in accord with the procedures of past studies. Then the rater checked the transcripts for repetitive ideas and calculated a new group total for nonrepetitive ideas. The nonrepetitive group total was used as a productivity index for comparing the general performance levels of nominal and interactive groups. As a check on the first rater, a second rater repeated the coding for 25% of the transcripts. The interrater reliability (Cronbach's alpha) for the raw group total was .94. The interrater reliability for the nonrepetitive group total was .96. In addition, the participants' use of categories within each 3-min time period was coded separately by two independent raters, who assigned each idea to 1 of the 10 categories or other categories of the University Problem. The interrater reliability for this measure was .94. Figure 1 shows the effects of presentation and group type on idea-generation performance over the ten 3-min time intervals. A 2 (presentation: sequential vs. simultaneous) X 2 (group type: interactive vs. nominal) X 10 (time interval) analysis of variance (ANOVA), with time interval as a within-subject factor, yielded significant main effects of presentation and group type, F(U 44) - 29.24, p < .0001, and F(l, This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 314 COSKUN, PAULUS, BROWN, AND SHERWOOD 12 15 18 21 24 30 Time Interval (minutes) - 9 - Nominal/Sequential -G-lnteractive/Sequential • No m i nal/S im u Itaneous -Interactive/Simultaneous Figure 1. The number of nonrepetitive ideas generated over time in Experiment 1 as a function of group type and presentation type. 44) = 89.80, p < .0001, respectively. The participants in the sequential problem presentation condition (M = 114.11, SD = 66.33) generated more ideas than those in the simultaneous condition (Af - 72.24, SD = 40.77), and the nominal groups (Af = 137.00, SD = 49.00) generated significantly more ideas than interactive groups (M = 48.44, SD = 22.39). There was also a significant Presentation X Group Type interaction, F(l, 44) = 5.46, p < .02, with the difference between the simultaneous- and sequential-presentation conditions being greater for nominal brainstormers than for interactive brains tormers. A main effect of time interval on idea-generation performance, F(9, 396) = 15.93, p < .0001, reflected the fact that idea-generation performance was higher in the early intervals than in the later intervals. There was a significant Time Interval X Problem Presentation interaction, F(9, 396) = 3.40,/> < .0005, indicating that the difference in performance due to problem presentation was greater in the later intervals than the earlier ones. This was because idea generation declined more over time with simultaneous presentation than it did with sequential presentation. A Time Interval X Group Type interaction, F(3, 396) = 1.96, p < .04, reflects the fact that the difference between nominal and interactive groups was larger in the early time intervals than in the later ones. A similar analysis was performed for the number of categories from which ideas were generated within each 3-min time period (see Figure 2). Participants processed fewer categories as time progressed, F(9, 396) = 27.86, p < .0001. There was also a Presentation X Time Interval interaction, F(9, 396) = 8.01, p < .0001, reflecting the facts that the participants in the simultaneouspresentation condition generated ideas from more categories in each time interval than those in the sequential-presentation condition and that this category usage declined more over time in the two simultaneous conditions than it did in the two sequential conditions. Those in the sequentialpresentation condition tended to focus on about one category on average within the 3-min time intervals. There was also a significant effect of problem presentation on the recall of the presented categories, F(l, 47) - 27.98, p < .0001. Participants in the sequential-problem-presentation condition (Af = 6.81, SD = 1.32) recalled significantly more categories than did those in the This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION 12 15 18 21 315 27 30 Time Interval (minutes) - B - Nominal/Sequential -^-Interactive/Sequential - Nominal/Simultaneous - Interactive/Simultaneous Figure 2. Category usage per 3-minute interval as a function of group type and presentation type in Experiment 1. simultaneous-problem-presentation condition (M = 4.72, SD = 1.44). An analysis of ratings of the number of ideas revealed a significant effect of the group type on perceived performance, F(l, 152) = 8.17,/? < .005. Using a 9-point scale, participants in the interactive groups (M ^ 5.24, SD = 2.01) reported that they generated more ideas than those in the nominal groups (M = 4.29, SD = 1.60). There was no significant difference in rating of quality, although there was a trend for the participants in the interactive condition to report generating higher quality ideas than those in the nominal condition. Model simulations of Experiment I. The patterns of results obtained were consistent with an associative memory perspective. To provide further support for this perspective, the conditions of the experiment were simulated using a model based on associative memory assumptions (Brown et al., 1998). Simulations of Experiment 1 activated all of the relevant categories in immediate succession at the beginning of the session to represent the simultaneous-presentation condition. In the case of orally presented external primes, there can be no true simultaneous condition, because spoken words must be presented in sequence to be properly recognized. In the simulations of the sequential condition, the 10 primes were presented with much more time between them (every seven time cycles). The short-term memory weight was set to 0.2 for the simulations of Experiment 1. Each point in the figures represents the average of 5,000 tests. Figure 3 shows that in keeping with the data from Experiment 1 (see Figure 1), the model simulations generated both a strong effect of presentation type and a Group Type X Presentation Type interaction. The model clearly predicts that successive presentation will improve the productivity of brainstorming individuals and groups. Figure 3 shows that although in the simultaneous conditions, participants started the session at a slightly higher level of productivity than those in the sequential conditions, productivity declined more rapidly in the simultaneous conditions than in the sequential conditions, producing a long-term advantage for the se- This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 316 COSKUN, PAULUS, BROWN, AND SHERWOOD 2 3 4 5 Time Interval (simulated) • Nominal/Sequential —©—Interactive/Sequential •—Nominal/Simultaneous Nominal/No Priming •—Interactive/Simultaneous - - - -Interactive/No Priming Figure 3. Model predictions for number of ideas generated over time for the four conditions of Experiment 1. The dashed lines represent the performance of hypothetical no-priming conditions. quential conditions.4 This is because the sequential conditions continued to get a boost as new category primes were presented throughout the session, whereas the primes were used up at the start of the session in the simultaneous conditions. Successive presentation helped groups to overcome two related tendencies: (a) the tendency for rate of idea generation to decrease, often rapidly, from the beginning to the end of a brainstorming session, and (D) groups' tendency to converge and generate ideas from only a subset of the possible problem categories. With nearsimultaneous presentation, only the most recently presented categories in the sequence (or some other select few) remained strongly active in memory. Because of short-term memory decay, these primes were not as readily available later in the session. With sequential presentation, each primed category was likely to be active in short-term memory until it was replaced somewhat later by the next external prime.5 It is possible that overwhelming the brainstormers with simultaneous primes right at the start of the task could actually reduce performance to a level below what it would have been if no primes had been presented. The hypothetical no-priming conditions generated by the model are shown as the dashed lines in Figure 3. 4 The advantage in the simulations for the simultaneous presentation condition during the first time bin was the result of the continuous priming that occurred during the starting phase of the brainstorming session. This early advantage was not as readily apparent in the simulations of interactive groups (see the bottom lines of Figure 3), because most of the extra ideas were lost due to blocking: There was not time for everyone to state their ideas even if a high number was initially generated in response to the simultaneous priming. For simplicity's sake, the simulations assumed that brainstormers always attended perfectly to the primes throughout the session (the attention weight for the primes was set to 1.0), In reality, participants probably did not attend perfectly to the primes, and in particular, attention to a sequence of primes presented rapidly at the start of a session was likely to be somewhat poor: Participants simply might not have the time to hear a prime, process it, activate relevant ideas, and switch their focus to the next primed category. Using a lower attention weight during the initial simultaneous primes, such as the value of 0.5 (the value with which group members were assumed to attend each other), reduced this spurious advantage. 5 The simulations did not take into account the fact that participants in the simultaneous presentation conditions were given a printed list of the categories, which they kept throughout the session. If the list had helped participants to any significant extent, performance in the simultaneous conditions would have been much closer to performance in This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION 2 3 317 4 5 Time Interval (simulated) —B—Nominal/Sequential —&—Interactive/Sequential -•—Nominal/Simultaneous Nominal/No Priming -•—Interactive/Simultaneous - - - -Interactive/No Priming Figure 4. Model predictions for number of categories used each time interval for the four conditions of Experiment 1. The dashed lines represent the performance of hypothetical no-priming conditions. The long dashes represent a nominal no-priming condition; the short dashes represent an interactive no-priming condition. Both of these lines fall roughly between the simulated data for the sequential and simultaneous conditions. In fact, there is evidence from the study of memory that improper cuing can be detrimental. The surprising result, known as the "part-list cuing" effect, occurs when participants in a free-recall task are given some of the items on the remembered list as cues to recall. Such cues often actually serve to decrease recall performance. This is believed to occur because the seemingly friendly prompts actually disrupt the participant's own internal organization of the material (D. R. Basden, Basden, & Galloway, 1977; Raaijmakers & Shiffrin, 1981). B. H. Basden et the sequential conditions. Furthermore, the fact that participants in the simultaneous conditions recalled fewer of the presented categories than participants in the sequential conditions, despite having die categories available to diem continuously throughout the session, strongly suggests that they were not as attentive to the printed list as they might have been. al. (1997) have suggested that this may be the primary factor responsible for inferior group performance in experiments on collective recall. It is not surprising then that a rapidly presented sequence of primes could actually serve to confuse brainstormers. Figure 4 illustrates the prediction that simultaneous priming for nominal groups will lead to the highest level of category usage of the four experimental conditions. Simulated nominal groups tended to generate high category-usage scores, owing to the fact that there was no interaction between individuals in a nominal group and so there was little reason that their brainstorming will be synchronized. There was also the tendency for simulated-simultaneouspresentation conditions to generate higher category-usage scores than simulated-sequentialpresentation conditions. This was because in the early time intervals the large number of simultaneous primes activated a wide variety of ideas without providing a specific focus to the task and during later time intervals the primes were less available in short-term memory, giving rise to performance that was closer to that observed This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 318 COSKUN, PAULUS, BROWN, AND SHERWOOD when no primes were presented. The hypothetical no-priming conditions are again shown as dashed lines in Figure 4. These two factors led the nominal simultaneous condition to always have the highest category usage, but exactly where the other three conditions fell with respect to each other depended on a number of other factors. Extensive simulations demonstrated that the frequency of sequential priming, the convergent or divergent styles of the brainstormers involved, attention, and short-term memory all had effects on category usage. Presenting primes more frequently caused brainstormers in the sequential condition to focus more on the primed category, whereas too much time between the primes allowed the brainstormers to wander, and category usage per time interval increased. When more divergent brainstormers were simulated, category usage over time increased, reflecting the less strict category boundaries of a divergent thinker. Thus, category usage in the simultaneous and sequential conditions became more equal (divergent thinkers just did not stick with a sequentially primed category as much as convergent thinkers). The effects of attention and short-term memory on idea generation are further examined in the General Discussion. Although the model was not specifically designed to simulate participants' memory performance, a somewhat informal analysis of the model output supported the expectation that recall of the presented categories would be better in the sequential condition than in the simultaneous condition. One factor affecting memory performance was the amount of time the to-beremembered material was studied or rehearsed, regardless of whether participants knew that a memory test was to be given. A rough measure of rehearsal of the categories in the model was the amount of time a category had been active in working memory, taking into account the degree of activation (short-term memory strength). This measure was obtained simply by summing the short-term memory strengths of each category over all of the time intervals in a simulated session. The simulations showed that the total short-term memory strength (rehearsal time) with sequential presentation was greater than that with simultaneous presentation for about 73% of the categories for nominal groups and for about 64% of the categories for inter- active groups. This would lead to better recall of sequentially presented categories in both cases. Discussion The sequential-presentation condition produced a higher rate of idea generation than did the simultaneous-presentation condition. This effect was obtained for both the nominal and interactive conditions. The results for the interactive condition are consistent with those of Dennis, Aronson, et al. (1996) and Dennis, Valacich, et al. (1996) and indicate that the benefits of problem decomposition are not limited to the electronic ideageneration format. The finding of an effect for individual performance suggests that the decomposition effect for idea generation is also not limited to interactive settings. In fact, nominal groups benefited more than interactive groups from task decomposition. Participants in the sequential condition generally focused their idea generation on the category presented. This led to a very consistent number of ideas being generated from each of the categories. Priming the brainstormers by explicitly presenting them with categories of solutions to the problem makes it possible for all relevant categories to be considered. The cognitive model simulations suggest that presenting the primes sequentially throughout the session helps to compensate for the limitations of short-term memory, which might be particularly noticeable under highly attention-demanding conditions. Simultaneous (i.e., rapid sequential) presentation may overwhelm the participants and prevent them from focusing their attention adequately on each of the primes presented. In fact, the results of simulations suggest that rapid sequential presentation may lead to performance below that occurring when no primes are presented. The stronger effect of presentation mode for nominal groups indicates that the priming benefits of sequential presentation are more easily induced when individuals are performing alone. Once again, the inhibitory factors occurring in groups seem hard to overcome. Experiment 2 In Experiment 1, we used 10 subcategories, but the decomposition studies by Dennis, Valacich, et al. (1996) and Dennis, Aronson, et al. (1996) used only 3 subcategories. The theoretical rationales This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION discussed previously did not specify any definite boundary conditions regarding the number of categories. Increasing the number of categories, up to a point, would be beneficial in providing cues for the idea-generation process. Such a stimuli-enhancement view was also advocated by Nagasundaram and Dennis (1993), suggesting that the greater the variety of stimuli presented, the more ideas generated. With each new category, a potentially new set of related ideas can be stimulated (Brown et al., 1998; Paulus et al., 2000). However, if the number of categories becomes too large, there may be too little time allotted for each category in a typical, brief experimental session (30 min or less). In this case, there would be little opportunity for related idea generation and thus little benefit of decomposition. Conversely, if the number of categories is too small, the beneficial effect of priming would also be less evident (see also Nagasundaram & Dennis, 1993). A proper test to examine such predictions requires a paradigm that includes a control or no-priming condition in addition to a low or high number of categories. The studies by Dennis and his colleagues did not include a control or no-priming condition as a baseline to the other conditions in their research. Furthermore, although Dennis, Aronson, et al. (1996) found that the three 10-min segmentations did not have any effect on ideageneration performance, it is possible that smaller time segmentations (e.g., 3-min time segmentations) may have strong impact and motivational or cognitive stimulation value on performance (Kelly & Karau, 1993). In Experiment 2, we examined the impact of presenting either a small or a large number of categories in a simultaneous or sequential fashion. In this experiment, there were two independent variables: the type of presentation (simultaneous or sequential) and the number of categories (2 or 10). Differences in timing or time constraints were controlled by having 10 task segments, each of which lasted 3 min, in all four conditions. In contrast to Experiment 1, in Experiment 2, participants in both the simultaneous and sequential conditions were exposed to category primes every 3 min, and the writing format was used instead of an oral one. There was also a control condition in which the problem was presented to the participants without information about the categories or task segmentation. We predicted that a greater number of categories would have positive effects on idea generation 319 because the participants would have sufficient time (3 min) available for each category. However, presenting both the simultaneous and sequential category information every 3 min might decrease the difference between the two presentation methods because the categories would be reactivated in short-term memory each time the cues were re-presented. However, if the written simultaneous presentation produced some degree of task overload or the use of suboptimal ideageneration strategies, the sequential presentation would still lead to superior performance. Method Participants. Eighty-five students enrolled in introductory psychology classes participated in the study in exchange for experimental credit. Seventeen brainstormers were assigned to each treatment condition: either a low- or high-category condition and to either a simultaneous- or sequential-presentation condition, and 17 were assigned to the no-primary control condition. Procedure. When participants arrived for the experiment, they were handed a packet that consisted of the informed-consent form, which provided general information about the nature of research on the 1 st page, detailed instructions about both the brainstorming procedure and the problem on the 2nd page, and the categories appropriate to the participant's experimental condition from the 1st page to the 10th page. The same problem used in Experiment 1 was used: Students were asked to generate ideas on how to improve their university. The same categories of the problem and order of presentation used in Experiment 1 were used in Experiment 2. After the presentation of the brainstorming procedure and the University Problem, participants were instructed (a) to write down their ideas, (b) to number each idea before they wrote it down, and (c) that they did not need to make complete sentences when writing the ideas. They were also instructed to turn to a new page every 3 min and to continue generating ideas on this page. This feature equated all conditions in terms of number of distinct task segments. In the low-category condition, participants were given the two most popular categories (classes and campus life), whereas in the highcategory condition, participants were given the same 10 categories of the University Problem used in Experiment 1. In the sequential-pre sen- COSKUN, PAULUS, BROWN, AND SHERWOOD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 320 tation condition, the relevant categories of the problem were presented one at a time on each new page, whereas in the simultaneous-presentation condition, categories were presented at the same time on each new page. In the sequential-low-category condition, the first 5 pages mentioned the first category, and the second 5 pages mentioned the second category. In the sequential-high-category condition, each page presented a new category. On the other hand, in the simultaneous-low-category condition, each page mentioned each of the two categories. In the simultaneous-high-category condition, each page mentioned all 10 categories. After finishing instructions and answering questions regarding the brainstorming problem, the experimenter instructed all participants to turn to page 1, read the instructions, and begin generating ideas. As soon as the experimenter finished the instructions, the experimenter started a stopwatch and allowed participants to brainstorm until 3 min had passed. When 3 min had passed, the experimenter instructed the participants to stop brainstorming. Then the experimenter instructed them to turn to the next page, read the instructions, and continue generating ideas. Again, the experimenter started a stopwatch, and allowed them to 6 9 12 15 brainstorm until 3 min passed. This procedure remained the same until the end of the 10th problem page. All participants were instructed to generate ideas on any aspect of the problem that came to mind, whether or not these ideas fit the categories. At the end of the brainstorming session, participants were also asked to rate the number and quality of ideas generated on a 9-point scale ranging from very few or very low to very many or very high. Results Experimental data. As in Experiment 1, each participant's transcript was coded separately by one rater for unique ideas. The rater checked each participant's transcripts for repetitive ideas and calculated a new individual total for nonrepetitive ideas. A second rater repeated coding for 25% of the transcripts. The nonrepetitive ideas were used as a productivity index for comparing the performance levels of individual brainstormers. The interrater reliability for tfie raw total was .98, that for the nonrepetitive total was .96, and that for assigning ideas to categories was .96. Figure 5 shows the idea-generation performance for each 3-min time interval for individ- 18 21 24 27 Time Interval (minutes) - High/Sequential —•— High/Simultaneous —6— Low/Sequential -Low/Simultaneous No Priming Figure 5. The number of nonrepetitive ideas generated over time in Experiment 2 as a function of number of primes and presentation type. 30 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION uals in the four experimental conditions and the no-prime control condition. The effects were examined by means of a 2 (presentation: sequential vs. simultaneous) X 2 (the number of categories: low [2] vs. high [10] categories) X Time Intervals (10) ANOVA, with time interval as a within-subject factor. This analysis indicated a main effect of number of categories on idea-generation performance, F(l, 64) = 13.53, p < .0005, with more ideas generated with a high number of categories. However, there was no main effect of presentation, F(l, 64) = 1.75, p > .19, nor Presentation X Number of Categories interaction, F(l, 64) = .07, p > .79. The main effect of time interval was significant, F(9, 576) = 11.40, p < .0001, reflecting decreased idea generation over time. There was a significant three-way Time Intervals X Presentation X Number of Categories interaction, F(9, 576) = 2.22, p < .02, reflecting the fact that the differences in idea-generation performance became evident in the later time periods for the high-category condition. A planned one-factor ANOVA comparing the number of ideas generated in the low-category, high-category, and control conditions was significant, F(2, 36) = U.96,p< .0001. Tukey 9 12 15 321 tests showed that there was a significant difference (a = .01) between the mean of participants in the high-category conditions (M = 48.92, SD = 15.32) and the mean of participants in the low-category conditions (M — 30.77, SD = 10.96), as well as the mean of participants in the high-category conditions and the mean of those in the control condition (M = 25.85, SD = 11.26). There was no significant difference between the mean of participants in the low-category conditions (Af = 30.77, SD = 10.96) and the mean of those in the control condition (M = 25.85, SD = 11.26; see Figure 5). Figure 6 shows the number of categories processed within each 3-minute time period for the high-category conditions. The processing of number of categories was assessed for the highcategory conditions similar to the category usage analyses performed in Experiment 1. A 2 (presentation: sequential vs. simultaneous) X 10 (time interval) ANOVA yielded a main effect of presentation, f(l, 32) = 85.25,;? < .0001, indicating that participants in the simultaneous-presentation condition did process more categories than those in the sequential-presentation condition during each time interval. The main effect of time inter- 18 21 27 Time Interval (minutes) -0-High/Sequential -+-High/Simultaneous Figure 6. Category usage per 3-min interval as a function of presentation type for the high number of categories condition in Experiment 2. 30 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 322 COSKUN, PAULUS, BROWN, AND SHERWOOD val on category-processing performance was significant, F(9, 288) - 12.62, p < .0001, reflecting a reduction in number of categories used over time. The interaction effect between time interval and presentation also was significant, F(9T 288) = 4.68, p < .0003, indicating that the gap in number of categories processed between the simultaneous and sequential conditions became smaller over time. The perceptions of individual brainstormers regarding the number of ideas and quality of ideas they generated showed no significant effects for either problem presentation or number of categories. Model simulations of Experiment 2. Simulations of visually presented primes, as used in Experiment 2, are potentially more complex than modeling the auditory primes used in Experiment 1. Simultaneous presentation of written primes is truly all at once, and different individual brainstormers will probably read the items differently depending on a number of factors, such as attentional capacity, short-term memory capacity, knowledge of the task, and interest. The model is flexible enough to accommodate a number of individual variations on these parameters. We present the results of a simulation in which each brainstormer is as- 2 sumed to read a subset of words from the longer list and enter them simultaneously into shortterm memory. Categories were activated at equal intervals in both the sequential- and simultaneous-presentation conditions. In the sequential conditions, categories were activated one at a time, every seven time cycles. Tn the high-category-sequential condition, a different category was activated every seven cycles; in the low-category-sequential condition, 1 category was activated five times, and then a 2nd category was activated five times, as was done in the experiment. In the high-category-simultaneous condition, a random number of up to 7 categories, randomly chosen from the 10 available, were activated simultaneously, also every seven time cycles. In the low-category-simultaneous condition, 1 or 2 of the 2 available categories were randomly activated every seven time cycles. Each point in the figures represents the average of 15,000 tests. Short-term memory weight was set to 0.8 in the Experiment 2 simulations. As can be seen in Figure 7, the simulations predicted that this method of presentation would cause presentation type to have a much smaller effect on overall productivity than it did 3 4 5 Time Interval (simulated) -High/Sequential —•—High/Simultaneous —A—Low/Sequential -Low/Simultaneous —*— No Priming Figure 7. Model predictions for the number of ideas generated over time for the five conditions of Experiment 2. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION for the procedure used in Experiment 1. Both simultaneous and sequential priming seemed to be more effective than the control condition in which no primes were presented, especially when a high number of categories were primed. Because the primes were re-presented at the same intervals in both presentation conditions, both the simultaneous and sequential conditions provided a boost throughout the session. However, the effectiveness of the simultaneouspriming condition depended on the number of items scanned and the short-term memory weight. Much smaller values of either parameter caused the simultaneous condition to become less effective than the sequential condition, because the brainstormer was less able to process and retain the information provided by the cues. The simulations nicely reproduced the crossover of the high-sequential and highsimultaneous graphs, because idea generation declined much less rapidly in the sequential than in the simultaneous condition, even though overall output for the session was nearly equal for the two. Note that the model predicted a "bump" in the idea-generation graph for the sequential-low-category condition. This corre- 2 323 sponded to the change in categories presented to the brainstormer halfway through the session. This slight increase in idea generation did not appear to be visible in the empirical data, although the graph did seem to flatten out at that point. Figure 8 shows the simulations of category usage, which appear to nicely match the empirical data of Figure 6. The high-sequential condition maintained a much more even sampling of categories throughout the session than did the high-simultaneous condition. Category usage declined over time in this case; because the same categories were presented each interval, some of them were eventually sampled from more than others and thus were not as readily available as the session progressed. Discussion The main rinding of Experiment 2 is that presenting many categories of a problem enhances the generation of ideas for that problem. This is consistent with the notion that category labels provide explicit stimuli for a range of related ideas and with Osborn's (1957, 1963) 3 4 Time Interval (simulated) -^-High/Sequential -•-High/Simultaneous Figure 8. Model predictions for number of categories used each time interval for the high-category-simultaneous- and sequential-presentation conditions of Experiment 2. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 324 COSKUN, PAULUS, BROWN, AND SHERWOOD suggestion that the brainstorming problem should be very specific. The effect of number of categories also is consistent with both the Nagasundaram and Dennis (1993) and the Paulus et al. (2000) models of cognitive stimulation in groups. The greater the number of explicit stimuli (categories) encountered during the brainstorming session, the greater the number of ideas generated. However, there was no difference in performance due to type of problem presentation (simultaneous vs. sequential). The fact that in both of the problem-presentation conditions the task was broken into 3-min intervals may be critical. This feature controlled for differences in time restrictions or pacing. Although 10-min segments do not seem to have much impact on brainstorming performance (Dennis, Aronson, et al., 1996), smaller time segments may have more impact (Kelly & Karau, 1993) and may have eliminated the potential differences due to problem structuring. In addition, because the categories were re-presented at the start of each 3-min segment in both presentation conditions, both sets of participants were reminded of task-relevant categories instead of having to keep them in shortterm memory throughout the session. General Discussion Two experiments found that presenting groups and individuals with categorical information during performance of a brainstorming task increased the generation of ideas. In Experiment 1, when the category primes were presented either all at once at the start of the session (the simultaneous condition), or one at a time at 3-min intervals throughout the session (the sequential condition), sequential presentation led to the best performance for both interactive and nominal groups. Nominal groups outperformed interactive groups in both presentation conditions, and the effect of presentation type was stronger with nominals. Thus, although categorical priming seems to be an effective aid to brainstorming for both groups and individuals, it does not enable groups to overcome the productivity gap. Categorical priming may be more effective for individual performers because in group brainstorming, individuals may be exposed to ideas by other group members that do not fall into the category being primed. In Experiment 2, category primes were presented to individual brainstormers either simultaneously every 3 min during the brainstorming session or one category at a time at 3-min intervals, as in Experiment 1. In this case, there was little difference between the two methods of presenting the category primes. However, presenting primes to 10 categories did lead to greater idea generation than presenting primes to just 2 categories. These results suggest that the frequency of explicit category priming during a session may be a more important determinant of performance than how many primes are given at each presentation, at least for the fairly straightforward type of idea-generation task used in the present experiments. The brainstorming model of Brown et al. (1998) accounted qualitatively very well for the results of both experiments. The model suggests that brainstormer's short-term memory capacity plays a role in determining the effectiveness of externally presented primes. Presenting primes every so often throughout the session helps remind brainstormer's of the categories of ideas available to them. Figure 9 illustrates the role of short-term memory by showing how the performance of individual brainstormers changes as a function of short-term memory weight for the conditions of Experiment 1. The short-term memory parameter has little effect on performance in the sequential condition, presumably because the presentation of primes throughout the session is effective at activating the relevant categories of ideas in the (simulated) brainstorming participants. On the other hand, increasing the strength of short-term memory improves performance in the simultaneous conditions. When brainstormers are able to keep in mind the categories that are presented to them at the start of the session, they are less likely to need to be reminded of those categories throughout the rest of the session. However, the performance gap between the sequential and the simultaneous conditions is not eliminated until the short-term memory weight approaches the unrealistic value of one, representing perfect memory. There are at least two important factors that could influence an individual brainstormer's ability to keep in mind the information presented during an idea-generating session. One factor, which was discussed earlier, is the attention demands or degree of distraction present during the task. A second factor is the degree of This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION 325 15 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Short Term Memory Weight - O - Nominal/Sequential - O - Interactive/Sequential - Nominal/Simultaneous - Interactive/Simultaneous Figure 9. Effect of shoit-tenn memory weight on performance in model simulations of Experiment 1. experience the participants have had with the particular task or problem (i.e., their level of expertise). Experts who are highly familiar with a particular domain of knowledge or performance have usually developed a domain-specific organization of memory that allows them to keep in mind greater amounts of information, usually in the form of larger "chunks," than individuals who are less experienced in that domain (e.g., Ericsson & Charness, 1994). Another parameter of the model that will be affected by the attention demands of a particular brainstorming situation is the attention weight. In interactive settings, the more attention group members must devote to factors such as turntaking or evaluation concerns, the less attention they have to allocate to the ideas being presented by other group members. In the model, the attention weight represents the degree to which an individual is likely to use the ideas being presented by others. Figure 10 shows how the performance of individuals in interactive groups in the sequential- and simultaneouspriming conditions of Experiment 1 changes as a function of the amount of attention allocated to other group members' ideas. As was seen with the short-term memory weight, increased attention improves performance in the simulta- neous condition, but not in the sequential condition. Apparently, the simulations suggest, if group members are all attending closely to externally presented primes, attending to each other is unnecessary because the primes have already focused the group on a particular category. The sequential primes will be most effective in this way, when they are presented alone to provide a single focus and when they are sufficiently closely spaced to prevent brainstormers from wandering too much into other categories before the next prime is presented. Although we have interpreted the results of the two experiments in terms of cognitive processes, we also considered the potential influence of other mediating factors. Sequential task presentation may increase the pace of idea generation because of the task segmentation involved in this condition. This factor could explain the fact that differences in performance were obtained for task presentation in Experiment 1 (only the sequential task involved task segmentation) but not in Experiment 2 (both the sequential and simultaneous conditions involved task segmentation). However, this perspective would not predict that sequential presentation would have a more positive effect for nominal groups than interactive groups. Dennis, This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 326 COSKUN, PAULUS, BROWN, AND SHERWOOD 17 0.4 0.6 0.6 0.7 0.B 0.9 Attention Weight - O Interactive/Sequential - • - Interactive/Simultaneous Figure 10. Effect of attention weight on performance in model simulations of Experiment 1. Aronsoti, et al. (1996) also did not find support for the role of a pacing factor. However, given the evidence for the importance of pacing factors in productivity (Kelly & Karau, 1993), it may be that both pacing and cognitive factors play a role in the effects of task segmentation. Although our analysis of task decomposition has focused on brainstorming tasks, our findings have implications for any context in which groups share information or ideas. This could include teams engaged in knowledge work (Paulus, 2000), collaborative learning groups (Paulus & Paulus, 1997), and therapy groups involved in sharing personal information (Paulus, 2000). For example, in therapy groups, more effective accessing of feelings and relevant information may occur when the group is led to consider specific subaspects of a problem in sequence rather than focusing on all aspects of the problem as a whole. Although the model used to simulate the experiments presented here is not designed to model all the intricacies of interactions in complex social situations like therapy groups, it can be used to support the possibility that task decomposition may be an effective means of fa- cilitating group therapy discussions. In standard idea-generation situations, particularly those in the laboratory, the goal is generally just to produce as many ideas as possible; in fact, number of ideas produced is the standard dependent variable in the experimental brainstorming literature. Sheer quantity of verbal output is not necessarily the goal of group therapy. Although it is important that group members share experiences and ideas with each other, it is likely that those who share less or not at all may still benefit from the experience. What an individual gets out of a group therapy session, much like what one gets out of a class discussion or any other interaction where ideas and information are exchanged, depends on what thoughts and feelings the discussion generates in her or him, even if these thoughts and feelings are not actually expressed at the time. The model allows us to examine (hypothetically) the number of ideas generated by an individual during interactive brainslorming over and above the number of ideas he or she actually presented to the rest of the group. Figure 11 shows the hypothetical number of unspoken ideas generated by each individual in the interactive conditions of Ex- 327 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION 1 2 3 4 5 Time Interval (simulated) —O— Interactive/Sequential — # - Interactive/Simultaneous Interactlv«/No Priming Figure 11. Hypothetical number of unspoken ideas generated over time under the interactive conditions of Experiment 1. The dashed line represents the performance of a hypothetical no-priming condition. periment I. 6 Although the generation of ideas decreases over time for all conditions, brainstormers in the sequential condition seem to produce more unspoken ideas. The tendency to elicit more relevant thoughts and feelings would seem to be an advantage (although quite speculative at this point) of the sequential organization produced by problem decomposition. The present research suggests that group therapy sessions may be most effective in tapping the full range of thoughts and feelings of individuals when the group is encouraged to work through the topic in a sequential fashion. Although, to the extent that therapy sessions and brainstorming sessions share some common processes, the fact that nominal groups still outperform interacting groups in all of the experiments and simulations presented here suggests that individual therapy sessions may still be the most effective in facilitating full expression of feelings and ideas. We believe that experimental research and simulations are very useful in developing and testing theoretical models of group dynamics. To what extent can our and other findings from studies on laboratory group brainstorming be generalized to real-life settings? We believe that there is considerable potential for such application, but much additional research will be required to assess this potential, and applications may require significant fine-tuning (Paulus, 1996). In contrast, Ford (1999) has suggested that this type of laboratory research may have very limited applicability. He suggests that studies need to be done in more realistic contexts with a longer time frame. We strongly endorse this suggestion, and in fact, a number of such programs of research are ongoing (e.g., Dunbar, 1995; West, 1997). However, realism is no guarantee of generalizability from one context to another (Anderson & Bushman, 1997). For example, the research by Sutton and Hargadon (1996) that is highlighted by Ford as a model to emulate is basically an impressionistic study with no quantitative data on group process or comparison groups. Although these 6 The model generates output for the total number of ideas generated by each group member in addition to the number of ideas spoken by each member. This is because the model first generates ideas for each individual and then determines which individual is to be the speaker for a given time interval. Figure 11, depicting unspoken ideas, is the difference between the two. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 328 COSKUN, PAULUS, BROWN, AND SHERWOOD types of field studies provide interesting descriptions of real-world groups, they do not allow for clear theoretical conclusions. Moreover, the potential generalizability of laboratory research may be much greater than that suggested by the skeptics. Several reviews have demonstrated that findings from artificial laboratory studies in a number of empirical domains mesh quite nicely with those of field studies in more realistic contexts (Anderson & Bushman, 1997; Anderson, Lindsay, & Bushman, 1999). References Anderson, C. A., & Bushman, B. J. (1997). External validity of "trivial" experiments: The case of laboratory aggression. Review of General Psychology, 1, 19-41. Anderson, C. A., Lindsay, J. J., & Bushman, B. J. (1999). Research in the psychological laboratory: Truth of triviality? Current Directions in Psychological Science, 8, 3-9. Armstrong, J. S., Denniston, W. B., & Gordon, M. M. (1975). The use of the decomposition principle in making judgments. Organizational Behavior and Human Performance, 14, 257-263. Basden, B. H., Basden, D. R., Bryner, S., & Thomas, R. L. III. (1997). A comparison of group and individual remembering: Does group participation disrupt retrieval? Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 1176-1189. Basden, D. R., Basden, B. H., & Galloway, B. C. (1977). Inhibition with part-list cuing: Some tests of the item strength hypothesis. Journal of Experimental Psychology: Human Learning and Memory, 3, 100-108. Borgatta, E. F., & Bales, R. F. (1953). interaction of individuals in re-constituted groups. Sociometry, 16, 302-320. Bouchard, T. J., Drauden, G., & Barsaloux, J. (1974). A comparison of individual, subgroup, and total group methods of problem solving. Journal of Applied Psychology, 59, 226-227. Brown, V., & Paulus, P. B. (1996). A simple model of social factors in group brainstorming. Small Group Research, 27, 91-114. Brown, V., Tumeo, M., Larey, T. S., & Paulus, P. B. (1998). Modeling cognitive interactions during group brainstorming. Small Group Research, 29, 495-526. Camacho, L. M , & Paulus, P. B. (1995). The role of social anxiousness in group brainstorming. Journal of Personality and Social Psychology, 68, 1071-1080. Collaros, P. A., & Anderson, L. R. (1969). Effect of perceived expertness upon creativity of members of brainstorming groups. Journal of Applied Psychology, 53, 159-163. Collins, A. M., & Loftus, E. F. (1975). A spreadingactivation theory of semantic processing. Psychological Review, 82, 407-428. Connolly, T., Routhieaux, R. L., & Schneider, S. K. (1993). On the effectiveness of group brainstorming: Test of one underlying cognitive mechanism. Small Group Research, 24, 490-503. Cowan, N. (1995). Attention and memory: An integrated framework. New York: Oxford University Press. Dennis, A., Aronson, I., Heninger, B., & Walker, E. (1996). Task and time decomposition in electronic brainstorming. Proceedings of Hawaii International Conference on Systems Science, 3, 51-59. Dennis, A. R., Valacich, J. S., Connolly, T., & Wynne, B. E. (1996). Process structuring in electronic brainstorming. Information Systems Research, 7, 268-277. Diehl, M., & Stroebe, W. (1987). Productivity loss in brainstorming groups: Toward the solution of a riddle. Journal of Personality and Social Psychology, 53, 497-509. Diehl, M., & Stroebe, W. (1991). Productivity loss in idea generating groups: Tracking down the blocking effect. Journal of Personality and Social Psychology, 61, 392-403. Dunbar, K. (1995). How scientists really reason: Scientific reasoning in real-world laboratories. In R. J. Sternberg & I. E. Davidson (Eds.), The nature of insight (pp. 365-395). Cambridge, MA: MTT Press. Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725-747. Ford, C. M. (1999). Thinking big about small groups in the real world: Comment on Craig and Kelly (1999). Group Dynamics: Theory, Research, and Practice, 3, 257-262. Gallupe, R. B., Bastianutti, L. M., & Cooper, W. H. (1991). Unblocking brainstorms. Journal of Applied Psychology, 76, 137-142. Gettys, C. F., Pliske, R. M., Manning, C , & Casey, J. T. (1987). An evaluation of human act generation performance. Organizational Behavior and Human Decision Processes, 39, 23—31. Harari, O., & Graham, W. K. (1975). Task and task consequences as factors in individual and group brain storm ing. Journal of Social Psychology, 95, 61-65. Kelly, J. R., & Karau, S. J. (1993). Entrainment of creativity in small groups. Small Group Research, 24, 179-198. Lamm, H., & Trommsdorff, G. (1973). Group versus individual performance on tasks requiring ideational proficiency (brainstorming): A review. European Journal of Social Psychology, 3, 361-387. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. STIMULATION AND PRESENTATION Larey, T. S. (1994), Convergent and divergent thinking> group composition, and creativity in brainstorming groups. Unpublished doctoral dissertation, University of Texas at Arlington. Larey, T. S., & Paulus, P. B. (1999). Group preference and convergent tendencies in groups: A content analysis of group brainstorming performance. Creativity Research Journal, 12, 175-184. Mednick, S. A. (1962). The associative basis of creative process. Psychological Review, 69, 220-232. Mullen, B., Johnson, C , & Salas, E. (1991). Productivity loss in brainstorming groups: A meta-analytic integration. Basic and Applied Social Psychology, 12, 3-24. Nagasundaram, M., & Dennis, A. R. (1993). When a group is a not group: The cognitive foundation of group idea generation. Small Group Research, 24, 463-489. Neely, J. H. (1991). Semantic priming effects in visual word recognition: A selective review of current findings and theories. In D. Besner & G. W. Humphreys (Eds.), Basic processes in reading: Visual word recognition (pp. 264-350). Hillsdale, NJ: Erlbaum. Nunamaker, J. R Jr., Briggs, R. O., & Mittleman, D. D. (1995). Electronic meeting systems: Ten years of lessons learned. In D. Coleman & R. Khanna (Eds.), Groupware: Technology and applications (pp. 149193). Upper Saddle River, NJ: Prentice Hall. Offner, A. K., Kramer, T. J., & Winter, J. P. (1996). The effects of facilitation, recording, and pauses on group brainstorming. Small Group Research, 27, 283-298. Osborn, A. F. (1957). Applied imagination: Principles and procedures of creative problem-solving. New York: Scribner's. Osbom, A. F. (1963). Applied imagination: Principles and procedures of creative problem-solving (2nd ed.). New York: Scribner's. Oxley, N. L., Dzindolet, M. T., & Paulus, P. B. (1996). The effects of facilitators on the performance of brainstorming groups. Journal of Social Behavior and Personality, 11, 633-646. Paulus, P. B. (1996). Making groups effective: Easier written than done. Contemporary Psychology, 41, 612-613. Paulus, P. B. (2000). Groups, teams, and creativity: The creative potential of idea generating groups. Applied Psychology: An International Journal, 49, 237-262. ' Paulus, P. B., Brown, V., & Ortega, A. H. (1999). Group creativity. In R. E. Purser & A. Montuori (Eds.), Social creativity (Vol. 2, pp. 151-176). Cresskill, NJ: Hampton. Paulus, P. B., & Dzindolet, M. T. (1993). Social influence processes in group brainstorming. Journal of Personality and Social Psychology, 64, 575-586. View publication stats 329 Paulus, P. B., Dzindolet, M. T., Poletes, G., & Camacho, L. M. (1993). Perception of performance in group brainstorming: The illusion of group productivity. Personality and Social Psychology Bulletin, 19, 78-79. Paulus, P. B., Larey, T. S., & Dzindolet, M. T. (2000). Creativity in groups and teams. In M. Turner (Ed.), Groups at work: Advances in theory and research (pp. 237-262). Mahwah, NJ: Erlbaum. Paulus, P. B., Larey, T. S., Putman, V. L., Leggett, K. L., & Roland, E. J. (1996). Social influence processes in computer brainstorming. Basic and Applied Social Psychology, 18, 3-14. Paulus, P. B., & Paulus, L. E. (1997). Implications of research on group brainstorming in gifted education. Roeper Review, 19, 225-229. Pitz, G. F., Sachs, N. J., & Heerboth, J. (1980). Procedures for eliciting choices in the analysis of individual decision making. Organizational Behavior and Human Performance, 26, 396-408. Putnam, V. L., Paulus, P. B., Dugosh, K. L., & Coskun, H. (1999). Effects offacilitators and task instructions on productivity in brainstorming groups. Unpublished manuscript, University of Texas at Arlington. Raaijmakers, J. G., & Shiffrin, R. M. (1981). Search of associative memory. Psychological Review, 88, 93-134. Samson, D. (1988). Managerial decision analysis. Homewood, IL: Irwin. Sherwood, J. (1998). Modeling cognitive facilitation in brainstorming groups. Unpublished master's thesis, University of Texas at Arlington. Sherwood, J., Dugosh, L,, Brown, V., & Paulus, P. (2000). Predicting semantic priming effects in group brainstorming: A cognitive modeling approach Unpublished manuscript, Washington State University. Sutton, R. I., & Hargadon, A. (1996). Brainstorming groups in context: Effectiveness in a product design firm. Administrative Science Quarterly, 41, 685-718. 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., & Connolly, T. (1994). Idea generation in computer-based groups: A new ending to an old story. Organizational Behavior and Human Decision Processes, 57, 448-467. Vroom, V. H., Grant, L. D., & Cotton, T. S. (1969). The consequence of social interaction in group problem-solving. Organizational Behavior and Human Performance, 4, 77-95. West, M. A. (1997). Developing creativity in organizations. Leicester, England: British Psychological Society.

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