# Structuring Electronic Brainstorming Tasks to Improve Group Creativity: How Structuring Serially Can Benefit Idea Elaboration

Baptiste van Eeckhout, Nicolas Michinov, Karine Le Rudulier

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Baptiste van Eeckhout, Nicolas Michinov, Karine Le Rudulier. Structuring Electronic Brainstorming Tasks to Improve Group Creativity: How Structuring Serially Can Benefit Idea Elaboration. The Journal of Creative Behavior, 2025, 59 (2), 10.1002/jocb.70023. hal-05049667

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Article published in the *Journal of Creative Behavior*:

Van Eeckhout, B., Michinov, N., & Le Rudulier, K. (2025). Structuring electronic brainstorming tasks to improve group creativity: How structuring serially can benefit idea elaboration [special issue, Exploring the intersection of media, technology, and creativity]. *The Journal of Creative Behavior*. https://doi.org/10.1002/jocb.70023

# Structuring Electronic Brainstorming Tasks to Improve Group Creativity: How Structuring Serially Can Benefit Idea Elaboration

Baptiste van Eeckhout

Univ Rennes, LP3C (Psychology of Cognition, Behavior, Communication Laboratory), France

Nicolas Michinov

Univ Rennes, LP3C (Psychology of Cognition, Behavior, Communication Laboratory), France

Karine Le Rudulier

Univ Rennes, IGR-IAE, IODE (UMR CNRS 6262), France

Correspondence concerning this article should be sent to the following address: Nicolas

Michinov, LP3C, Université Rennes 2, place du Recteur Henri Le Moal, 35043, Rennes Cedex
(France). E-mail: nicolas.michinov@univ-rennes2.fr
Authors notes

ORCID iD

Baptiste van Eeckhout ID 0009-0000-4811-2122

Nicolas Michinov ID 0000-0002-6065-8061

Karine Le Rudulier ID 0009-0005-5265-9936

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship,
and/or publication of this article.

Funding

This research was supported by the the Agence Nationale de la Recherche, France 2030
programme (ANR-21-DMES-0001).

The data that support the findings of this study are openly available in OSF at:
[https://osf.io/re8az/](https://osf.io/re8az/)
ABSTRACT

For several decades, brainstorming in groups and its variants have been widely examined in research as a technique to produce ideas. The way to stimulate elaboration by linking ideas to those previously given by others during a brainstorming session is a challenge for researchers and practitioners aiming to go beyond idea generation. Despite Osborn’s (1953, 1963) rules inviting participants to build on ideas of their group members to produce their own, until recently very few research has explicitly examined idea elaboration and its determinants. The present study aimed to investigate how structuring an electronic brainstorming task using a digital environment to produce ideas freely or serially, might influence the elaboration of ideas in groups. A multilevel modeling analysis revealed that, independently of the groups, the quantity and quality of ideas produced, serial brainstorming led to a greater elaboration of ideas than free brainstorming. These findings provide the initial empirical evidence about the efficacy of structuring electronic brainstorming in a serial mode to stimulate idea elaboration in groups.

Keywords: group creativity, idea elaboration, building on others’ ideas, electronic brainstorming, digital collaborative environment.
# Structuring Electronic Brainstorming Tasks to Improve Group Creativity: How Structuring Serially Can Benefit Idea Elaboration

Brainstorming and its main variants, brainwriting and electronic brainstorming, are ideation techniques commonly used in studies on group creativity to generate ideas (Barrett et al., 2021; Le Hénaff et al., 2018; Michinov, 2012; Michinov & Jeanson, 2023; Nelson & Guegan, 2022; Paulus & Baruah, 2018; Peter et al., 2021). Since Osborn's (1953, 1963) book 'Applied imagination', a large number of studies have been conducted on brainstorming, and most of them have examined *fluency* (the number of ideas), *flexibility* (the number of idea categories), *originality* (the novelty of ideas). Far fewer studies have examined elaboration, selection and integration of ideas produced in a common brainstorming activity. The present study thus aimed to investigate idea elaboration in an electronic brainstorming session to answer the following questions: How can an electronic brainstorming task be structured to promote idea elaboration? How can elaboration from ideas produced by group members using virtual post-it® in a digital collaborative environment be measured?

## IDEA ELABORATION IN BRAINSTORMING RESEARCH

One of Osborn's main contributions was to propose four rules to optimize the efficacy of the brainstorming technique: (1) Criticism is ruled out; (2) *Freewheeling* is welcomed. The wilder the idea, the better; (3) Quantity is wanted. The greater the number of ideas, the more likely that ideas are useful; (4) Combination and improvement of ideas are sought. In addition to contributing ideas of their own, participants should suggest how the ideas of others can be turned into *better* ideas; or how two or more ideas can be combined in yet another idea. Concerning the fourth rule, many concepts have been used to describe the act of combining, improving or getting inspired by an idea such as elaborating, building on, linking, or piggybacking on others' ideas.
As there is a lack of agreement about the terminology used to describe this rule, we considered the different concepts interchangeably in the present research.
In proposing the fourth rule, Osborn (1953) thought that exposure to ideas, even unrealistic ones, would stimulate creativity of group members who could build on the ideas of others to generate their own. This proposition found an echo in Bormann's (1985) conception of idea chains. Chaining represents the process of adding an idea to another that resonates within the group and starting chains of original ideas leads to more and better ideas. As mentioned by Henningsen and Henningsen (2018), group members may 'build on' the ideas of other group members during an idea generation task leading to linking between ideas. Similarly, in order to study creativity processes in design, Goldschmidt (2014) developed the *linkography* technique based on creating links between different ideas. According to this approach, creativity develops over a large number of small steps, called "design moves" that combine together in a network of moves, and the patterns of links in a network expressing a "good fit". This technique was adapted to brainstorming by van der Lugt (2000) who replaced the design moves by the ideas of groups. While Goldschmidt (2014) relied on common sense to identify the links between design moves, van der Lugt (2000) used indicators to classify the type of links, such as similarity in association and reference to another idea.

Some research has examined the impact of Osborn's rules given simultaneously (Meadow et al., 1959; Parnes & Meadow, 1959) or separately (Litchfield et al., 2011; Nemeth et al., 2004; Paulus et al., 2011). However, studies examining the impact of the fourth rule inviting participants to build on others' ideas remain scarce to date and very little research has examined this question. Certain studies have highlighted the incompatibility of the freewheeling and build-on rules, referring to two alternative approaches that can be used to generate ideas (Goldenberg et al., 2013). The former refers to divergent thinking encouraging participants to think freely and generate as many ideas as possible. The latter implies convergent thinking, leveraging others' ideas as a starting point to generate new ones using a piggybacking process which consists in building on the ideas of others to link, combine, modify and expand the others' ideas. In their
study, Goldenberg et al (2013) varied these two rules during a brainwriting session consisting of writing ideas in interacting groups or nominal groups, that is, groups composed of the same number of individuals working alone. The effect of each of these rules was compared to a control condition in which both rules were given. The results showed that when the two rules were presented separately, interacting and nominal groups generated ideas from more semantic categories in response to the freewheeling rule, and generated more practical ideas in response to the build-on rule. However, one of the limitations of this study was that it only used divergent thinking measures and not idea elaboration based on building on others' ideas. This limitation is common to several studies, and in addition, the way to measure idea elaboration has not been extensively examined in the literature and when it was, different measures were used.

The majority of studies have examined the impact of brainstorming in groups using the three main indicators of divergent thinking (Guilford, 1967; Torrance, 1969): fluency, flexibility and originality (Michinov et al., 2015; Peter et al., 2021; Runco & Acar, 2012; Said-Metwaly et al., 2020). By contrast, fewer studies have used the fourth indicator - elaboration - that is, taking inspiration from other ideas to improve and develop them, for example adding details to a given idea or linking several ideas (Baruah et al., 2021; Baruah & Green, 2023; de Vreede et al., 2010; Gillier & Bayus, 2022; Kohn et al., 2011; McMahon et al., 2016; Qi et al., 2022). In their study, Kohn et al. (2011) asked participants to produce ideas as groups or individuals then switch conditions to combine and build on those ideas. They found that the rarity of the ideas used for combinations had an effect on the novelty and feasibility of the combination, and that people who brainstormed as groups preferred combining their own ideas, whereas people who brainstormed as individuals preferred using the ideas of others. In another study, Gillier and Bayus (2022) examined idea-generation sessions and analyzed the vocal interactions between participants within three-member groups. They used the *linkography* technique (van der Lugt, 2000) to identify the links between ideas of participants mentioning earlier ideas when they
verbalized their own. They found that the type of ideas, novel or feasible, had an effect on how different ideas were combined, novel ideas led to combining novel ideas, while feasible ideas led to combining feasible ideas. More recently, Baruah and Green (2023) divided participants into small groups in either anonymous or identified conditions, and measured different indicators of creativity including elaboration (number of details added to each core idea) at the three phases of the creative process (generation, selection and refinement). They found a higher proportion of idea elaboration was observed in the refinement phase than in the phases of generation and selection, which did not significantly differ from each other.

## STIMULATING IDEA ELABORATION IN GROUPS

Beyond studies examining the effect of Osborn's brainstorming rules, and specifically the fourth rule, other studies tried to stimulate idea elaboration indirectly by means of different techniques, either by exposing participants to a set of ideas (Paulus et al., 2013; Zhou et al., 2019), or using a circular or serial technique in which ideas were passed to another group member to facilitate linking to others' ideas (Korde & Paulus, 2017; Paulus & Yang, 2000). To our knowledge, only two studies measured idea elaboration using such techniques. One of them examined intragroup cooperation (Qi et al., 2022), while the other examined the effects of task structuring (de Vreede et al., 2010). In the study of Qi et al. (2022), participants generated ideas individually and then in groups. Idea elaboration during the group ideation phase was measured by assessing each idea on its level of elaboration from low (similar to the one produced independently by a member before joining the group) to high (totally different from any idea generated independently by an individual member before joining the group). In the study of de Vreede et al. (2010), participants of two different organizations were involved in an idea-generation task using an electronic brainstorming system. The task was structured either in a way in which ideas passed from a group to another (serial mode), or each group did the whole task (parallel mode). Idea elaboration was measured using an *elaboration coefficient*: number of ideas
containing a reference to a previously submitted idea divided by the total number of ideas.

Results showed that the serial mode led to more idea elaboration stimulating in-depth discussions around a solution, while the parallel mode led to more idea production.

Although the serial method has a positive impact on idea elaboration, this study did not examine the impact on elaboration of relaying ideas between members of the same group. Thus, the present study aimed to examine how linking one's own ideas to those of group members could be stimulated by structuring the brainstorming task following a serial mode. More specifically, a strategy constraining participants to piggyback on previous ideas to produce their own applying a serial method could contribute to promoting idea elaboration within groups. In this perspective, collaborative digital environments allow brainstorming tasks to be structured differently, freely when participants can produce their ideas as they want, or serially when they are constrained to produce their ideas following the previous ones.

## THE CURRENT STUDY AND HYPOTHESIS

During a seminar on entrepreneurship, participants were randomly divided into 20 teams and had 20 minutes to generate ideas about creating a company using Klaxoon®, a collaborative digital environment based on electronic brainstorming (https://klaxoon.com). All teams received Osborn's four brainstorming rules but only 10 groups worked freely in a brainstorming task to produce their ideas. The remaining 10 groups were invited to produce their ideas following a procedure consisting of relaying ideas produced by their group members in a serial mode. Idea elaboration was assessed by the number of links between ideas, and more specifically when a further idea contained a task-relevant reference to a previously submitted idea. In using such a technique, the number of links between ideas was identified as belonging to a chain measuring the first step of the idea elaboration process.

Based on previous findings (de Vreede et al., 2010), it is reasonable to consider that idea elaboration occurs by piggybacking on previous ideas generated by others. It was expected that
when there was a relay process between participants to produce their ideas, there would be a
greater probability that an original chain would develop, leading to greater idea elaboration in
groups, and consequently to more links between ideas. Thus, idea elaboration should be greater
in the brainstorming task in which participants had to produce their ideas serially rather than
freely.

METHOD

PARTICIPANTS

We estimated the sample size using G*Power 3.1 software. According to the
experimental design, power analysis determined that a minimum of 128 participants was
required, with a test power (1-β) set at 0.80, a probability of error (α) of 0.05, and a medium
effect size (d) of 0.5. In the present study, 142 students (72 female and 70 male) from a medium-
sized university in France were recruited. They were paired in groups, and randomly assigned to
two conditions, and gender balanced across conditions (see TABLE 1). Participants were in their
third year of enterprise management aged between 19 and 21years old, and were participating as
part of a team in a mandatory one-week seminar on entrepreneurship. They were assigned to
teams prior to the seminar and had to prepare together their own business project to present to a
judging panel at the end of the week. The 20 teams were randomly divided equally between the
control ('Free' brainstorming task) and the experimental ('Serial' brainstorming task) condition.
Teams ranged from five to eight members, and were gender balanced.
<table><caption>TABLE 1. Number (and percentage in parentheses) of male and female students in each team per condition</caption><thead><tr><th>Condition</th><th>Team</th><th>Male students</th><th>Female students</th><th>Team size</th></tr></thead><tbody><tr><td rowspan="10">Free</td><td>#7</td><td>3 (43%)</td><td>4 (57%)</td><td>7</td></tr><tr><td>#8</td><td>4 (50%)</td><td>4 (50%)</td><td>8</td></tr><tr><td>#9</td><td>2 (29%)</td><td>5 (71%)</td><td>7</td></tr><tr><td>#10</td><td>4 (50%)</td><td>4 (50%)</td><td>8</td></tr><tr><td>#11</td><td>5 (63%)</td><td>3 (38%)</td><td>8</td></tr><tr><td>#12</td><td>3 (38%)</td><td>5 (63%)</td><td>8</td></tr><tr><td>#13</td><td>1 (17%)</td><td>5 (83%)</td><td>6</td></tr><tr><td>#14</td><td>3 (60%)</td><td>2 (40%)</td><td>5</td></tr><tr><td>#19</td><td>7 (100%)</td><td>0 (0%)</td><td>7</td></tr><tr><td>#20</td><td>0 (0%)</td><td>8 (100%)</td><td>8</td></tr><tr><td rowspan="10">Serial</td><td>#1</td><td>2 (29%)</td><td>5 (71%)</td><td>7</td></tr><tr><td>#2</td><td>4 (50%)</td><td>4 (50%)</td><td>8</td></tr><tr><td>#3</td><td>2 (29%)</td><td>5 (71%)</td><td>7</td></tr><tr><td>#4</td><td>6 (75%)</td><td>1 (13%)</td><td>8</td></tr><tr><td>#5</td><td>3 (43%)</td><td>4 (57%)</td><td>7</td></tr><tr><td>#6</td><td>5 (63%)</td><td>3 (38%)</td><td>8</td></tr><tr><td>#15</td><td>3 (60%)</td><td>2 (40%)</td><td>5</td></tr><tr><td>#16</td><td>4 (67%)</td><td>2 (33%)</td><td>6</td></tr><tr><td>#17</td><td>4 (57%)</td><td>3 (43%)</td><td>7</td></tr><tr><td>#18</td><td>7 (88%)</td><td>1 (13%)</td><td>8</td></tr><tr><td colspan="2">Total</td><td>3.6 (50%)</td><td>3.6 (50%)</td><td>7.15</td></tr></tbody></table>

## MATERIALS AND INSTRUMENTS

The Klaxoon® collaborative digital environment was used for two main reasons: (1) It included an electronic brainstorming system giving participants the possibility to produce their ideas in groups by means of virtual post-its® posted on a shared whiteboard of infinite space; (2) It enables the administrator to build templates to structure the task to help teams to collaborate.

## PROCEDURE
The study was conducted in accordance with the Declaration of Helsinki, the General Data Protection Regulation (GDPR), and was approved by the Ethics Committee of the University (ethics attestation no. 2025-005).

The experiment was designed as part of a seminar entitled “The Countertops of Creation”. Participants were informed of the procedure on the first day during the seminar presentation by the teacher and the experimenter. During the seminar, all teams had their own space on Microsoft Teams® to communicate with the teacher and the experimenter. This space was used to give the task instructions and brainstorming rules; it also included a web link to access their team’s board on the Klaxoon® collaborative digital platform. They were told that the board provided for the brainstorming task would be used as a starting point for their business project.

Participants from different groups were assigned a room to work in during the seminar, there were between two and four groups in a room, and each group was under the same experimental or control condition. The experimenter went to each room to initiate the task and provide working instructions. The task was presented as pertaining to the course, aiming to help them initiate their project by generating original and useful ideas. The experimenter told them that the time to be spent in each room was set at 30 minutes, including 10 minutes to present and prepare, and 20 minutes to perform a brainstorming task using a digital collaborative platform. First, participants were invited to access their team’s board by clicking on the web link of their usual course space on Microsoft Teams®. When connecting to their board, each group member had to choose a color in which to write their ideas to ensure that they would be recognized by the others. As students had already used the Klaxoon® collaborative digital platform with their teachers prior to the seminar, they had a certain familiarity with it, making a habituation phase unnecessary. Second, once participants were connected, the experimenter explained the working instructions orally, insisting that they had to work silently in each group to produce their ideas.
## TASK STRUCTURATION AND IDEA ELABORATION

All groups were given Osborn's four brainstorming rules, both orally by the experimenter in the room and written on their board. After this the participants in each group began the brainstorming task.

Participants were given 20 minutes to generate the most ideas they could about their business project without communicating orally in their room so as not to disturb the work of other groups. Two brainstorming structuration tasks were designed to evaluate the quality of idea elaboration. In both conditions, participants had to follow the four brainstorming rules: (1) Criticism is ruled out; (2) *Freewheeling* is welcomed; (3) Quantity is wanted; and (4) Combination and improvement of ideas are sought.

In the control condition, participants accessed a blank board that they could use freely to produce their ideas as they wanted in a large pooling space. In the experimental condition, each participant was assigned a specific column to write their ideas in. Once they had generated one idea, they moved right to the adjacent column where another group member had written an idea, and they had to generate a new idea. The person in the last column on the right had to move to the first column on the left (see Appendix A for an overview of the board in the serial brainstorming condition). They followed this procedure until the end of the time allocated to the task.

At the end of the task the experimenter verified that the participants downloaded both the board of each group in a PDF format and an Excel file containing all the ideas of each participant in a group organized chronologically from the first to the last idea.

## MEASURES

*Number of ideas.* The quantity of ideas produced by each participant was counted to calculate fluency.

*Idea elaboration.* The number of ideas that linked (or did not link) to a previous one was counted for participants in all the groups. A link between two ideas was defined both by a similarity in contents and in associations (see van der Lugt, 2000). Two ideas were considered linked when
they referred to similar semantic elements. Unlike the clustering technique (Nijstad & Stroebe, 2006), semantic categories were not assigned to ideas given by each group member, but for each time an idea referred to a concept mentioned in a previous idea it was considered as linked to this new idea. In cases where several ideas contained a reference to many previous ideas, links were considered to follow a chronological order to form a chain (the first idea being linked to the second that was linked to the third, etc.). Although the links between ideas was a minimal indicator, it was nonetheless a first step in the idea elaboration process. Indeed, for ideas to be combined, or to be improved, a link has to be made between them, either between two pre-existing ideas to combine them, or between a pre-existing idea and a new idea derived from it to improve them. Therefore, elaborated ideas should share more similarities than non-elaborated ideas. An idea elaboration index was calculated by subtracting the number of linked ideas from that of unlinked ideas. A positive idea elaboration index meant that a participant began to build on the ideas of others, while a negative index meant that the majority of ideas were produced without being linked to previous ideas. In this latter case, the probability that ideas are elaborated is reduced.

For coding the link between ideas, a research assistant read all the ideas of a group and marked those that had an association with one or more previous ideas, as well as the number of each of those ideas in order to keep a trace of the idea elaboration process (see TABLE 2 for a coding procedure illustration). The process was conducted twice to limit the risk of mistakes or oversight. Moreover, to ensure the reliability of the measure a second rater scored about 20% of the data using the same procedure and the percentage agreement was 83% for the number of linked ideas.
TASK STRUCTURATION AND IDEA ELABORATION

<table><caption>TABLE 2. Illustration of the coding procedure of idea elaboration.</caption><thead><tr><td>Order of ideas</td><td>Idea description</td><td>References to previous ideas</td><td>Idea associations</td></tr></thead><tbody><tr><td>1</td><td>Highest lifespan possible</td><td>—</td><td>No association (0 link)</td></tr><tr><td>2</td><td>Having a system to recycle every part</td><td>—</td><td>No association (0 link)</td></tr><tr><td>3</td><td>Avoiding planned obsolescence by using high quality components</td><td>Planned obsolescence is linked with lifespan</td><td>Idea #3 is associated with idea #1 (1 link)</td></tr><tr><td>4</td><td>To validate our corporate social responsibility, we could use components made with recycled materials</td><td>Recycling and components have been referred to in previous ideas</td><td>Idea #4 is associated with ideas #2 and #3 (2 links)</td></tr><tr><td>5</td><td>Producing locally with materials that respect the environment</td><td>Material has been referred to in a previous idea</td><td>Idea #5 is associated with idea #4 (1 link)</td></tr><tr><td>6</td><td>Maybe we can use components from old fridges?</td><td>Components have been referred to in previous ideas</td><td>Idea #6 is associated with idea #4 (1 link)</td></tr></tbody></table>

*Note.* The group's topic was to design a “smart fridge”, and the ideas have been translated from French. In this selection of 6 ideas, 5 links were counted as a measure of idea elaboration.
*Originality and utility of ideas.* The quality of ideas produced by each group member was coded by two raters blind to the hypotheses and trained to use the “quasi-experts” procedure defined by Kaufman et al. (2013) and Reiter-Palmon (2020). The use of “quasi-experts” can be an appropriate substitute to using experts in Amabile's (1982) Consensual Assessment Technique (see Kaufman et al., 2013). Indeed, as it was not possible to have experts to rate ideas of each group project pertaining to very different topics, this procedure appeared as particularly well-adapted to the context. Thus, two laboratory engineers were recruited to code the ideas, and because they were not experts in creativity, a definition of originality and utility was proposed. For the former criterion, raters had to evaluate the degree of novelty of the ideas on a five-point Likert scale; for the latter, they had to evaluate on a similar scale whether the ideas were appropriate and useful in the context of the project and specific to each group. When an idea could not be coded, the raters rated a zero. To perform the coding task, all the ideas produced in each group were listed in a common master list to be rated by the two raters individually. A total of 1,000 ideas from the different groups were listed and among them, 598 were coded on originality and utility (59.8%). Nearly 40% of the remaining ideas were not rated due to insufficient information about the context.

The coding procedure began by a training session for one hour in which the two raters learned the context of each entrepreneurship project, and notably the topic of the project (e.g., mobility for seniors, disabled-friendly sports halls or an innovative refrigerator). The objective was to share a clear understanding of each project and to apply a similar coding strategy. Then, the two raters evaluated individually a sub-sample of about fifty ideas, and a comparison was made between their ratings by means of a correlation analysis. They discussed the reasoning for their ratings and potential points of disagreement. The raters followed the same procedure until they converged toward similar coding with sufficient inter-reliability. They were given a week to rate individually the list of ideas of each group. Then, a master list of ideas was compiled to
evaluate the inter-rater reliability which was satisfactory. Indeed, a significant Pearson
correlation between the ratings was observed both on originality (r = .47, p < .001) and utility of
the ideas (r = .42, p < .001) for the entire list of ideas produced by the groups. The evaluations of
each rater were averaged in two distinctive scores (originality and utility). As generally observed
in the literature (Paulus, 2020), a significant negative correlation was found between these two
scores (r = -.37, p < .001).

ANALYTIC STRATEGY AND RESULTS

To test whether task structuring predicts idea elaboration, we applied a linear mixed
model using the GAMLj package which is based on the R language, and available in the Jamovi
software (Gallucci, 2020; T. Snijders & Bosker, 2012; *The Jamovi project*, 2022). Linear mixed
models enable multilevel data analyses to be conducted by grouping individual data based on the
defined clusters (in this case groups) and allowing both fixed and random effects. Multilevel
model variability at the between as well as within cluster levels simultaneously, enabled these
variance components to be studied separately. In our model, the participant idea elaboration
score was considered as the dependent variable, the brainstorming structuring task as a fixed
factor, the number of ideas produced, and the originality and utility scores as covariates taking
into account random intercepts for groups. The model included random intercepts for groups to
account for the non-independence of data in the generation and elaboration of ideas. As a
relatively small sample size at the higher level was used in this study (20 groups), a restricted
maximum likelihood estimation was privileged because it performs more favorably in
comparison to full maximum likelihood (McNeish, 2017). Indeed, the sample size at the higher
level must be large with ideally at least 50 units, although between 10 and 30 groups at the
higher level can be considered as correct (Maas & Hox, 2005; T. A. B. Snijders, 2005). At a
lower level, 30 units per group is recommended (Bickel, 2017), although a lower number of five
units per group is acceptable (Maas & Hox, 2005).
We adapted the multilevel modeling procedure used by Aguinis et al. (2013) without testing the cross-level interaction effect as the sample size was too small. Running a multilevel model accounted for the nested structure of the data set in which individuals’ ideas (Level 1) were nested within groups (Level 2), a frequent situation in research (Luke, 2004; Nezlek, 2008). Mixed-effects models are called mixed because they simultaneously test fixed and random effects models. Fixed effects models average trends, whereas random effects models indicate the extent to which these trends vary across levels of a grouping factor (see Brown, 2021). We studied individual-level (Level 1) and group-level (Level 2) predictors of idea elaboration within groups.

Three models were tested successively. Model 1, the null model with no predictor was used to check the variability between groups without inserting the other variables, predictor and covariates. In allowing intercepts (group means on idea elaboration) to randomly vary, this model was used to verify whether the data provided evidence to assess the random effects at the group level. Model 2 was an adjustment for the individual level variables (number, originality and utility of ideas produced) used as covariates. Model 3 was an adjustment for the group level variable which was significant at the individual level when the predictor variable (brainstorming task structure) was entered into the equation. The results are presented in TABLE 3.

Firstly, the Intraclass Coefficient Correlation (ICC) is what we were trying to lower as successive models were tested. A decrease in the ICC from 42% (Model 1) to 31% (Model 3) was observed, suggesting a reduction in group variability when the structure of the brainstorming task was taken into consideration in the model.

Secondly, the *Pseudo R*² refers to the proportion of reduction in the variance (within and between groups), and revealed a 67% reduction in variation between groups when structuring the brainstorming task in two different ways, freely or serially.
Finally, and as shown in FIGURE 1, a significant effect of task structuring was observed, *t*
(18.7) = 3.06, *p*=.007, with participants in the serial brainstorming condition demonstrating
greater idea elaboration (*M* = 2.42) than those in the free brainstorming condition (*M* = -0.33).

Results also showed no significant effects of the covariates relative to the number of ideas or the
utility of ideas, and a marginally significant effect of the originality of ideas (p= .076).

Moreover, a significant positive correlation between the idea elaboration index and the
originality of ideas was observed (r = .19, p < .05), suggesting that a greater elaboration of ideas
(i.e. ideas linked to each other) resulted in ideas that were more original. No correlation was
found between the quantity of ideas produced and their quality (elaboration, originality and
utility of ideas).

To examine more thoroughly whether the idea elaboration index based on the difference
between the linked and unlinked ideas reflected an elaboration process, the number of words and
characters contained in each idea written on virtual post-its® were counted. Interestingly, positive
and significant correlations were found between the idea elaboration index and both the number
of words (*r* = .18, *p* < .05) and the number of characters used in each idea (*r* = .37, *p* < .001).

Although the idea elaboration index did not count how many details were added to an idea
compared to another, these indicators suggest that the index has a relative validity because
greater linking between ideas resulted in ideas which were richer.
**FIGURE 1.** Scores on idea elaboration index according to the brainstorming task structure, controlling the originality of ideas.

<figure><img src="image_2.png" /></figure>
TASK STRUCTURATION AND IDEA ELABORATION

<table><caption>TABLE 3. Multilevel Modeling Analysis with Model Parameters for Linear Changes on the Idea Elaboration Index (Number of linking ideas minus Number of non-linking ideas)</caption><thead><tr><th rowspan="2">Level and variables</th><th colspan="9">Model</th></tr><tr><th>Null<br>(Step 1)</th><th>Random Intercept and<br>Fixed Slope<br>(Step 2)</th><th>Random Intercept and<br>Random Slope<br>(Step 3)</th></tr></thead><tbody><tr><td><strong>Level 1 (individuals)</strong></td><td></td><td></td><td></td></tr><tr><td>Intercept</td><td>1.04+</td><td>(0.53)</td><td>[0.00006, 2.08]</td><td>0.57</td><td>(0.80)</td><td>[-1.003, 2.149]</td><td>-3.64</td><td>(2.47)</td><td>[-8.489, 1.197]</td></tr><tr><td>Number of ideas</td><td></td><td></td><td></td><td>0.06</td><td>(0.08)</td><td>[-0.102, 0.235]</td><td>0.10</td><td>(0.08)</td><td>[-0.071, 0.267]</td></tr><tr><td>Originality of ideas</td><td></td><td></td><td></td><td>0.93</td><td>(0.57)</td><td>[-0.185, 2.043]</td><td>0.98+</td><td>(0.55)</td><td>[-0.095, 2.058]</td></tr><tr><td>Utility of ideas</td><td></td><td></td><td></td><td>0.48</td><td>(0.48)</td><td>[-0.463, 1.428]</td><td>0.57</td><td>(0.48)</td><td>[-0.367, 1.516]</td></tr><tr><td>Brainstorming task structure</td><td></td><td></td><td></td><td></td><td></td><td></td><td>2.75**</td><td>(0.90)</td><td>[0.899, 0.988]</td></tr><tr><td><strong>Level 2 (groups)</strong></td><td></td><td></td><td></td></tr><tr><td>Within-Group variance</td><td></td><td>6.60</td><td></td><td></td><td>6.56</td><td></td><td></td><td>6.64</td><td></td></tr><tr><td>Between-group variance</td><td></td><td>4.70</td><td></td><td></td><td>4.72</td><td></td><td></td><td>3.02</td><td></td></tr><tr><td><strong>Additional information</strong></td><td></td><td></td><td></td></tr><tr><td>ICC</td><td></td><td>0.42</td><td></td><td></td><td>0.42</td><td></td><td></td><td>0.31</td><td></td></tr><tr><td>Log likelihood</td><td></td><td>-352.60</td><td></td><td></td><td>-351.81</td><td></td><td></td><td>-346.99</td><td></td></tr><tr><td>Number of estimate parameters</td><td></td><td>1</td><td></td><td></td><td>3</td><td></td><td></td><td>4</td><td></td></tr><tr><td>Pseudo R<sup>2</sup> (reduction in variation<br>between groups)</td><td></td><td>0</td><td></td><td></td><td>0.003</td><td></td><td></td><td>0.67</td><td></td></tr></tbody></table>

Note. Level 1 sample size = 142 and Level 2 sample size = 20. Values in parentheses are standard errors; 95% confidence intervals are between the square brackets; t-statistics were computed as the ratio of each regression coefficient divided by its standard error. Brainstorming task was coded with 1 = free and 2 = serial.

+ p < .10, *p < .05, **p < .01
Additional analyses on the length of the chains of ideas

For further analysis on the elaboration process, the number and the length of the chains of ideas in each group was counted to reinforce the previous results. As some idea chains may contain a same idea (in the case when one idea is linked to several others) we also measured the number of clusters. A cluster was defined as a group of ideas linked to each other through idea chains. This allowed us to observe whether the idea chains tended to be independent or connected to one another. Figure 2 illustrates the chains of ideas on the topic of a “smart fridge” based on the example given in Table 2. In this example, the links between ideas are represented by arrows. We observe two chains of idea, one starting at idea 1 and the other starting at idea 2. The length of the first chain is 5 ideas, whereas the second chain is 4 ideas. All 6 ideas make up one cluster, as they are all linked together.

<figure><img src="image_3.png" /><figcaption>FIGURE 2. Visualization of the chains of ideas about the topic of a “smart fridge”.</figcaption></figure>

However, due to the small sample (10 groups per condition), we were unable to conduct group level analyses and we only used these data for descriptive information to provide a fine-grained picture of the quality of idea elaboration according to either free or serial task structuring. The data for each group are available in supplementary materials in our OSF project.
On the one hand, the analyses revealed that in the free brainstorming condition, the number of idea chains was heterogeneous (ranging from 5 to 48), whereas it was more homogeneous in the serial brainstorming condition (ranging from 8 to 24). This would suggest that the serial structuration of brainstorming leads to low variability between groups, participants tending to focus on a reduced number of idea chains compared to the free brainstorming condition (see Table 4).

On the other hand, the chains were longer in the serial than in the free brainstorming condition, suggesting that ideas are elaborated more when the brainstorming task is serially structured. In addition, there was half the number of clusters in the serial compared to the free brainstorming condition. Taken together, these results suggest that when the brainstorming task was serially structured ideas were analyzed in depth, while in the free brainstorming condition ideas were analyzed more superficially with more fragmented chains of ideas.

<table><caption>TABLE 4. Descriptive analyses of the chains of ideas at a group level according to condition</caption><thead><tr><th>Condition</th><th>Number of idea chains</th><th>Mean number of idea chains</th><th>Mean length of idea chains</th><th>Mean number of clusters</th></tr></thead><tbody><tr><td>Free</td><td>5-48</td><td>16.8</td><td>3.22</td><td>8.0</td></tr><tr><td rowspan="2">Serial</td><td rowspan="2">8-24</td><td>14.3</td><td>5.28</td><td>4.4</td></tr><tr><td>15.55</td><td>4.25</td><td>6.2</td></tr></tbody></table>

DISCUSSION

The present study aimed to determine how to stimulate and measure idea elaboration by acting on the structuring of an electronic brainstorming task. Despite the multitude of studies examining group creativity (see Paulus et al., 2012, 2023; Paulus & Kenworthy, 2020; for reviews), the large majority have focused on divergent thinking measures such as fluency,
flexibility and originality of ideas, whereas fewer studies have focused on elaboration (Baruah &
Green, 2023; de Vreede et al., 2010; Gillier & Bayus, 2022; Kohn et al., 2011; Qi et al., 2022).

However, understanding how individuals piggyback on the ideas of their group members is a
true challenge to stimulate group creativity, notably using collaborative digital environments to
structure the brainstorming task. Brainstorming tasks structured to foster the linking of different
ideas, in which group members build on the ideas of others, remains overlooked today, except in
rare studies (de Vreede et al., 2010; Qi et al., 2022). For example, greater idea elaboration was
found when participants had to pass their ideas from a sub-group to another in a serial mode
(de Vreede et al., 2010). Based on these findings, it was expected that structuring an electronic
brainstorming task serially rather than freely should influence the elaboration of ideas in groups.

Indeed, the more participants can piggyback on others’ ideas, namely, linking their ideas to
previous ones, the greater the probability that an original chain would develop, leading to a
greater idea elaboration in groups. As predicted, the results of the present study revealed that, in
comparison to free structuring, a serially structured brainstorming task led participants to
produce a greater number of linked ideas (compared to unlinked ideas). Moreover, this effect
was observed independently of the group participants belonged to, or the number and quality of
ideas they produced. In other words, when the task constrained participants to relay an idea
subsequent to ideas given by other group members, they demonstrated greater elaboration.

This study contrasts with a large amount of brainstorming research which does not
propose structuring the task to stimulate idea generation, except for example brainstorming tasks
consisting in alternating individual and group sessions (V. R. Brown & Paulus, 2002; Girotra et
al., 2010; Korde & Paulus, 2017), reading ideas produced by others (Michinov, 2012; Paulus &
Yang, 2000), focusing on one or several topics at the same time (Dennis et al., 1999) or adding
breaks (Offner et al., 1996; Paulus et al., 2006). However, even in studies in which tasks are
structured, it is worth noting that participants are left free to produce their ideas as they want
instead of being directed to build on others' ideas.

As in all research, our study is not without limitations. Since our method did not include
any sort of communication because group members had to produce their ideas silently, we did
not have access to communication processes involved during the idea-generation task. Thus, the
links between ideas had to be deduced from the group production itself and not directly observed
from verbal recordings as in the Gillier and Bayus (2022) study. This was why similarity in
contents and in associations was used to define a link between two ideas and why links were
considered to follow a chronological order. This limits our analysis since we could neither
qualify the elaboration process applying techniques such as *linkography*, nor observe idea
transformation and combination. However, additional analyses revealed that the idea elaboration
index was correlated to the number of words and characters used in ideas written on virtual post-
its®, suggesting that the more ideas were linked to each other, the richer they were, i.e. ideas
were elaborated using more words and/or more complex language. Although the idea elaboration
index did not examine the number of details added to a new idea developed from a previous idea,
the number of words and characters used in ideas can be considered as an indicator of the
elaboration process.

Further analyses also provided additional information about the number and length of the
chains of ideas within groups according to the two conditions. It reveals that structuring the
brainstorming serially led to longer chains of ideas with fewer clusters in idea chains than in the
free brainstorming condition, suggesting that ideas were elaborated more when the brainstorming
task was serially structured. Taken together, these analyses provide more arguments supporting
that serial structuring of electronic brainstorming has a positive effect on idea elaboration. In
general, a free structuring mode of brainstorming is used in both research and practice, but the
present findings suggest that it leads to less idea elaboration than serial brainstorming, and
therefore the latter should be privileged to boost group creativity. Future studies should include diverse measures of elaboration in order to determine how exactly the elaboration process is influenced by serial structuring of the task. For example, questionnaires could be used to observe how group members perceived whether the task was influenced by the serial structure. Other measures of elaboration can also be used based on the number of details following a core idea (Baruah et al., 2021; Baruah & Green, 2023) or by assessing the level of elaboration of each idea using a questionnaire (Qi et al., 2022). It is reasonable to consider that multiple measures of idea elaboration would improve knowledge on the process.

The strength of our study is that it was performed in a real educational context with an authentic challenge for each group to conduct a business project. However, its weakness compared to laboratory experiments, was that the number of different categories of ideas - flexibility - that could be extracted was reduced. Indeed, each group worked on its own entrepreneurship project, and had its own unique subject to work on during the brainstorming session. Indeed, Kohn et al. (2011) and Gillier and Bayus (2022) showed in their studies that the properties of ideas from combination and building-on processes may vary depending on the idea on which they are based, indicating that the elaboration may have a positive or negative effect on idea quality and originality. Although this field study did not enable the same topic to be proposed to all the groups, a coding procedure based on “quasi-experts” was applied to rate each idea on two criteria, originality and utility (Kaufman et al., 2013; Reiter-Palmon, 2020). A marginal effect of originality, considered as covariate, was observed on idea elaboration, and a positive correlation between the idea elaboration index and originality was found, suggesting that with greater linking between ideas, the ideas produced are more original. These findings are consistent with previous studies revealing mixed findings in the relationship between elaboration and originality of ideas. While some researchers have demonstrated that more elaboration yields better ideas (Gonthier & Besançon, 2024), others have shown that elaboration may hinder the
## TASK STRUCTURATION AND IDEA ELABORATION

production of original ideas (Dippo & Kudrowitz, 2015). The present study suggests that idea elaboration measured by the linking between ideas is positively related to originality. Further research is required to examine the relationship between idea elaboration and originality.

Furthermore, there was no mandatory standardized summary of the projects. This meant there was no opportunity to analyze the selection of ideas and their integration into a common production. Despite these limitations, knowing how to stimulate idea elaboration in groups is important because building on others' ideas could be a significant predictor of the novelty of production (Baruah & Green, 2023; Coursey et al., 2019; Kenworthy et al., 2021).

## CONCLUSION

As recently stated by Paulus et al. (2023), more research is needed “on the factors that enhance the elaboration process” (p. 10). In this perspective, the present study provides empirical evidence about the way to structure a brainstorming task to elicit greater idea elaboration, and a serial structure appears promising. Indeed, our study indicates that idea elaboration can be stimulated by using a serial structure during electronic brainstorming in groups, while the majority of other studies have left participants free to produce their ideas. This finding can be used to guide ideation in teams to explore some categories of ideas and/or ensure that the team members try to deepen their reflection and produce elaborated and developed ideas. It indicates that it is possible to influence idea elaboration in an experimental setting by using specific templates to guide the teams. Group creativity is complex and there are different strategies to evaluate how creative a group is, and the serial structure is not the sole technique. Nevertheless, structuring a digital environment based on collaboration may be a simple and elegant solution when electronic brainstorming is used to promote group creativity.

## REFERENCES

* Aguinis, H., Gottfredson, R. K., & Culpepper, S. A. (2013). Best-practice recommendations for estimating cross-level interaction effects using multilevel modeling. *Journal of Management, 39*(6), 1490-1528. https://doi.org/10.1177/0149206313478188
Amabile, T. M. (1982). Social psychology of creativity: A consensual assessment technique. *Journal of Personality and Social Psychology, 43*(5), 997-1013.
https://doi.org/10.1037/0022-3514.43.5.997

Barrett, M. S., Creech, A., & Zhukov, K. (2021). Creative collaboration and collaborative creativity: A systematic literature review. *Frontiers in Psychology, 12*, 713445.
https://doi.org/10.3389/fpsyg.2021.713445

Baruah, J., & Green, K. (2023). Innovation in virtual teams: The critical role of anonymity across divergent and convergent thinking processes. *The Journal of Creative Behavior*, jocb.603. https://doi.org/10.1002/jocb.603

Baruah, J., Paulus, P. B., & Kohn, N. W. (2021). The effect of the sequence of creative processes on the quality of the ideas: The benefit of a simultaneous focus on originality and feasibility. *The Journal of Creative Behavior, 55*(4), 946-961.
https://doi.org/10.1002/jocb.500

Bickel, R. (2017). *Multilevel analysis for applied research: It's just regression!* Guilford Press.

Bormann, E. G. (1985). Symbolic convergence theory: A communication formulation. *Journal of Communication, 35*(4), 128-138. https://doi.org/10.1111/j.1460-2466.1985.tb02977.x

Brown, V. A. (2021). An introduction to linear mixed-effects modeling in R. *Advances in Methods and Practices in Psychological Science, 4*(1), 251-258.
https://doi.org/10.1177/2515245920960351

Brown, V. R., & Paulus, P. B. (2002). Making group brainstorming more effective: Recommendations from an associative memory perspective. *Current Directions in Psychological Science, 11*(6), Article 6. https://doi.org/10.1111/1467-8721.00202

Coursey, L. E., Gertner, R. T., Williams, B. C., Kenworthy, J. B., Paulus, P. B., & Doboli, S. (2019). Linking the divergent and convergent processes of collaborative creativity: The impact of expertise levels and elaboration processes. *Frontiers in Psychology, 10*, 699.
https://doi.org/10.3389/fpsyg.2019.00699

Dennis, A. R., Aronson, J. E., Heninger, W. G., & Walker, E. D. (1999). Structuring time and task in electronic brainstorming. *MIS Quarterly, 23*(1), 95. https://doi.org/10.2307/249411

de Vreede, G.-J., Briggs, R. O., & Reiter-Palmon, R. (2010). Exploring asynchronous brainstorming in large groups: A field comparison of serial and parallel subgroups. *Human Factors, 52*(2), Article 2. https://doi.org/10.1177/0018720809354748

Dippo, C., & Kudrowitz, B. (2015). The effects of elaboration in creativity tests as it pertains to overall scores and how it might prevent a person from thinking of creative ideas during the early stages of brainstorming and idea generation. *Volume 7: 27th International Conference on Design Theory and Methodology*, V007T06A007.
https://doi.org/10.1115/DETC2015-46789

Gallucci, M. (2020). *GAMLj suite for jamovi* [Logiciel]. https://github.com/gamlj/gamlj

Gillier, T., & Bayus, B. L. (2022). Group creativity in the wild: When building on ideas enhances the generation and selection of creative ideas. *Creativity and Innovation Management, 31*(3), 430-446. https://doi.org/10.1111/caim.12509

Girotra, K., Terwiesch, C., & Ulrich, K. T. (2010). Idea generation and the quality of the best idea. *Management Science, 56*(4), 591-605. https://doi.org/10.1287/mnsc.1090.1144

Goldenberg, O., Larson, J. R., & Wiley, J. (2013). Goal instructions, response format, and idea generation in groups. *Small Group Research, 44*(3), 227-256.
https://doi.org/10.1177/1046496413486701

Goldschmidt, G. (2014). *Linkography: Unfolding the design process*. The MIT Press.
https://doi.org/10.7551/mitpress/9455.001.0001

Gonthier, C., & Besançon, M. (2024). It is not always better to have more ideas: Serial order and the trade-off between fluency and elaboration in divergent thinking tasks. *Psychology of Aesthetics, Creativity, and the Arts, 18*(4), 480-492. https://doi.org/10.1037/aca0000485
Guilford, J. P. (1967). *The nature of human intelligence*. McGraw-Hill.

Henningsen, D. D., & Henningsen, M. L. M. (2018). Does brainstorming promote cohesiveness? *How the rules of brainstorming mirror symbolic convergence*. *Communication Reports*, 31(2), 103-114. https://doi.org/10.1080/08934215.2017.1394476

Kaufman, J. C., Baer, J., Cropley, D. H., Reiter-Palmon, R., & Sinnett, S. (2013). Furious activity vs. understanding: How much expertise is needed to evaluate creative work? *Psychology of Aesthetics, Creativity, and the Arts*, 7(4), 332-340.
https://doi.org/10.1037/a0034809

Kenworthy, J. B., Paulus, P. B., Minai, A. A., & Doboli, S. (2021). Divergent and convergent creativity. In S. Doboli, J. B. Kenworthy, A. A. Minai, & P. B. Paulus (Éds.), *Creativity and innovation* (p. 69-98). Springer International Publishing. https://doi.org/10.1007/978-3-030-77198-0_4

Kohn, N. W., Paulus, P. B., & Choi, Y. (2011). Building on the ideas of others: An examination of the idea combination process. *Journal of Experimental Social Psychology*, 47(3), 554-561. https://doi.org/10.1016/j.jesp.2011.01.004

Korde, R., & Paulus, P. B. (2017). Alternating individual and group idea generation: Finding the elusive synergy. *Journal of Experimental Social Psychology*, 70, 177-190.
https://doi.org/10.1016/j.jesp.2016.11.002

Le Hénaff, B., Michinov, N., & Le Bohec, O. (2018). Applying the SIDE model to brainwriting: The impact of intergroup comparison and anonymity on creative performance. *Journal of Applied Social Psychology*, 48(7), https://doi.org/10.1111/jasp.12515

Litchfield, R., Fan, J., & Brown, V. (2011). Directing idea generation using brainstorming with specific novelty goals. *Motivation & Emotion*, 35(2), 135-143.
https://doi.org/10.1007/s11031-011-9203-3

Luke, D. (2004). *Multilevel modeling*. SAGE Publications, Inc.
https://doi.org/10.4135/9781412985147

Maas, C. J. M., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling. *Methodology*, 1(3), 86-92. https://doi.org/10.1027/1614-2241.1.3.86

McMahon, K., Ruggeri, A., Kämmer, J. E., & Katsikopoulos, K. V. (2016). Beyond idea generation: The power of groups in developing ideas. *Creativity Research Journal*, 28(3), 247-257. https://doi.org/10.1080/10400419.2016.1195637

McNeish, D. (2017). Small sample methods for multilevel modeling: A colloquial elucidation of REML and the Kenward-Roger correction. *Multivariate Behavioral Research*, 52(5), 661-670. https://doi.org/10.1080/00273171.2017.1344538

Meadow, A., Parnes, S. J., & Reese, H. (1959). Influence of brainstorming instructions and problem sequence on a creative problem-solving test. *Journal of Applied Psychology*, 43(6), 413-416. https://doi.org/10.1037/h0043917

Michinov, N. (2012). Is electronic brainstorming or brainwriting the best way to improve creative performance in groups? An overlooked comparison of two idea-generation techniques. *Journal of Applied Social Psychology*, 42, E222-E243.
https://doi.org/10.1111/j.1559-1816.2012.01024.x

Michinov, N., Jamet, E., Métayer, N., & Le Hénaff, B. (2015). The eyes of creativity: Impact of social comparison and individual creativity on performance and attention to others’ ideas during electronic brainstorming. *Computers in Human Behavior*, 42, 57-67.
https://doi.org/10.1016/j.chb.2014.04.037

Michinov, N., & Jeanson, S. (2023). Creativity in scientific research: Multidisciplinarity fosters depth of ideas among scientists in electronic “brainwriting” groups. *Human Factors*, 65(7), 1542-1553. https://doi.org/10.1177/00187208211048301

Nelson, J., & Guegan, J. (2022). Creative collaboration in groups. In T. Lubart, M. Botella, S. Bourgeois-Bougrine, X. Caroff, J. Guegan, C. Mouchiroud, J. Nelson, & F. Zenasni
(Éds.), *Homo creativus* (p. 87-105). Springer International Publishing.
https://doi.org/10.1007/978-3-030-99674-1_6

Nemeth, C. J., Personnaz, B., Personnaz, M., & Goncalo, J. A. (2004). The liberating role of conflict in group creativity: A study in two countries. *European Journal of Social Psychology*, 34(4), 365-374. https://doi.org/10.1002/ejsp.210

Nezlek, J. B. (2008). An introduction to multilevel modeling for social and personality psychology: Multilevel analyses. *Social and Personality Psychology Compass*, 2(2), 842-860. https://doi.org/10.1111/j.1751-9004.2007.00059.x

Nijstad, B. A., & Stroebe, W. (2006). How the group affects the mind: A cognitive model of idea generation in groups. *Personality and Social Psychology Review*, 10(3), 186-213.
https://doi.org/10.1207/s15327957pspr1003_1

Offner, A. K., Kramer, T. J., & Winter, J. P. (1996). The effects of facilitation, recording, and pauses on group brainstorming. *Small Group Research*, 27(2), 283-298.
https://doi.org/10.1177/1046496496272005

Osborn, A. F. (1953). *Applied imagination: Principles and procedures of creative problem solving* (First edition). Charles Scribner's Sons.

Osborn, A. F. (1963). *Applied imagination: Principles and procedures of creative thinking* (Third edition). Charles Scribner's Sons.

Parnes, S. J., & Meadow, A. (1959). Effects of « brainstorming » instructions on creative problem solving by trained and untrained subjects. *Journal of Educational Psychology*, 50(4), 171-176. https://doi.org/10.1037/h0047223

Paulus, P. B. (2020). Reflections on the impact of Teresa Amabile on the development of the field of group creativity. In R. Reiter-Palmon, C. M. Fisher, & J. S. Mueller (Éds.), *Creativity at Work* (p. 109-119). Springer International Publishing.
https://doi.org/10.1007/978-3-030-61311-2_11

Paulus, P. B., & Baruah, J. (2018). Enhancing creativity in e-planning: Recommendations from a collaborative creativity perspective. In C. N. Silva (Éd.), *New Approaches, Methods, and Tools in Urban E-Planning* (p. 192-222). IGI Global. https://doi.org/10.4018/978-1-5225-5999-3.ch007

Paulus, P. B., Baruah, J., & Kenworthy, J. (2023). Brainstorming: How to get the best ideas out of the “group brain” for organizational creativity. In R. Reiter-Palmon & S. Hunter (Éds.), *Handbook of organizational creativity: Individual and group level influences* (p. 373-389). Elsevier. https://doi.org/10.1016/B978-0-323-91840-4.00019-0

Paulus, P. B., Dzindolet, M., & Kohn, N. W. (2012). Collaborative creativity—Group creativity and team innovation. In M. D. Mumford (Éd.), *Handbook of Organizational Creativity* (p. 327-357). Academic Press.

Paulus, P. B., & Kenworthy, J. B. (2020). Group and intergroup creativity. In L. Argote & J. M. Levine (Éds.), *The Oxford Handbook of Group and Organizational Learning* (p. 388-410). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190263362.013.34

Paulus, P. B., Kohn, N. W., & Arditti, L. E. (2011). Effects of Quantity and Quality Instructions on Brainstorming. *The Journal of Creative Behavior*, 45(1), 38-46.
https://doi.org/10.1002/j.2162-6057.2011.tb01083.x

Paulus, P. B., Kohn, N. W., Arditti, L. E., & Korde, R. M. (2013). Understanding the group size effect in electronic brainstorming. *Small Group Research*, 44(3), 332-352.
https://doi.org/10.1177/1046496413479674

Paulus, P. B., Nakui, T., Putman, V. L., & Brown, V. R. (2006). Effects of task instructions and brief breaks on brainstorming. *Group Dynamics: Theory, Research, and Practice*, 10(3), 206-219. https://doi.org/10.1037/1089-2699.10.3.206
Paulus, P. B., & Yang, H.-C. (2000). Idea generation in groups: A basis for creativity in organizations. *Organizational Behavior and Human Decision Processes, 82*(1), 76-87.
https://doi.org/10.1006/obhd.2000.2888

Peter, L., Michinov, N., Besançon, M., Michinov, E., Juhel, J., Brown, G., Jamet, E., Cherbonnier, A., & ProFAN Consortium. (2021). Revisiting the effects of gender diversity in small groups on divergent thinking: A large-scale study using synchronous electronic brainstorming. *Frontiers in Psychology, 12*:723235, Article 12:723235.
https://doi.org/10.3389/fpsyg.2021.723235

Qi, S., Bai, X., & Li, Y. (2022). Competing within and beyond the boundary: Joint effect of intergroup and intragroup competitions on group creativity. *Thinking Skills and Creativity, 46*, 101194. https://doi.org/10.1016/j.tsc.2022.101194

Reiter-Palmon, R. (2020). The consensual assessment technique: Refinement and further development. In R. Reiter-Palmon, C. M. Fisher, & J. S. Mueller (Éds.), *Creativity at Work: A festschrift in honor of Teresa Amabile* (p. 157-165). Springer International Publishing. https://doi.org/10.1007/978-3-030-61311-2_15

Runco, M. A., & Acar, S. (2012). Divergent thinking as an indicator of creative potential. *Creativity Research Journal, 24*(1), 66-75. https://doi.org/10.1080/10400419.2012.652929

Said-Metwaly, S., Fernández-Castilla, B., Kyndt, E., & Van den Noortgate, W. (2020). Testing conditions and creative performance: Meta-analyses of the impact of time limits and instructions. *Psychology of Aesthetics, Creativity, and the Arts, 14*(1), 15-38.
https://doi.org/10.1037/aca0000244

Snijders, T. A. B. (2005). Power and sample size in multilevel linear models. In B. S. Everitt & D. C. Howell (Éds.), *Encyclopedia of Statistics in Behavioral Science* (1re éd.). Wiley.
https://doi.org/10.1002/0470013192.bsa492

Snijders, T., & Bosker, R. (2012). *Multilevel analysis. An introduction to basic and advanced multilevel modeling*. London Sage Publishers.

*The Jamovi project* (Version 2.3). (2022). [Logiciel]. https://www.jamovi.org

Torrance, E. P. (1969). *Creativity. What Research Says to the Teacher, Series, No. 28*. National Education Association, 1201 Sixteenth Street, N. https://eric.ed.gov/?id=ED078435

van der Lugt, R. (2000). Developing a graphic tool for creative problem solving in design groups. *Design Studies, 21*(5), 505-522. https://doi.org/10.1016/S0142-694X(00)00021-1

Zhou, X., Zhai, H.-K., Delidabieke, B., Zeng, H., Cui, Y.-X., & Cao, X. (2019). Exposure to ideas, evaluation apprehension, and incubation intervals in collaborative idea generation. *Frontiers in Psychology, 10*, 1459. https://doi.org/10.3389/fpsyg.2019.01459
**APPENDIX A.** Illustration of a serial brainstorming task structure. Each color represents one participant. A group member starts to write their ideas on the bottom line of a column, then moves up to the column on the right to develop the idea of another group member, and each group member follows the same procedure.

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