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Networked Flow in Creative Collaboration: A Mixed Method Study

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Title: Networked Flow in Creative Collaboration: A Mixed Method Study
Language: English
Authors: Gaggioli, Andrea, Mazzoni, Elvis (ORCID 0000-0002-7258-5381), Benvenuti, Martina, Galimberti, Carlo, Bova, Antonio (ORCID 0000-0002-6371-0371), Brivio, Eleonora, Cipresso, Pietro, Riva, Giuseppe, Chirico, Alice
Source: Creativity Research Journal. 2020 32(1):41-54.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 14
Publication Date: 2020
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Creativity, Group Dynamics, Networks, Social Networks, Network Analysis, Interpersonal Relationship, Undergraduate Students, Business Communication, Course Descriptions, Foreign Countries, Student Attitudes, Interaction Process Analysis, Cooperative Learning
Geographic Terms: Italy (Milan)
DOI: 10.1080/10400419.2020.1712160
ISSN: 1040-0419
Abstract: The recent model of Networked flow (NF) mapped out factors underlying optimal creative collaboration in blended spaces (physical and digital). NF conceives creativity as an evolving network bridging material and symbolic resources of the creative collaboration process at both inter and the intra-group levels. First, this model posits that optimal group creativity is characterized by highest levels of the experiences of flow and social presence. Secondly, these experiences should stem from a peculiar group communicative structure. Therefore, group creativity should be studied through a mixed-method approach focusing on experiential and structural features of group collaboration, on their evolution, and on group artifacts. Here, we measured the evolution of 10 groups' structural dynamics by means of Social Network Analysis (SNA), and we assessed group experience through group flow experience (Flow State Scale) and social presence (NMSPI). Moreover, four independent raters evaluated the creative products through a domain-based approach, that is the Consensual Assessment Technique. Finally, we deepened the analysis of the highest creative group' micro-interaction through the qualitative approach of Interlocutory Logic. Group flow and social presence were positively related. Both experiential dimensions and creative outcomes were predicted by specific SNA indexes. Qualitative approach of Interlocutory Logic and an analysis of most and least creative groups' sociograms, suggested two structural patterns underlying optimal group creativity instances. Specifically, even a few but well-aimed interactions could facilitate the emergence of higher creativity levels, which could emerge silently, with few but effective interactions, or explicitly, with several (mostly) democratic exchanges among members.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1244282
Database: ERIC
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  Value: <anid>AN0141876848;7lo01jan.20;2020Feb25.01:26;v2.2.500</anid> <title id="AN0141876848-1">Networked Flow in Creative Collaboration: A Mixed Method Study </title> <sbt id="AN0141876848-2">Introduction</sbt> <p>The recent model of Networked flow (NF) mapped out factors underlying optimal creative collaboration in blended spaces (physical and digital). NF conceives creativity as an evolving network bridging material and symbolic resources of the creative collaboration process at both inter and the intra-group levels. First, this model posits that optimal group creativity is characterized by highest levels of the experiences of flow and social presence. Secondly, these experiences should stem from a peculiar group communicative structure. Therefore, group creativity should be studied through a mixed-method approach focusing on experiential and structural features of group collaboration, on their evolution, and on group artifacts. Here, we measured the evolution of 10 groups' structural dynamics by means of Social Network Analysis (SNA), and we assessed group experience through group flow experience (Flow State Scale) and social presence (NMSPI). Moreover, four independent raters evaluated the creative products through a domain-based approach, that is the Consensual Assessment Technique. Finally, we deepened the analysis of the highest creative group' micro-interaction through the qualitative approach of Interlocutory Logic. Group flow and social presence were positively related. Both experiential dimensions and creative outcomes were predicted by specific SNA indexes. Qualitative approach of Interlocutory Logic and an analysis of most and least creative groups' sociograms, suggested two structural patterns underlying optimal group creativity instances. Specifically, even a few but well-aimed interactions could facilitate the emergence of higher creativity levels, which could emerge silently, with few but effective interactions, or explicitly, with several (mostly) democratic exchanges among members.</p> <p>For many years, research on creativity focused on an individual level of analysis, following up the romantic image of the "lone genius" (e.g., Eisler, Donnelly, & Montuori, [<reflink idref="bib18" id="ref1">18</reflink>]; Montuori & Purser, [<reflink idref="bib50" id="ref2">50</reflink>]; Sawyer, [<reflink idref="bib59" id="ref3">59</reflink>]) and identifying key personal factors sparking unique and useful ideas. However, now, scholars are becoming increasingly aware of the importance of socio-cultural factors in shaping creativity (e.g., Glăveanu, [<reflink idref="bib28" id="ref4">28</reflink>]). Creativity view as an individual-level phenomenon emphasizes more intrapersonal processes (Walton, [<reflink idref="bib71" id="ref5">71</reflink>]) compared to interpersonal ones, such as the role of social, cultural and physical contexts. The perspective on creativity as a systemic and context-dependent process is reinforced by the words of Csikszentmihalyi:</p> <p>"We cannot study creativity by isolating individuals and their works from the social and historical milieu in which their actions are carried out. This is because what we call creative is never the result of individual action alone" (Csikszentmihalyi, [<reflink idref="bib13" id="ref6">13</reflink>], pp. 325-326).</p> <p>Creativity theories based on individual factors and on socio-cultural processes can appear as incompatible, yet a recent model proposed a feasible way to integrate both. The <emph>We-paradigm</emph> introduced by Glăveanu, includes individual-based theories as part of a complex creativity system (Glăveanu, [<reflink idref="bib29" id="ref7">29</reflink>]), and relies on a distributed creativity concept (Hutchins, [<reflink idref="bib34" id="ref8">34</reflink>]) as a phenomenon dwelling beyond individuals' minds, and consisting of a <emph>network</emph> of people, cultural and material artifacts, as well as their relationships across time.</p> <p>Along this line of Gaggioli, Chirico, Mazzoni, Milani, and Riva ([<reflink idref="bib21" id="ref9">21</reflink>], [<reflink idref="bib22" id="ref10">22</reflink>], [<reflink idref="bib24" id="ref11">24</reflink>]) have developed a theoretical and methodological framework – <emph>Networked Flow</emph> – which posits the concept of creative networks as means to capture the complexity of collective creativity (Gaggioli, Riva, Milani, & Mazzoni, [<reflink idref="bib24" id="ref12">24</reflink>]). The core of this model rests on three ideas.</p> <p>First, the concept of "group creativity" is extended by introducing the notion of <emph>networked creativity</emph>, relying on the <emph>structural</emph> dynamics among individuals, material and symbolic resources as part of the same creative collaboration process. That is, groups achieving optimal creativity levels also show a <emph>peculiar network structure</emph>, also including communication artifacts used by group members to collaborate – i.e., online collaboration platforms, groupware tools, social media, etc. (Gaggioli et al., [<reflink idref="bib24" id="ref13">24</reflink>]). The NF model captures the "blended" side of communication prevailing in creative collaboration practices when people combine in-presence communication and mediated communication for achieving a common goal (e.g., Bell, Sawaya, & Cain, [<reflink idref="bib5" id="ref14">5</reflink>]; Hinds, Kiesler, & Kiesler, [<reflink idref="bib33" id="ref15">33</reflink>]; So & Brush, [<reflink idref="bib64" id="ref16">64</reflink>]). The NF model states that it is possible to achieve optimal group creative performances even in mediated communication exchanges, thanks to a peculiar <emph>quality of group experience</emph>. That is, when group members experience the highest levels of social presence (i.e., sense of being cognitively, behaviorally, attentively and emotional interconnected with other people in the real and virtual world; Biocca & Harms, [<reflink idref="bib8" id="ref17">8</reflink>]) and flow experience (i.e., an optimal psychological state associated to outstanding group performance; Diana, Villani, Muzio, & Riva, [<reflink idref="bib51" id="ref18">51</reflink>]; Jackson & Eklund, [<reflink idref="bib38" id="ref19">38</reflink>]; Jackson & Marsh, [<reflink idref="bib39" id="ref20">39</reflink>]) they enter a <emph>Mutual zone of proximal development (MZPD</emph>) (Goos, Galbraith, & Renshaw, [<reflink idref="bib30" id="ref21">30</reflink>]; John-Steiner, [<reflink idref="bib40" id="ref22">40</reflink>]) (i.e., members share the same frame of reference, and co-build a collective intention) at the base of optimal group creativity levels. Following up Vygotsky's model, John-Steiner and Mahn ([<reflink idref="bib41" id="ref23">41</reflink>]) stated that the participation to group activities would allow sharing collective knowledge and its final internalization in people' consciousness. All group members scaffold each other, and this process allows the network's ideas development. This collective space has been conceived as a "<emph>Mutual Zone of proximal development</emph>" (Armstrong, [<reflink idref="bib3" id="ref24">3</reflink>]) where people can negotiate shared meaning and generate and pursue collective intentions (Sawyer, [<reflink idref="bib60" id="ref25">60</reflink>]).</p> <p>Finally, to assess the emergence of the MZPD, the analysis of micro-level qualitative communicative interactions among group members is also required. The main goal of the present study was to investigate creative collaboration through the lens of the NF model, using a mixed-method approach. More specifically, we zoomed in the relationship between the abovementioned key components of the model:</p> <p></p> <ulist> <item> <emph>Communicative structure</emph> (to identify network markers of optimal creativity);</item> <p></p> <item> <emph>Quality of experience</emph> (to investigate flow and social presence);</item> <p></p> <item> <emph>Communicative interaction</emph> (to assess the collective zone of proximal development and dialogical style).</item> <p></p> <item> <emph>Creativity performance</emph> (to assess the final product of the creative collaboration).</item> </ulist> <p>At the methodological level, these tenets can be translated into three main operative requirements. A first requirement is to consider both <emph>structural</emph> and <emph>experiential</emph> features of creative collaboration and its outcomes, thus focusing on the quality of group experiences, on the structural features, and on the creative product. The structural dynamics of group collaboration can be detected using Social Network Analysis (SNA) (Scott, [<reflink idref="bib62" id="ref26">62</reflink>]). Then, the experience of group involvement can be measured through group flow experience (Csíkszentmihályi, [<reflink idref="bib16" id="ref27">16</reflink>]; Diana et al., [<reflink idref="bib51" id="ref28">51</reflink>]; Jackson & Marsh, [<reflink idref="bib39" id="ref29">39</reflink>]) and social presence (Biocca & Harms, [<reflink idref="bib8" id="ref30">8</reflink>]). Finally, the creative product should also be analyzed through a domain-based approach, such as the <emph>Consensual Assessment Technique</emph> (Amabile, [<reflink idref="bib2" id="ref31">2</reflink>]). As a second requirement to examine the <emph>evolution</emph> of the creative collaboration, the analysis should focus on micro, meso and macro levels of interaction, that is, on the interaction patterns between group participants over time (micro-level); on the structural changes in internal group dynamics (meso-level); and on the outcomes of micro- and meso-interactions, i.e., transfer of the creative product (the artifact) over a larger socio-cultural context (i.e., a community: the macro level).</p> <p>As a third requirement, in order to identify the possible links between the experiential features of NF (social presence, flow) and the inherent dialogical structure of group dynamics, qualitative and quantitative data need to be collected. A key prediction of this model concerns the role of a specific group structure in facilitating (or not) the emergence of an optimal group experience and creative performance.</p> <p>To meet all these requirements in a consistent way, first, a longitudinal, mixed methodology, combining qualitative, quantitative and topographical analysis of NF process (Galimberti et al., [<reflink idref="bib27" id="ref32">27</reflink>]) has been developed. Here, the term "mixed methodology" refers to the procedure of collecting and analyzing heterogeneous types of data within the context of a single study. Then, it was investigated the emergence of the NF process in 10 groups of university students tasked with the ideation of a videoclip over 11 weeks within the context of a university teaching course on "Enterprise Communication" at Università Cattolica del Sacro Cuore. Students were not told explicitly to produce "creative" ideas. The main assumption was that a peculiar group structure would be able to promote (or hinder) group optimal experience and group creative performance. Groups' network structure was longitudinally analyzed by extracting online communication datasets from social media applications used by the teams to collaborate, and all these data were integrated.</p> <hd id="AN0141876848-3">Method</hd> <p></p> <hd id="AN0141876848-4">Sample</hd> <p>This study took place during the winter semester. It involved 111 undergraduate students (30 males and 81 females, mean age = 24.44; SD = 3.75) enrolled in a course on Enterprise Communication at the Università Cattolica del Sacro Cuore. The Ethical Committee of Università Cattolica del Sacro Cuore assessed and approved the experimental protocol. Each participant provided written informed consent for study participation in accordance with the Helsinki Declaration. Students participated in the study on a voluntary basis and they did not receive rewards or credits. They were aware of each stage of the research process.</p> <hd id="AN0141876848-5">Setting and experimental design</hd> <p>The course on Enterprise Communication at the Catholic University of Milan focuses on topics related to the design, management and the assessment of communication processes within groups and organizations. As part of the final assignment of the course, students worked in groups and created a multimedia project (i.e., including photographic, video and audio materials) addressing the topic of improvisation in organizational settings. This is an open-ended task, related to a specific domain, in which students were trained during the course. During task execution, students were invited to collaborate both face to face or using two widespread and free social media applications (Facebook and Whatsapp). The course combined both frontal lessons and commentaries from experts in the field of improvisation.</p> <p>The study consisted of a longitudinal design, in which social network data were collected from online group interaction over 11 weeks of project collaboration. The research protocol included also: (i) an assessment of group quality of experience in the last week of collaboration; (ii) a collection of conversational data and (iii) the creative product assessment by independent experts in the domain (Figure 1).</p> <p>Graph: Figure 1. Timeline for the longitudinal data collection on collaborative interactions</p> <hd id="AN0141876848-6">Measures</hd> <p>This mixed methodology integrated four measurements: (i) <emph>communicative structure</emph> (to identify network markers of optimal creativity); (ii) <emph>quality of experience</emph> (to investigate flow and social presence); (iii) <emph>communicative interaction</emph> (to assess Mutual zone of proximal development and dialogical style); (iv) <emph>creativity</emph> (to assess the final product of the creative collaboration).</p> <hd id="AN0141876848-7">Communication structure</hd> <p>NF considers both processual and structural features of collaboration and its outcomes (e.g., the creative product). Therefore, the Social Network Analysis technique (SNA) was used to analyze communication exchanges as an index of group structure. This analysis has been already successfully implemented to study creativity and friendship (McKay, Grygiel, & Karwowski, [<reflink idref="bib48" id="ref33">48</reflink>]). SNA is a quantitative method to analyze real (Zohar & Tenne-Gazit, [<reflink idref="bib73" id="ref34">73</reflink>]) and virtual interactions (De Laat, Lally, Lipponen, & Simons, [<reflink idref="bib17" id="ref35">17</reflink>]; Palonen & Hakkarainen, [<reflink idref="bib54" id="ref36">54</reflink>]). Any kind of interaction among group members can be examined (e.g., money, friendship, information) and represented into two formats: numerical and graphical. The resulting group structure can be visualized as graphs (i.e., s<emph>ociograms</emph>), representing the members as nodes of the graphs and the exchanges among them as lines in the graphs. Alternatively, group structural characteristics can be encapsulated into numerical indexes, which can be individual indices (i.e., based on relations and exchanges characterizing each actor of the networks) or group indices (i.e., based on relations and exchanges characterizing the network as a whole). To study the NF, different structural SNA indices have been proposed, such as <emph>Density, Group Centralization</emph> and <emph>Cliques Participation index</emph> (CPI) (for a full description of these indexes, see Gaggioli, Mazzoni, Milani, & Riva, [<reflink idref="bib22" id="ref37">22</reflink>]). Furthermore, it is possible to carry out SNA either focusing on the group structure at a precise moment in time or adopting a longitudinal approach, thus taking multiple "snapshots" of the network structure over time. In this study, a longitudinal structural data analysis concerning group exchanges across 11 weeks was carried out. SNA data were collected every week, but the collaboration process was split in three phases according to the instructions provided to participants during the course. First, groups were created. Central weeks dealt with group collaboration. Last weeks concerned the final stages of collaboration after the delivery of the group product. Here, given the crucial role of central weeks of collaboration for the emergence of a specific group structural pattern (Galimberti et al., [<reflink idref="bib26" id="ref38">26</reflink>]), the analysis focused on the time window ranging from the 4th to the 9th week, middle stages of the collaboration process.</p> <p>Finally, dichotomous relations (the relation is present/not present) were calculated to perform correlation analyses and comparisons, and to analyze the structural features of each group.</p> <hd id="AN0141876848-8">Quality of experience</hd> <p>We investigated group quality of experience as indicated by the degree of group flow and group social presence, in line with the NF model (Gaggioli et al., [<reflink idref="bib24" id="ref39">24</reflink>], [<reflink idref="bib22" id="ref40">22</reflink>]).</p> <p>Flow was assessed using the Italian version of the Flow State Scale (Diana et al., [<reflink idref="bib51" id="ref41">51</reflink>]) initially developed by Jackson and colleagues (Jackson & Eklund, [<reflink idref="bib37" id="ref42">37</reflink>]; Jackson & Marsh, [<reflink idref="bib39" id="ref43">39</reflink>]), a widely used 36 items on a 5-point likert scale self-reported questionnaire. Each item taps one of the nine dimensions of flow (Csíkszentmihályi, [<reflink idref="bib16" id="ref44">16</reflink>]; Jackson & Csikszentmihalyi, [<reflink idref="bib36" id="ref45">36</reflink>]). This scale showed an acceptable internal consistency (global mean Cronbach's alpha = 0.83) (Jackson & Marsh, [<reflink idref="bib39" id="ref46">39</reflink>]). A total flow score for each dimension (ranging from 4 to 20) was obtained by summing scores of the single subscales. The range of scores for individual flow is from 36 (lowest flow) to 180 (highest flow). Global group flow score is computed by summing the average flow score for each individual team's member.</p> <p>Social Presence was assessed using the Networked Minds Social Presence Inventory (NMSPI), a 34-item scale developed by Biocca and Harms (Biocca & Harms, [<reflink idref="bib7" id="ref47">7</reflink>], [<reflink idref="bib8" id="ref48">8</reflink>]; Harms & Biocca, [<reflink idref="bib31" id="ref49">31</reflink>]) and adapted into Italian (Gaggioli et al., [<reflink idref="bib21" id="ref50">21</reflink>]), also for non-mediated settings. Here, we focused on the first and second-order constructs of Social Presence.</p> <p>The internal consistency of the scale was high (mean Cronbach's alpha = 0.83). Here, a global level of Social presence was computed by summing the Co-presence and second-order Social Presence dimensions scores for each team.</p> <hd id="AN0141876848-9">Communicative interactions</hd> <p>Communicative interactions were investigated in relation to the concept of <emph>Mutual zone of proximal development</emph> and the dialogical style. The focus was on dialogical processes in conversations (i.e., dialogical patterns between participants during their group's activity; Galimberti et al., [<reflink idref="bib26" id="ref51">26</reflink>]), analyzed by means of Interlocutory Logic (Trognon & Batt, [<reflink idref="bib68" id="ref52">68</reflink>]). The qualitative analysis of macro-sequences of idea-generating processes is aimed at identifying potential dialogical markers of NF, such as:</p> <p></p> <ulist> <item> The ratio between conflicts produced and conflicts resolved;</item> <p></p> <item> The number of group members that take part into the conversation;</item> <p></p> <item> Indicators of role fluidity: organizational/institutional roles, enunciative roles;</item> <p></p> <item> Team management processes (problem solving, decision-making, etc.) supported by internal or external (material and/or human) resources;</item> <p></p> <item> Type of problems and the created ethnomethods used to solve them;</item> <p></p> <item> Number of subroutines that the group can/cannot solve;</item> <p></p> <item> Prevalence of dialogical continuity over monological coherence;</item> <p></p> <item> The ratio between successful and satisfied speech acts and the total number of speech acts.</item> </ulist> <hd id="AN0141876848-10">Creative performance</hd> <p>Four expert judges in the domain of Enterprise Communication independently evaluated each group creativity using the Consensual Assessment Technique (CAT) developed by Amabile (Amabile, [<reflink idref="bib2" id="ref53">2</reflink>]). This procedure consists in providing participants with instructions for creating (in this case) group artifacts and asking experts to independently evaluate the creativity levels of those products (Amabile, [<reflink idref="bib2" id="ref54">2</reflink>]). Following this procedure, we asked four raters to judge the creativity levels of group artifacts on a 7-point scale, using their expertise on creativity in this domain.</p> <hd id="AN0141876848-11">Procedure</hd> <p>At the beginning of the course, 10 self-selected students teams groups (size 8–11 members) were tasked with the creation of a multimedia product (time constraint: 11 weeks) on the theme of "improvisation" in organizational settings. The instructions were as follows:</p> <p>Please, get inspiration from experts, who talked during our lessons, or from other elements presented during our lessons and related to the topic of 'improvisation', to create a multimedia product (min 3 minutes – max 5 minutes length) in which the topic of 'improvisation' is represented.</p> <p>They were allowed to collaborate through a) face-to-face meeting sessions in the classroom – video-recorded by students themselves and used to carry out qualitative analyses of dialogical interactions (2-h session once a week) – and b) virtually – using two social media platforms (Facebook and Whatsapp as they chose – both or one), analyzed by means of Social Network Analysis. Teams created either a Whatsapp group or a Facebook group to exchange information supporting their collaborative process. To collect data related to online interactions, a critical issue was how to safeguard students' privacy, following the recommendation of the Ethical Committee. To address this issue, we asked and taught students themselves to collect data related to their online conversations and create the adjacency matrixes, i.e., a square matrix used to represent relational data as a starting point for SNA.</p> <hd id="AN0141876848-12">Data analyses</hd> <p></p> <hd id="AN0141876848-13">Results</hd> <p>A global creativity score for each group was computed, given the high level of consistency among raters (Cronbach Alpha =.729). Considering the aim of this study and the longitudinal nature of SNA data, all analyses were carried out at group level (10 groups). First, the focus was on the relationship between SNA indexes, quality of experience and group creativity scores. Then, the SNA analysis was deepened by considering the structure of communication exchanges in three groups, which showed highest (Group A, Group B) and lowest (Group C) creativity scores. The choice of these groups was determined by the interactive dynamics showed by their members that were interesting and suitable for the following qualitative analysis.</p> <p>Finally, the analysis concerned verbal exchanges at quantitative – by means of SNA- and qualitative level – through Interlocutory Logic analyses of conversation. Two normality tests (i.e., Kolmogorov-Smirnov and Shapiro-Wilk) showed that variables were normally distributed. Then, Pearson correlation coefficients indicated positive correlations between global and sub-dimensions of flow and social presence, as reported in Table 2. Results showed that Global flow and Global Social Presence were positively and highly correlated. Moreover, rwg(i) indexes for Flow and Social presence factors were computed in order to justify the aggregation of scores, as reported in Table 3.</p> <p>Table 1. Metrics for social network analysis.</p> <p> <ephtml> <table><thead><tr><td>Factors</td><td>Measures</td></tr></thead><tbody><tr><td>Density</td><td>It represents the intensity of communication/collaboration within the group: the relationships expressed with respect to the maximum of possible relationships (percentage that describes how much in a group everyone has interacted or looked at all the others group members).</td></tr><tr><td>InDegree Centralization</td><td>It represents the inequality in the intensity of incoming interaction, the increase of this value there are individuals who have received a greater intensity of communications/collaborations (i.e., the more a person receives relations or exchanges the more he/she could be with high status-Leader)</td></tr><tr><td>OutDegree Centralization</td><td>it represents the inequality in the intensity of outgoing interactions, the increase of this index there are students who have sent/started a greater intensity of communications/collaborations (i.e., the more a person activates relations or exchanges the more he/she is influent)</td></tr><tr><td>CPI (cliques participation index)</td><td>It considers not only the number of cliques (i.e., subgroups) but relates it to the total number of members for each group. Identifies the average involvement of each subject in the existing subgroups.</td></tr></tbody></table> </ephtml> </p> <p>Table 2. Pearson's correlations between global and sub-dimensions of flow and social presence.</p> <p> <ephtml> <table><thead><tr><td>Perception of the Self</td><td>Perception of the Other</td></tr><tr><td /><td>Co-presence</td><td>Attentional Engagement</td><td>Emotional Contagion</td><td>Comprehension</td><td>Behavioral interdependence</td><td>Co-presence</td><td>Attentional Engagement</td><td>Emotional Contagion</td><td>Comprehension</td><td>Behavioral interdependence</td><td>Global Social Presence</td></tr></thead><tbody><tr><td>Challenges Skills Balance</td><td>.58</td><td>.65*</td><td>.41</td><td>.74*</td><td>.81**</td><td>.59</td><td>.53</td><td>.49</td><td>.68*</td><td>.59</td><td>.67*</td></tr><tr><td>Action Awareness Merge</td><td>.91**</td><td>.66*</td><td>.49</td><td>.88**</td><td>.87**</td><td>.86**</td><td>.80**</td><td>.56</td><td>.82**</td><td>.62</td><td>.84**</td></tr><tr><td>Clear Goals</td><td>.73*</td><td>.44</td><td>.46</td><td>.77**</td><td>.83**</td><td>.68*</td><td>.59*</td><td>.56</td><td>.71*</td><td>.57</td><td>.73*</td></tr><tr><td>Un-ambiguous Feedback</td><td>.55</td><td>.32</td><td>.36</td><td>.67*</td><td>.81**</td><td>.53*</td><td>.58*</td><td>.53</td><td>.64*</td><td>.60</td><td>.64*</td></tr><tr><td>Concentration</td><td>.84**</td><td>.59</td><td>.65*</td><td>.86**</td><td>.93**</td><td>.75*</td><td>.70*</td><td>.75*</td><td>.83**</td><td>.71*</td><td>.87**</td></tr><tr><td>Paradox of control</td><td>.69*</td><td>.41</td><td>.28</td><td>.73*</td><td>.78**</td><td>.65*</td><td>.70*</td><td>.46</td><td>.73*</td><td>.55</td><td>.67*</td></tr><tr><td>Loss of Self</td><td>.86**</td><td>.67*</td><td>.38</td><td>.78**</td><td>.75*</td><td>.82**</td><td>.83**</td><td>.51</td><td>.81**</td><td>.53</td><td>.77**</td></tr><tr><td>Time transformation</td><td>.86**</td><td>.75*</td><td>.66*</td><td>.79**</td><td>.78**</td><td>.79**</td><td>.60</td><td>.61</td><td>.62</td><td>.48</td><td>.79**</td></tr><tr><td>Autotelic experience</td><td>.57</td><td>.38</td><td>.68*</td><td>.69*</td><td>.75*</td><td>.53</td><td>.32</td><td>.63</td><td>.54</td><td>.55</td><td>.67*</td></tr><tr><td>Group Flow</td><td>.81**</td><td>.56</td><td>.54</td><td>.85**</td><td>.91**</td><td>.76*</td><td>.69*</td><td>.63</td><td>.79**</td><td>.65*</td><td>.82**</td></tr></tbody></table> </ephtml> </p> <p>1 N = 10 teams.*p <.05, two-tailed; **p <.01</p> <p>Table 3. Rwg(i) indexes for all flow and social presence scores.</p> <p> <ephtml> <table><thead><tr><td>Group</td><td>Chall Skills Balance</td><td>Action Awareness Merge</td><td>Clear Goals</td><td>Un-ambiguous Feedback</td><td>Concentration</td><td>Paradox of control</td><td>Loss of Self</td><td>Time transformation</td><td>Autotelic experience</td><td>Group Flow</td><td>Co-presence</td><td>Global Social Presence</td></tr></thead><tbody><tr><td>1</td><td>0.95</td><td>0.88</td><td>0.90</td><td>0.99</td><td>1.00</td><td>0.84</td><td>0.99</td><td>0.93</td><td>0.86</td><td>0.94</td><td>0.98</td><td>0.97</td></tr><tr><td>2</td><td>1.00</td><td>0.90</td><td>0.83</td><td>0.96</td><td>0.86</td><td>0.85</td><td>0.89</td><td>0.87</td><td>0.84</td><td>0.96</td><td>0.96</td><td>0.97</td></tr><tr><td>3</td><td>0.93</td><td>0.83</td><td>0.89</td><td>0.90</td><td>0.87</td><td>0.87</td><td>0.88</td><td>0.83</td><td>0.89</td><td>0.94</td><td>0.95</td><td>0.95</td></tr><tr><td>4</td><td>0.88</td><td>0.88</td><td>0.75</td><td>0.82</td><td>0.89</td><td>0.87</td><td>0.93</td><td>0.76</td><td>0.85</td><td>0.94</td><td>0.96</td><td>0.97</td></tr><tr><td>5</td><td>0.89</td><td>0.90</td><td>0.93</td><td>0.89</td><td>0.93</td><td>0.92</td><td>0.87</td><td>0.94</td><td>0.93</td><td>0.96</td><td>0.99</td><td>0.99</td></tr><tr><td>6</td><td>0.75</td><td>0.91</td><td>0.70</td><td>0.79</td><td>0.78</td><td>0.77</td><td>0.90</td><td>0.83</td><td>0.71</td><td>0.89</td><td>0.98</td><td>0.96</td></tr><tr><td>7</td><td>0.84</td><td>0.90</td><td>0.91</td><td>0.92</td><td>0.93</td><td>0.94</td><td>0.96</td><td>0.90</td><td>0.80</td><td>0.97</td><td>0.97</td><td>0.96</td></tr><tr><td>8</td><td>0.94</td><td>0.95</td><td>0.90</td><td>0.92</td><td>0.90</td><td>0.94</td><td>0.88</td><td>0.93</td><td>0.81</td><td>0.97</td><td>0.97</td><td>0.98</td></tr><tr><td>9</td><td>0.86</td><td>0.92</td><td>0.88</td><td>0.89</td><td>0.96</td><td>0.95</td><td>0.93</td><td>0.94</td><td>0.89</td><td>0.96</td><td>0.99</td><td>0.99</td></tr><tr><td>10</td><td>0.81</td><td>0.87</td><td>0.83</td><td>0.88</td><td>0.88</td><td>0.96</td><td>0.81</td><td>0.76</td><td>0.76</td><td>0.94</td><td>0.97</td><td>0.95</td></tr></tbody></table> </ephtml> </p> <p>2 We computed <emph>rw<subs>g(j)</subs></emph> ('≥.70) to calculate interrater agreement. We found all the groups had a r<subs>WG</subs> value above.7 or higher for all of the scales.</p> <p>To test the relationship between structural dynamics (SNA), creativity, flow and social presence, we carried out a Generalized Linear Model which can accept a violation of sphericity and collinearity (Agresti & Kateri, [<reflink idref="bib1" id="ref55">1</reflink>]; Mackinnon & Puterman, [<reflink idref="bib44" id="ref56">44</reflink>]). Therefore, three models were tested including all SNA indexes (i.e., Density, Indegree Centralization, OutDegree Centralization, CVIndegree Centralization, CVOutdegree Centralization, CPI) for predicting creativity, group flow and social presence levels. By calculating these SNA indexes, based on exiting literature (such as Freeman, [<reflink idref="bib19" id="ref57">19</reflink>]; Mazzoni, [<reflink idref="bib45" id="ref58">45</reflink>]), dichotomous data become continous, as they represent interconnected dynamics of the entire network.</p> <p>In Table 4, all the tested models are reported.</p> <p>Table 4. Generalized linear model: SNA indexes as predictors, group flow, global social presence and group creativity as measures.</p> <p> <ephtml> <table><thead><tr><td /><td>Dependent Measures</td></tr><tr><td>Predictors</td><td>Statistics</td><td>Creativity</td><td>Group Flow</td><td>Global Social Presence</td></tr></thead><tbody><tr><td>Density</td><td>B</td><td>−4.455</td><td>−62.518</td><td>−159.562</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>3.236</td><td>19.812</td><td>7.894</td></tr><tr><td>Sign.</td><td>p =.072</td><td>p <.005</td><td>p =.005</td></tr><tr><td>InDegree Centralization</td><td>B</td><td>62.151</td><td>−79.872</td><td>−721.133</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>4.177</td><td>.164</td><td>.818</td></tr><tr><td>Sign.</td><td>p =.041</td><td>p =.685</td><td>p =.366</td></tr><tr><td>CVInDegree Centralization</td><td>B</td><td>.236</td><td>−.511</td><td>−5.510</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>.445</td><td>.369</td><td>2.629</td></tr><tr><td>Sign.</td><td>p =.118</td><td>p = 543</td><td>p =.105</td></tr><tr><td>OutDegree Centralization</td><td>B</td><td>−62.494</td><td>90.761</td><td>785.197</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>4.178</td><td>.212</td><td>.972</td></tr><tr><td>Sign.</td><td>p =.04</td><td>p =.645</td><td>p =.324</td></tr><tr><td>CVOutDegree Centralization</td><td>B</td><td>.193</td><td>.237</td><td>4.923</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>1.720</td><td>.085</td><td>2.254</td></tr><tr><td>Sign.</td><td>p =.190</td><td>p =.770</td><td>p =.133</td></tr><tr><td>CPI</td><td>B</td><td>.476</td><td>7.020</td><td>11.487</td></tr><tr><td><bold><italic>Wald χ</italic><sup>2</sup></bold></td><td>.959</td><td>6.668</td><td>1.092</td></tr><tr><td>Sign.</td><td>p =.327</td><td>p =.010</td><td>p =.296</td></tr></tbody></table> </ephtml> </p> <p>Table 5. Group creativity, group flow and global social presence of the selected groups.</p> <p> <ephtml> <table><thead><tr><td>Groups</td><td>Creativity</td><td>Flow</td><td>Social Presence</td></tr></thead><tbody><tr><td>A</td><td>28</td><td>326</td><td>1038</td></tr><tr><td>B</td><td>23</td><td>251</td><td>851</td></tr><tr><td>C</td><td>11</td><td>225</td><td>824</td></tr></tbody></table> </ephtml> </p> <p>3 Three out of 10 groups are presented. Scores were computed as sums.</p> <p>Group creativity was significantly and positively predicted by OutDegree Centralization and InDegree Centralization, although in an opposite direction. Flow was negatively predicted by Density, but positively by CPI. Finally, Density predicted Group Global Social Presence negatively.</p> <p>The analysis was deepened by focusing on three groups, which were selected because they showed the highest (Group A, Group B) and lowest creativity scores (Group C). Given the crucial role of central weeks of collaboration for the emergence of a specific group structural pattern (Galimberti et al., [<reflink idref="bib26" id="ref59">26</reflink>]), only the time window ranging from the 4th to the 9th week was considered.</p> <hd id="AN0141876848-14">Analysis of group structural dynamics</hd> <p>Because of the richness of SNA data available, the analysis focused on a subset of groups with well-defined profiles in terms of creativity outcomes, flow and social presence. The selection criteria are detailed as follows. All groups were ranked based on creativity. Then, groups with the highest creativity scores (i.e., Group A and Group B), and the group who reported the lowest creativity score (i.e., Group C) were identified. Since the aim was to map out relevant structural dynamics involved in creative collaboration, communication exchanges among members were used to build a model of group interactions. However, Group A (highly creative) reported very few online interactions across the 11 weeks of collaboration. Therefore, in line with NF model requirements, we chose to balance out in two ways. First, we included in the analysis another high-performing group whose exchanges were richer (Group B). Second, we deepened the analysis of the most Group A by focusing on the micro-level of interaction among members, using Interlocutory Logic technique (Trognon & Batt, [<reflink idref="bib68" id="ref60">68</reflink>]). The analysis of dialogs allowed us to examine more closely the group dynamics and to provide a richest context for the interpretation of the relatively small number of online communication exchanges reported by this group.</p> <p>Table 5 Group A featured the highest global creativity scores (i.e., 28) and Group Flow (<reflink idref="bib326" id="ref61">326</reflink>), as well as a high Global Social presence (1038). In terms of SNA, Group A showed low Density and low InDegree Centralization (Figure 2, Table 1). The sequence of images in the line above showed the amount of interactions between the group across 4 weeks and during the ending phase. This group accrued all interactions between the 8th and the 9th week of collaboration. Images above showed sociograms of interactions during the ending phase. The left-below image showed the trend of Density, InDegreeCentralization, OutDegreeCentralization (we considered only dicotomous values indicating only the presence/absence of an interaction between members) and CPI during the same phase. The right-below image represented the same trend for InDegree and OutDegree Centralization.</p> <p>PHOTO (COLOR): Figure 2. Density, InDegree Centralization, Outdegree Centralization of Group A throughout weeks 6-9</p> <p>Table 5 Group B showed a high creativity score (<reflink idref="bib23" id="ref62">23</reflink>), as well as high levels of Group flow (<reflink idref="bib251" id="ref63">251</reflink>) and Global Social Presence (<reflink idref="bib851" id="ref64">851</reflink>). SNA data indicated that Group B featured both high density and high InDegreeCentralization (Figure 3).</p> <p>PHOTO (COLOR): Figure 3. Density, InDegree Centralization, Outdegree Centralization of Group B throughout weeks 6-9</p> <p>Table 5 Group C, whose global creativity score (i.e., 11), Group flow (<reflink idref="bib225" id="ref65">225</reflink>) and Global Social presence (<reflink idref="bib824" id="ref66">824</reflink>) were the lowest, showed lower Density but higher InDegree Centralization indexes compared to the previous group (Figure 4).</p> <p>PHOTO (COLOR): Figure 4. Density, InDegree Centralization, Outdegree Centralization and CPI of Group C throughout weeks 6-9</p> <p>The analysis of interactions of Group A was deepened following the guidelines of Interlocutory logic method. This group was chosen since it resulted as the most informative group, according to NF model, because it scored highest creativity. Two recordings of conversations from the first and central weeks Group A's meeting were considered to find out prototypical macro-sequences of problem-solving or creative (idea-generating) processes. Three sequences from the first meeting and one from the half-way meeting were selected. These sequences were transcribed adopting the most commonly used conventions for transcribing vocal conduct in talk-in-interaction (Sacks, [<reflink idref="bib57" id="ref67">57</reflink>]; see supplementary materials) and revised by two researchers until a high level of consent (agreement rate = 90%) was reached. Crucially, the analysis of the first off-line meeting reported group collaborative dynamics occurring in the "silent" phase of online group collaboration, that is, when no SNA data was collected. The qualitative analyses of the two dialogical sequences presented in this chapter permit to exemplify the results obtained through the qualitative analysis of the whole corpus of data. The analysis of these sequences identified specific patterns of communicative interactions that may help explaining high creativity scores obtained by Group A, as well as a high level of flow and social presence that were reported by its members.</p> <p>Results of the analysis highlighted that Group A used the same pattern of "accumulation" of ideas across meetings and that two types of actors mainly managed this process. The first type of actor attended the first meeting and was the functional leader of the team. The second type of actor was absent but was "presentified" through the other participants' discourse. His "fictional" presence was used by the group to regulate decision-making processes. This second type of regulator could be either an absent team member or a person external to the group (in the example below, the regulating figure is the professor of their class). Two excerpts from the sequences are used here to support these analyses.</p> <p> <emph>Excerpt 1</emph> </p> <p></p> <p> <ephtml> <table><tbody><tr><td>1</td><td>G</td><td>= and we see ehm: different artists how they react, thus the: [= poet what he writes, the painter what</td></tr><tr><td>2</td><td /><td>He paints and: [the dancer what he dances:[= and:: that all I think</td></tr><tr><td>3</td><td>H</td><td>[Otherwise you cannot hear</td></tr><tr><td>4</td><td>E</td><td>= th[e painter!</td></tr><tr><td>5</td><td>H</td><td>[Otherwise you cannot hear</td></tr><tr><td>6</td><td>E</td><td>[= Eh!</td></tr><tr><td>7</td><td /><td>Correct</td></tr><tr><td>8</td><td>H</td><td>[This is so nice!</td></tr><tr><td>9</td><td>G</td><td>[= And:: then-</td></tr><tr><td>10</td><td>A</td><td>[Then (0.3) or we decide on a common theme, not music, a theme</td></tr><tr><td>11</td><td>G</td><td>A theme:</td></tr><tr><td>12</td><td>H</td><td>[But, that is:</td></tr><tr><td>13</td><td>-</td><td>[=</td></tr><tr><td>14</td><td>B</td><td>[Yeah one says to improv on something, instead a theme is focused</td></tr><tr><td>15</td><td>G</td><td>Then, what she is says is ok, but if you do that it's not real group work. I</td></tr><tr><td>16</td><td /><td>Think that it depends, that i[s = – depends on how you sell it (0.4), meaning-</td></tr><tr><td>17</td><td>B</td><td>= [that is- (0.3) correct that in my opinion if-</td></tr><tr><td>18</td><td>C</td><td>Then in the end there is something made by the group, because everyone is influenced by the same thing</td></tr><tr><td>19</td><td /><td>So if we rely on the fact that in the end the result is a – group thing (h) it is on point</td></tr><tr><td>20</td><td>G</td><td>In my opinion yes</td></tr><tr><td>21</td><td>A</td><td>Maybe we have to choose ehm: a theme – an idea</td></tr></tbody></table> </ephtml> </p> <p>In this first meeting, group members accumulated and discarded ideas randomly and rapidly, with no specific time management and no clear goal. Members showed a low monological coherence across different topics, but looked for dialogical continuity, necessary to solve the assigned task. This strategy was crucial to maintain group dialogue and to start shaping the quality of <emph>group experience</emph>.</p> <p>Students avoided starting an argumentative discussion to convince the other party to accept or retract his/her standpoint (van Eemeren & Grootendorst, [<reflink idref="bib70" id="ref68">70</reflink>]), as illustrated in line 15, when the student G advances an argument in support of his standpoint: <emph>but if you do that it's not real group work</emph>. Even though the argument advanced by the student was introduced by the linguistic marker "but", an index of disagreement between the participant to a discussion (Schiffrin, [<reflink idref="bib61" id="ref69">61</reflink>]), it did not trigger any conflict among the students. Rather, all the students promptly showed their agreement with the student's G argumentation. In this case, the absence of impulsive responses and rude behaviors during the argumentative discussions among group members may have played a crucial role in favoring group-creativity (Chiu, [<reflink idref="bib11" id="ref70">11</reflink>]; Chiu & Khoo, [<reflink idref="bib12" id="ref71">12</reflink>]; Hawlina, Gillespie, & Zittoun, [<reflink idref="bib32" id="ref72">32</reflink>]). Recently, several studies have demonstrated the link between the presence of argumentation among group members and the group-creativity levels. For instance, previous studies found that when group members valued one another's diverse contributions they created more ideas and justifications (Larson, [<reflink idref="bib43" id="ref73">43</reflink>]; Paulus & Brown, [<reflink idref="bib55" id="ref74">55</reflink>]; Stasson & Bradshaw, [<reflink idref="bib66" id="ref75">66</reflink>]; Swann, Kwan, Polzer, & Milton, [<reflink idref="bib67" id="ref76">67</reflink>]). In the same line, De Dreu and West ([<reflink idref="bib15" id="ref77">15</reflink>]) found that a disagreement among the members of the group might help them consider more aspects of a problem from more perspectives and, accordingly, increasing the level of creativity of the group (in this regard, see also Nemeth & Chiles, [<reflink idref="bib52" id="ref78">52</reflink>]; Nemeth & Rogers, [<reflink idref="bib53" id="ref79">53</reflink>]). In a similar vein, Gajda and her colleagues (Gajda, Beghetto, & Karwowski, [<reflink idref="bib25" id="ref80">25</reflink>]), using a micro-level interactional analysis to visually illustrate patterns of interactions between teachers and students, found more extended and exploratory interactions in classrooms where there was a positive association between students' measured creativity and academic achievement.</p> <p> <emph>Excerpt 2</emph> </p> <p></p> <p> <ephtml> <table><tbody><tr><td>1</td><td>E</td><td>But I think that he ((the professor)) wants us to use music because in my opinion because he – (.) but we – he is</td></tr><tr><td>2</td><td /><td>Introducing music to us, it's jazz and he linked jazz to organizations, to enterprises, to business</td></tr><tr><td>3</td><td /><td>etcetera, etcetera – thus perhaps he – thus he brings in music bands for us, otherwise he could have brought in</td></tr><tr><td>4</td><td /><td>even a painter – [and the painter would have done improv</td></tr><tr><td>5</td><td>G</td><td>[But maybe (0.4) ehm::: a way to demonstrate improv could be</td></tr><tr><td>6</td><td /><td>I put – a musician and – a painter in the same room and see how they relate to each other = – and I just</td></tr><tr><td>7</td><td /><td>Ask them "paint according to what you hear or play according to what you see:"</td></tr></tbody></table> </ephtml> </p> <p>In the second excerpt, group members accumulated ideas, proposals, analyzed each possibility, and solved problems. Then, they moved to another point of the discussion. At that moment, the group had a specific goal in mind that needed to be reached. Hence, dialogical continuity was not more a need to be fulfilled. On the contrary, the emergence of small oppositions in the dialogue below marked argumentative interactions among the members of the group. Accumulation of topics and ideas advanced as arguments in support of opinions was strictly linked to a sequence of problems and to the attempt to find their solutions. In this case, confrontation – the externalization of disagreement on a certain standpoint – emerged as a necessary condition for an argumentative discussion to occur. Therefore, recalling how group members dialectically solved differences of opinion was useful to highlight dialogical choices, forms and dynamics adopted by students. For notations used to analyze each except, please, see Appendix A "Transcriptions Conventions."</p> <p>In conclusion, the results of the qualitative analysis of two excerpts evidenced how Group A members exercised and managed both the <emph>dialogic continuity</emph> and the <emph>monological coherence</emph>, which is at the basis of the ability to manage both the group dynamics and the organizational dimension of the communication process within the group.</p> <hd id="AN0141876848-15">Discussion</hd> <p>A key finding concerns the relation between SNA indexes, creativity outcomes and flow. All SNA indexes resulted as significant predictors of group creativity outcomes, flow and social presence. These results are in line with a key hypothesis of the NF model on the role of group social network structure as a proxy of creative collaboration. However, as suggested by NF, SNA remains a quantitative method providing rich data that needs to be complemented by an integrative approach (Gaggioli, Riva, Milani, & Mazzoni, [<reflink idref="bib23" id="ref81">23</reflink>]; Wasserman, [<reflink idref="bib72" id="ref82">72</reflink>]) focusing on group performance, optimal experience and dialogical dynamics.</p> <p>On group performance, group centralization indexes (i.e., InDegree Centralization and OutDegree centralization) predicted teams' creative performance, even though in an opposite way. Specifically, the InDegree Centralization index was positively related to creativity, while the OutDegree Centralization index showed a negative link with group creative performance. OutDegree Centralization and InDegree Centralization indexes are measures of different kinds of group's leadership dynamics. High levels of OutDegree Centralization indicate a group structure with all interactions stemming from a specific member(s) – leader(s) – as a group "manager." InDegree Centralization indicates the extent to which group exchanges are directed toward a specific member(s), intended as a reference point or as an inspirational source. Consistently, several studies evidenced that network structural dynamics were crucial to achieve a shared goal (Brass, [<reflink idref="bib9" id="ref83">9</reflink>]; Burton & Carroll, [<reflink idref="bib10" id="ref84">10</reflink>]; Friedkin, [<reflink idref="bib20" id="ref85">20</reflink>]; Ibarra & Andrews, [<reflink idref="bib35" id="ref86">35</reflink>]; Molm, [<reflink idref="bib49" id="ref87">49</reflink>]; Sparrowe, Liden, Wayne, & Kraimer, [<reflink idref="bib65" id="ref88">65</reflink>]). Studies on small collaborative web groups showed that High Density and Low Centralization were associated with better performances (Aviv, Erlich, Ravid, & Geva, [<reflink idref="bib4" id="ref89">4</reflink>]; Mazzoni & Gaffuri, [<reflink idref="bib46" id="ref90">46</reflink>]; Mazzoni, Gaffuri, & Selleri, [<reflink idref="bib47" id="ref91">47</reflink>]). Also, Cliques Participation Index (CPI), defined as the average individual involvement in the substructure (clique), can be conceived as an indicator of small groups' originality and creativity levels, when members are involved in a shared-goal task (Mazzoni, [<reflink idref="bib45" id="ref92">45</reflink>]). Here, we found only a significant relationship between group creativity outcomes and centralization indexes, as a potential consequence of the small number of team members (Mazzoni, [<reflink idref="bib45" id="ref93">45</reflink>]). More, the density index was also not a significant predictor of creativity score. This may suggest finer processes underlying group creativity, thus requiring a more detailed approach of analysis. The NF model prescribes to deepen the analysis of the group creativity process by focusing on a micro-level of analysis, i.e., analyzing single group exchanges.</p> <p>As such, we chose to zoom in to three paradigmatic groups (which we called "Group A," "Group B," "Group C") identified as the highly creative (vs. lowly creative) teams. First, these groups were differentiated on the base of the interactive dynamics represented by the sociograms. Then, structural data from Group A were integrated with the dialogical ones achieved though Interlocutory Logic analysis. Group A – the most creative group – accrued interactions during last weeks, but several members interacted and participated. It showed low density and a low centralization. Despite the lack of online interactions during the first 2 weeks, members might have been able to bring forth necessary exchanges to generate a creative artifact. Qualitative dialogical analysis showed that Group A proceeded randomly in the initial phases, but it ended with a high level of monological coherence. Once a collaborative frame has been established in the early stages of group work, members might be able to focus on a common goal: the assigned task. Probably, they just need to interact to share ideas relevant to pursue the goal, and able to promote combination and "confrontation" of different points of view. Maybe, their overall approach led to low centrality and low density, as detected in the final stages of group collaboration. Similarly, Group B (the second most creative group) displayed low density, low CPI and low centralization. It also showed, in the final stages, a strong leader to whom information were oriented.</p> <p>On the opposite side, Group C (the least creative group) displayed a higher centralization of interactions oriented to specific members across the whole period (higher density and CPI). This pattern might have invalidated group creative performance.</p> <p>According to findings on small groups and creativity (Aviv et al., [<reflink idref="bib4" id="ref94">4</reflink>]; Mazzoni, [<reflink idref="bib45" id="ref95">45</reflink>]), a <emph>democratic</emph> sharing of information and a good but <emph>thriftly</emph> (i.e., the management of interaction was made only when necessary and not as a default control mechanism) managing of interactions could enhance creative performance. Therefore, despite Group C activated more interactions than group A (i.e., it showed higher Density), its dynamics resulted as not well structured, and this might have lowered the final performance. To date, a vertical approach of analysis has been adopted, from creative performance at the networked level (all groups) to the intra-group level (single groups). This investigation might seem exhaustive, but the NF model suggests also a horizontal plane of analysis. NF posited the need to investigate also the quality of group members' experience.</p> <p>As concerns group optimal experience, results evidenced that Density and CPI predicted flow experience at the team level. Density, i.e., a measure of participation, was negatively related to Group flow, while CPI (i.e., an indicator of members' involvement in different discussions) showed a positive relation with Group flow. Therefore, less but diversified exchanges among group members could lead to an increased experience of Group flow. Density was the only significant but negative SNA predictor of Social Presence. Groups with less exchanges reported a higher sense of co-presence a sense of mutual connectedness. At first sight, this result may seem rather unexpected, as one would anticipate that social presence is higher when members interact <emph>more</emph>. Despite previous research has shown that dense groups are more socially cohesive, share different points of view, and show higher levels of satisfaction and stability (Saqr, Fors, Tedre, & Nouri, [<reflink idref="bib58" id="ref96">58</reflink>]), these findings were in line with our analysis of dialogs. Only a few interactions were activated by highly creative groups, maybe because they did not need more relational effort to pursue the shared goal, since they have already achieved the right harmony among members. Once harmony was achieved, members, maybe, did not need to interact more; they were already "tuned" with each other.</p> <hd id="AN0141876848-16">Conclusions</hd> <p>Twenty-first-century survival skills should include also the ability to manage even complex interactions in a mediated context in a creative way (Kumpulainen, Mikkola, & Jaatinen, [<reflink idref="bib42" id="ref97">42</reflink>]). Technology and creativity have become a pervasive issue from the work (Turel & Zhang, [<reflink idref="bib69" id="ref98">69</reflink>]), to the artistic (e.g., Biasutti, [<reflink idref="bib6" id="ref99">6</reflink>]), and to the pedagogical domain (e.g., Kumpulainen et al., [<reflink idref="bib42" id="ref100">42</reflink>]). This work evidenced how creativity occurs even in blended environments when people interact physically and online. Starting from an idea of <emph>networked creativity</emph>, this study applied the NF model to unveil the experiential and structural dynamics of group creative process in blended environments. Here, two online social networks, which introduced a "mediated" interaction component of analysis, were considered, i.e., Facebook and Whatsapp. To our best knowledge, this study is a pioneer in the field of these two social networks and creativity. Crucially, since the NF model posited that both online and in presence interactions are useful for group creativity to emerge, an analysis integrating the physical exchanges among members with Facebook and Whatsapp-based interactions was adopted to achieve a more integrated and exhaustive group creative process view.</p> <p>Practically, the core aspects of this research can be summed up as follows. First, creative collaboration performance and Group flow may not have a simple linear relationship, even though they both resulted related to specific group structural dynamics. Micro-communicative exchanges among members are crucial, and could be either frequent or not frequent, but they need to be used to fuel group experience. Results may suggest a three-stage process. It starts with group members building a common frame to settle a shared collaborative ground with a maximum level of group flow and social presence. This would give rise a Mutual zone of proximal development in which individuals just need to find the best ways to sustain the highest levels group flow and social presence through specific interactions. This hypothesis is supported also by qualitative analysis of the dialogs among members in the early stages of group collaboration of Group A. Initially, members spend more time-sharing ideas to enter a MZPD. As a second stage, they need less coordination effort. This would lead to artifact creation in the third phase. We may assume an initial phase of "closeness" promoting engagement in the creative process. Then, the network could have displayed more lax links among members bringing forth an "open" network structure with a density no longer related to final creative outcomes (Porter, Keith, & Woo, [<reflink idref="bib56" id="ref101">56</reflink>]).</p> <p>To complete the picture, results may suggest that a formula for group creativity it does not exist, instead, there could be potentially different pathways. Specifically, there could be, at least, two possible interactive dynamics at the base of NF experience. NF might be either manifested in many interactions (i.e., "explicit" NF) or in fewer ones (i.e., a sort of "silent NF"). An effective metaphor to explain this process can be drawn from Quantum physics regarding the wave-particle dualism. This posits that light can be shaped as a wave or particle, but it is always light. This could be the case of NF in creative collaboration teams. Optimal group experience of excellent creative teams might take two different forms: an explicit one (e.g., Group B: high Density and Centralization indexes) or an implicit one (e.g., Group A: low Density and Centralization indexes). The explicit form could be easily detected through SNA indexes, since it would result into a larger number of frequent interactions among members. The implicit form would be more difficult to measure by means of structural indexes since it would require a smaller number of interactions among team members. This depends on the group members' "maintenance" strategy to sustain NF.</p> <p>A future step to test this hypothesis, could be implementing measures of implicit communication such as eye contact exchanges, as it has been successfully done in previous studies but in different domains (e.g., Gaggioli et al., [<reflink idref="bib21" id="ref102">21</reflink>]), overcoming the influence of social norms, and accessing a more authentic and sincere level of group dynamics. Finally, the aim of this study was explorative, and it focused only on 10 groups with small size, therefore, it would be useful to replicate and extend the findings of this study with a wider sample. Moreover, in order to advance the implementation of the NF model in ecological and complex contexts, a future step could be to integrate our current longitudinal network analysis approach with a more sophisticated modeling technique such as SIENA modeling (Simulation Investigation for Empirical Network Analysis) (Snijders, [<reflink idref="bib63" id="ref103">63</reflink>]).</p> <hd id="AN0141876848-17">Disclosure statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0141876848-18">Appendix A</hd> <hd1 id="AN0141876848-19">Transcriptions conventions</hd1> <p>- cut off of the prior word or sound</p> <p> <bold>()</bold> description of situation/speaker's actions</p> <p> <bold>word</bold> forms of stressing (pitch and/or volume)</p> <p> <bold>(0.1)</bold> elapsed time in tenths of seconds</p> <p> <bold>=</bold> lack of interval between the end of a prior and start of a next piece of talk</p> <p> <bold>(h)</bold> explosive aspiration</p> <p> <bold>°()</bold> low in volume</p> <p>: prolonging of sounds</p> <p> <bold>// //</bold> segments overlapped by the talk of another</p> <ref id="AN0141876848-20"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref55" type="bt">1</bibl> <bibtext> Author Note This article is part of a Special Issue and based on the "Creativity, learning, and technology" symposium held in Geneva on the 7th of December 2017, co-organized by the Webster Center for Creativity and Innovation (Webster University Geneva) and the Center for the Science of Learning and Technology (University of Bergen). The Guest editors are Vlad Glaveanu, Ingunn Ness and Constance de Saint Laurent. The authors attest that there are no conflicts of interest and that the data reported here have not been used in any other publications</bibtext> </blist> <blist> <bibl id="bib2" idref="ref31" type="bt">2</bibl> <bibtext> Color versions of one or more of the figures in the article can be found online at <ulink href="http://www.tandfonline.com/hcrj">www.tandfonline.com/hcrj</ulink>.</bibtext> </blist> </ref> <ref id="AN0141876848-21"> <title> References </title> <blist> <bibtext> Agresti, A., & Kateri, M. (2011). Categorical data analysis international encyclopedia of statistical science (pp. 206 – 208). Springer Berlin Heidelberg.</bibtext> </blist> <blist> <bibtext> Amabile, T. M. (1982). Social psychology of creativity: A consensual assessment technique. 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Networked Flow in Creative Collaboration: A Mixed Method Study
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Gaggioli%2C+Andrea%22">Gaggioli, Andrea</searchLink><br /><searchLink fieldCode="AR" term="%22Mazzoni%2C+Elvis%22">Mazzoni, Elvis</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-7258-5381">0000-0002-7258-5381</externalLink>)<br /><searchLink fieldCode="AR" term="%22Benvenuti%2C+Martina%22">Benvenuti, Martina</searchLink><br /><searchLink fieldCode="AR" term="%22Galimberti%2C+Carlo%22">Galimberti, Carlo</searchLink><br /><searchLink fieldCode="AR" term="%22Bova%2C+Antonio%22">Bova, Antonio</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-6371-0371">0000-0002-6371-0371</externalLink>)<br /><searchLink fieldCode="AR" term="%22Brivio%2C+Eleonora%22">Brivio, Eleonora</searchLink><br /><searchLink fieldCode="AR" term="%22Cipresso%2C+Pietro%22">Cipresso, Pietro</searchLink><br /><searchLink fieldCode="AR" term="%22Riva%2C+Giuseppe%22">Riva, Giuseppe</searchLink><br /><searchLink fieldCode="AR" term="%22Chirico%2C+Alice%22">Chirico, Alice</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Creativity+Research+Journal%22"><i>Creativity Research Journal</i></searchLink>. 2020 32(1):41-54.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 14
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2020
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Creativity%22">Creativity</searchLink><br /><searchLink fieldCode="DE" term="%22Group+Dynamics%22">Group Dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Networks%22">Networks</searchLink><br /><searchLink fieldCode="DE" term="%22Social+Networks%22">Social Networks</searchLink><br /><searchLink fieldCode="DE" term="%22Network+Analysis%22">Network Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+Relationship%22">Interpersonal Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Business+Communication%22">Business Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Course+Descriptions%22">Course Descriptions</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Interaction+Process+Analysis%22">Interaction Process Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Italy+%28Milan%29%22">Italy (Milan)</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/10400419.2020.1712160
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1040-0419
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The recent model of Networked flow (NF) mapped out factors underlying optimal creative collaboration in blended spaces (physical and digital). NF conceives creativity as an evolving network bridging material and symbolic resources of the creative collaboration process at both inter and the intra-group levels. First, this model posits that optimal group creativity is characterized by highest levels of the experiences of flow and social presence. Secondly, these experiences should stem from a peculiar group communicative structure. Therefore, group creativity should be studied through a mixed-method approach focusing on experiential and structural features of group collaboration, on their evolution, and on group artifacts. Here, we measured the evolution of 10 groups' structural dynamics by means of Social Network Analysis (SNA), and we assessed group experience through group flow experience (Flow State Scale) and social presence (NMSPI). Moreover, four independent raters evaluated the creative products through a domain-based approach, that is the Consensual Assessment Technique. Finally, we deepened the analysis of the highest creative group' micro-interaction through the qualitative approach of Interlocutory Logic. Group flow and social presence were positively related. Both experiential dimensions and creative outcomes were predicted by specific SNA indexes. Qualitative approach of Interlocutory Logic and an analysis of most and least creative groups' sociograms, suggested two structural patterns underlying optimal group creativity instances. Specifically, even a few but well-aimed interactions could facilitate the emergence of higher creativity levels, which could emerge silently, with few but effective interactions, or explicitly, with several (mostly) democratic exchanges among members.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1244282
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      – Text: English
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        PageCount: 14
        StartPage: 41
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      – SubjectFull: Italy (Milan)
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