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Preprint Design Thinking Research 2023, Springer
Priming Activity to Increase Interpersonal Closeness,
Inter-brain Coherence, and Team Creativity Outcome
Stephanie Balters, Grace Hawthorne, Allan L. Reiss
Center for Interdisciplinary Brain Sciences Research
Department of Psychiatry and Behavioral Sciences
Stanford University School of Medicine
401 Quarry Road
Stanford, CA 94305-5795
Stephanie Balters: balters@stanford.edu
Allan L. Reiss: reiss@stanford.edu
Hasso Plattner Institute of Design (d.school)
Building 550, 416 Escondido Mall
Stanford, CA 94305-3086
Grace Hawthorne: grace@dschool.stanford.edu
2
Abstract
Organizational research demonstrates that team interpersonal closeness enhances team
performance and creativity. Design thinking practitioners and educators have adopted the
concepts of interpersonal closeness and developed priming activities to propel subsequent
creative-innovation tasks. In recent years it has become paramount that these activities are
effective in in-person and virtual (Zoom®) interaction settings. In this chapter, we present a design
thinking (DT) activity to increase interpersonal closeness in in-person and virtual teams. We
derived the DT activity from a Nonviolent Communication exercise frequently used to increase
interpersonal closeness between individuals. In an empirical study (N = 72 participants, N = 36
dyads), we assessed whether the DT activity increased interpersonal closeness compared to two
control tasks (i.e., a problem-solving and a creative-innovation task). Dyads partners engaged in
either an in-person or virtual interaction group throughout the experiment (between-subject
design). We also captured inter-brain signatures between dyad partners with portable functional-
near infrared spectroscopy neuroimaging during the entire study. Results show that the DT activity
increased interpersonal closeness in the in-person and virtual groups compared to the control
tasks. We identified a distinct inter-brain signature in the right frontocortical region linked to the
DT activity. Notably, this inter-brain signature differed between in-person and virtual groups. This
finding suggests that conducting the DT activity in person may be more conducive to this prosocial
inter-brain coherence pattern than the virtual interaction setting. Finally, preliminary results (N =
12 dyads) suggest that the DT activity increased performance in a subsequent creative-innovation
task. Future research needs to confirm this hypothesis.
3
1. Introduction
Design thinking practice has adopted the concept of interpersonal closeness to improve team
collaboration and creative innovation (Druskat & Wolff, 2001b; Uebernickel & Thong, 2021).
Research shows that design thinking training can increase team collaboration and creative
confidence (Jobst et al., 2012; Kelley & Kelley, 2013; Rauth et al., 2010; Royalty et al., 2012,
2014) through practicing empathy and social interaction skills in a design thinking team setting
(Noweski et al., 2012; Plank et al., 2021; Traifeh et al., 2020; von Thienen et al., 2017).
Practitioners are using many design thinking activities – explicitly or implicitly- to help increase
interpersonal closeness and thereby enhance team collaboration and creative innovation
(Kerguenne, 2021; Koch, 2021; Ney & Meinel, 2019). For example, team “check-ins” and “check-
outs” before and after each workday to share momentary personal sensitivities, opinions, and
feelings with the team can improve team collaboration (Ney & Meinel, 2019). If a team or
interpersonal conflict needs to be resolved, design thinking encourages the use of structured
formats for communicating and receiving feedback (Ney & Meinel, 2019). Other activities serve
as primers for specific collaborative work modes (e.g., creative-innovation sessions) and are
typically applied when initiating a new design thinking work phase. Such design thinking (DT)
activities usually involve stepping out of one’s comfort zone and often result in some form of
playful body movement or verbal interaction (Rothouse, 2020; West et al., 2017). As a result,
these DT activities contribute to establishing a work culture of psychological trust (Auernhammer
& Roth, 2021; Edmondson, 1999; Liedtka, 2017), in which one is permitted to make mistakes and
show vulnerabilities in front of colleagues without fearing rejection (West et al., 2017).
In the last year’s edition of Design Thinking Research, we introduced a DT activity
designed to enhance interpersonal closeness and team creative innovation in in-person and
virtual (Zoom®) team interactions (Balters, Weinstein, et al., 2022). We derived the DT activity
from Nonviolent Communication Practices, a communication method to increase interpersonal
closeness and trust between individuals (Rosenberg & Chopra, 2015). Here, we provide empirical
validation of the effectiveness of this DT activity in both in-person and virtual (Zoom®) interaction
settings. We invited a total of N = 72 participants who interacted with their dyad partner either in
person or virtually during the duration of the study. Dyads collaborated during the DT activity and
two control tasks (i.e., a problem-solving and a creative-innovation task). After each of the three
tasks, participants rated measures of interpersonal closeness (i.e., connectedness, trust, likability,
other-in-self, and similarity). We also captured inter-brain signatures between dyad partners using
4
functional near-infrared spectroscopy neuroimaging during the entire study. Our analyses focused
on (1) elucidating the behavioral and inter-brain correlates of the DT activity and (2) assessing
whether the effectiveness of the interaction differed between in-person and virtual interactions.
2. DT Activity to Increase Interpersonal Closeness between Dyad Partners
During the DT activity, participants engage in a modified version of a Nonviolent Communication
exercise used to increase interpersonal closeness and trust between individuals (Rosenberg &
Chopra, 2015). Participants are provided with a list of “Needs We All Have” (Figure 1).
Participants are asked to collaborate and identify four needs from the list that are most meaningful
to them. To emphasize the importance of each need, they are asked to describe a situation from
their life when this need was not met and how it made them feel. The partner is instructed to
actively listen, acknowledge the feelings of the one who shared, and describe why the need is
also meaningful to them. The design thinking facilitator keeps a time of eight minutes.
Figure 1. Instructions for the DT activity. The Figure is derived from (Balters, Weinstein, et al., 2022).
Needs we all have
acceptance
affection
appreciation
belonging
cooperation
communication
closeness
community
companionship
compassion
consideration
consistency
empathy
inclusion
intimacy
love
mutuality
nurturing
respect/self-respect
safety
security
stability
support
to know and to be known
to see and be seen
to understand and be understood
trust
warmth
Introduction: For the next eight minutes collaborate with your partner. Together, identify four
needs from the list above that are most meaningful to both of you. To emphasize the
importance of each need, describe a situation from your own life when that need was not met
and how it made you feel. As a partner, listen actively, acknowledge the feelings of the one
who shared, and describe why the need is also meaningful to you.
5
Figure 2. Between-subject study setup. Thirty-six dyads interacted either in in-person (A) or virtually (B)
during the study.
3. Study Methodology to Assess the Efficacy of Need Sharing Activity
The study methodology was approved by the Stanford University Institutional Review Board (IRB
#18160) and followed COVID-19 regulations for human experimentation as defined by the
Stanford University School of Medicine. Written consent was obtained from all participants. The
study methodology has been previously presented in (Balters, Miller, et al., 2023). Below, we
summarize the study methodology and refer the reader to the original paper for detailed
information.
3.1 Participants
A total of 72 adults participated in the study (36 females, 36 males, mean age: 27.11 years, SD =
7.57 years). The racial and ethnic composition of the sample was 3% African American/Black,
23% Asian/Pacific Islander, 6% Biracial/Multiracial, 15% Hispanic/Latinx, 6% Middle Eastern,
22% South Asian, and 25% Caucasian/White.). All participants were right-handed, healthy, with
normal or corrected to normal hearing and vision. The study followed a between-subject design,
and participants interacted with their dyad partner either in person or virtually throughout the
experiment. The previously unacquainted dyad partners were randomly assigned to either
interaction condition. Groups were matched based on age, sex, and race/ethnicity. Both
interaction conditions contained six female-female, six female-male, and six male-male dyads.
The experimental procedure lasted approximately three hours, and participants were
compensated with an Amazon gift card ($25 USD per hour).
3.2 Experimental Procedure
In the in-person group, dyads sat face-to-face at a square table nine feet away, following
A
B
6
Figure 3. Functional NIRS regions of interest. We measured concentration changes of oxygenated
hemoglobin (HbO) in 32 regions of interest across the cortex.
COVID-19 guidelines. To decrease obstruction of faces, participants wore transparent, anti-fog
facemasks (ClearMask™). Dyads of the virtual group sat at desks in two separate rooms and
interacted over Zoom® video conferencing. The Zoom® window was maximized, and no self-view
window was displayed. We used two identical laptops for video conferencing (Lenovo Yoga 730-
15IKB, 15.6”) and placed the laptops to approximate the facial proportions of the in-person group.
Participants of the virtual group also wore a facemask to prevent bias between the conditions.
Before the experiment, participants had three minutes to introduce themselves to one another.
During the experiment, participants were alone in the room(s), and we provided instructions
through audio prompts. After the experiment, participants filled out post-experimental
questionnaires in two separate rooms.
3.3 Experimental Tasks
In addition to the 8-min-long DT activity described in Section 2, participants engaged in two other
collaborative tasks (i.e., a problem-solving and a creative-innovation task). Both tasks serve as
control tasks in data analyses that test the effectiveness of the DT activity. In the problem-solving
task, dyads were instructed to collaborate and identify four traffic rules that significantly impact
safety on US highways. To emphasize the importance of each rule, participants had to describe
how a chosen rule enhances safety on US highways and why the rule was more important than
other traffic rules. In the creative-innovation task, dyads were instructed to collaborate and to
design a solution to increase water conservation in California households. The solution could take
any form (i.e., product, process, campaign, etc.). Dyads were instructed to write down their
solution after completion of the task. Dyads collaborated on each task (i.e., DT activity, problem-
solving task, and creative-innovation task) for eight minutes without interruptions. The task order
was randomized across dyads, and we separated tasks by a two-minute calming video of a beach
to minimize carryover effects across tasks.
A
Top
Front
Left
Back
Right
7
3.4 Neuroimaging with Functional Near-Infrared Spectroscopy (fNIRS)
Functional Near-Infrared Spectroscopy (fNIRS) is a portable neuroimaging technology that has
become popular in the field of design (thinking) research (Balters & et al., 2022). Compared to
portable electroencephalography (EEG) neuroimaging, fNIRS has a higher spatial resolution (~1
cm) and higher robustness to motion artefacts (Li et al., 2017). These advantages make fNIRS
an ideal tool for assessing cortical brain function in applied design (thinking) contexts (Balters &
et al., 2022). For example, design (thinking) researchers have utilized fNIRS to investigate the
neural signatures associated with unstructured idea generation (i.e., brainstorming, Hu et al.,
2021) and structured idea generation via design science tools such as Theory of Inventive
Problem-solving “TRIZ” (Hu et al., 2018; Shealy et al., 2018) or sketching (Kato et al., 2017, 2018).
About a decade ago, researchers extended single-brain assessments to hyperscanning modes
in which two or more brains are scanned simultaneously. Researchers have focused on assessing
when and how neural processes become synchronized and how this inter-brain coherence (IBC;
correlation of cortical activity between brains) relates to behavioral measures (Babiloni & Astolfi,
2014; Balters et al., 2020; Czeszumski et al., 2020). Results from fNIRS hyperscanning studies
have shown increased IBC during enhanced levels of dyadic interaction, such as during
cooperative games (Baker et al., 2016; Cui et al., 2012; Kruse et al., 2021), in therapy sessions
(Zhang et al., 2018), mother-child bonding (Bembich et al., 2022), and after gift exchanges
(Balconi et al., 2019; Balconi & Fronda, 2020). For a more comprehensive introduction to fNIRS
hyperscanning, we refer the reader to Balters et al. (2020).
We utilized fNIRS hyperscanning in this study to elucidate the inter-brain correlates of the
DT activity and to assess whether the effectiveness of the interaction differed between in-person
and virtual interactions. Specifically, we recorded the cortical hemodynamic activity of each
participant using a continuous wave fNIRS system (NIRSport2 System, NIRX, Germany). We
utilized two wavelengths (760 and 850 mm) and a sampling frequency of 10.2 Hz. The system
high-density contains 64 sources and 64 detectors, which we we divided between the two
participants to generate 100 measurement channels per person. According to the international
10-20 EEG placement system, we placed the channels over the entire cortex. For data
processing, we followed rigorous scientific procedures (see Balters, Miller, et al., 2023 for detailed
processing steps) to derive concentration changes of oxygenated hemoglobin (HbO) for a total of
32 regions of interest (ROIs). We then applied Wavelet Transform Coherence analysis (Cui et al.,
2012) to assess averaged IBC values across each 8-minute task. (Note: Inter-brain coherence is
a measure of similarity between NIRS signals of dyad partners across a specific time duration).
8
For each task (i.e., DT activity, problem-solving task, and creative-innovation task), we calculated
IBC values for each possible ROI pair between participants. We utilized these IBC values in
statistical analyses.
3.5 Interpersonal Closeness Measures
Participants rated the subjective sense of closeness towards their dyad partner (i.e.,
“Interpersonal Closeness” [Tarr et al., 2015]) on five 7-point Likert subscales. This included
questions about connectedness and trust (Wiltermuth & Heath, 2009), likeability (Hove & Risen,
2009), similarity in personality (Valdesolo & DeSteno, 2011), and an adapted version of the
inclusion of other in self scale (i.e., “people’s sense of being interconnected with another”; Aron
et al., 1992). We used the five interpersonal closeness measures to test if the DT activity, in
contrast to the two control tasks, was effective in increasing interpersonal closeness in the in-
person and virtual dyads.
3.6 Post Experimental Assessments
After the experiment, participants filled out personality trait surveys (i.e., NEO-FFI-3 survey
[McCrae & Costa, 2007], Adult Attachment Scale Survey [Collins & Read, 1990], and Wong and
Law’s Emotional Intelligence Survey [Wong & Law, 2002]) to capture personality traits. They also
executed the Alternate Uses Task (AUT) to assess individual levels of divergent thinking and
creativity (Guilford, 1967). Lastly, participants rated their prior experience and proficiency with
Zoom® video conferencing. We used these measures to assess whether the two groups (in-
person, virtual) matched on various individual difference variables or whether certain covariates
would need to be considered in statistical analyses.
4. Study Results and Discussion
4.1 Conditions were Matched on Individual Difference Variables
In the original paper (Balters, Miller, et al., 2023), we demonstrated that the two groups (in-person,
virtual) matched on various individual difference variables. Specifically, subjects participating in
the two groups were matched on age, inter-dyad age differences, personality traits (i.e., NEO-
FFI-3 T scores, Adult Attachment style, emotional intelligence), creative ability (i.e., Alternate
Uses Task AUT fluency, AUT originality), and familiarity with Zoom® video conferencing (i.e.,
9
experience and proficiency). These findings allowed us to execute the primary research analyses
without controlling specific covariates.
4.2 Activity Increases Interpersonal Closeness
While we utilized the average score of all five interpersonal closeness measures in the original
paper (Balters, Miller, et al., 2023), we present a novel measure-specific in this chapter. For each
of the five interpersonal closeness measures (i.e., connectedness, trust, likability, other-in-self,
and similarity), we ran a two-way analysis of variance (ANOVA) with task (problem-solving,
creative-innovation, DT activity) as within-subjects factor and group (in-person, virtual) as
between-subjects factor. These analyses tested for potential main effects of task, main effects of
group, and interaction effects of task and group on the five measures. We applied false discovery
rate (FDR) correction for multiple testing on the resulting p values (i.e., five testings). The results
showed significant main effects of task on connectedness (F[2,140] = 9.458, p < 0.001, partial
η2 = 0.119), trust (F[2,140] = 8.556, p < 0.001, partial η2 = 0.109), likability (F[2,140] = 10.590, p
< 0.001, partial η2 = 0.131) and other-in-self (F[2,140] = 9.458, p = 0.013, partial η2 = 0.064), but
not on similarity (p = 0.068). We conducted subsequent posthoc pair-wise comparison analyses
with FDR correction for multiple comparisons (i.e., three comparisons per measure). The results
for all four measures showed increased values for the DT activity compared to the problem-
solving and creative-innovation task (Figure 4). We summarize the statistics in Table 1. There
were no significant differences between the problem-solving and the creative-innovation tasks.
The results indicate that the DT activity effectively increased connectedness, trust, likability, and
other-in-self measures in contrast to both control tasks. Notably, we did not find the main effects
of group or interaction effects of task and group on any of the five measures (p > 0.155). These
results suggest that the DT activity effectively increased interpersonal closeness measures
independent of the interaction settings.
For the four interpersonal closeness measures that showed significant univariate effects,
we conducted subsequent correlation analyses with each of the other three measures. These
analyses focused on data from the DT activity only. We used FDR-correction to adjust for multiple
testing (i.e., six correlation analyses). Results showed statistically significant positive correlations
for all six analyses (0.40 < r < 0.84, p < 0.001; Figure 5). These findings validate
that connectedness, trust, likability, and other-in-self are all measures of the same interpersonal
closeness construct.
10
Figure 4. Results of the interpersonal closeness measures. Four of the five interpersonal closeness
measures (i.e., connectedness, trust, likability, and other-in-self) showed higher values in the DT activity as
compared to the two control tasks (i.e., problem-solving and creative innovation tasks). We did not find
main or interaction effects of group on the measures. These findings suggest that the DT activity was
effective in increasing measures of interpersonal closeness in both in-person and virtual teams. Statistically
significant differences at FDR-corrected p < 0.05 are indicated by *. Variance is illustrated as the standard error
of the means.
Interpersonal closeness measures
Mean difference between task with adjusted p values
Connectedness
DT activity > problem-solving task
DT activity > creative-innovation task
0.389 [95% CI, 0.181 to 0.596, p < 0.001]
0.458 [95% CI, 0.214 to 0.702, p < 0.001]
Trust
DT activity > problem-solving task
DT activity > creative-innovation task
0.208 [95% CI, 0.040 to 0.377, p = 0.024]
0.347 [95% CI, 0.170 to 0.525, p < 0.001]
Likability
DT activity > problem-solving task
DT activity > creative-innovation task
0.222 [95% CI, 0.009 to 0.355, p = 0.002]
0.403 [95% CI, 0.222 to 0.583, p < 0.001]
Other-in-self
DT activity > problem-solving task
DT activity > creative-innovation task
0.208 [95% CI, 0.022 to 0.394, p = 0.044]
0.319 [95% CI, 0.072 to 0.567, p = 0.036]
Table 1. Overview of the pair-wise comparison statistics. Abbreviation: Confidence Interval (CI)
5
5.2
5.4
5.6
5.8
6
6.2
Connectedness
5
5.2
5.4
5.6
5.8
6
6.2
Trust
7
7.2
7.4
7.6
7.8
8
8.2
Likeability
3.2
3.4
3.6
3.8
4
4.2
4.4
Other-in-self
Problem-
solving Creative-
innovation DT
Activity Problem-
solving Creative-
innovation DT
Activity
Problem-
solving Creative-
innovation DT
Activity Problem-
solving Creative-
innovation DT
Activity
****
****
11
Figure 5. Results of the correlation analyses across interpersonal closeness measures. Results
showed statistically significant correlations between all four interpersonal closeness measures that
demonstrated significant differences in the primary analyses. The moderate to strong associations are
positive. These findings validate that connectedness, trust, likability, and other-in-self are all measures of
the same interpersonal closeness construct.
4.3 Inter-Brain Coherence
In the original paper (Balters, Miller, et al., 2023), we executed statistical analyses to assess
whether there were main effects of task (problem-solving task, creative-innovation task, DT
activity), main effects of group (in-person, virtual), or interaction effects of task and group on inter-
brain coherence values. The results showed a statistically significant interaction effect of task and
group for an ROI pair spanning the right dorsal frontopolar area (dFPA) across dyad partners
(Figure 6A). In other words, specifically for the DT activity (and not the other two tasks), IBC
significantly differed between in-person and virtual dyads. As demonstrated in Figure 6B, IBC
was higher in the in-person group than in the virtual group (mean difference = 0.084 [95% CI,
0.045 to 0.123, p < 0.001]). Prior research has consistently found increased IBC, particularly in
right prefrontal ROI pairs, to be positively associated with prosocial behavior (Cui et al., 2012; Dai
et al., 2018; Liu et al., 2016; Lu et al., 2019; Miller et al., 2019; Pan et al., 2017; Xue et al., 2018).
Therefore, our findings suggest that conducting the DT activity in person elicits IBC, which may
be more conducive to prosocial interaction (Balters, Miller, et al., 2023).
0
2
4
6
8
0 2 4 6 8 10
Connectedness
Trust
0
2
4
6
8
4 6 8 10
Connectedness
Likability
0
2
4
6
8
02468
Connectedness
Other-in-self
0
2
4
6
8
4 6 8 10
Trust
Likability
0
2
4
6
8
02468
Trust
Other-in-self
4
6
8
10
0 2 4 6 8
Likability
Other-in-self
r= 0.84
p< 0.001
r= 0.56
p< 0.001
r= 0.46
p< 0.001
r= 0.64
p< 0.001
r= 0.41
p< 0.001
r= 0.40
p< 0.001
12
Figure 6. Results of the inter-brain coherence analyses. Results showed a statistically significant
interaction effect between task and group for the ROI pair spanning the right dorsal frontopolar area (dFPA)
across dyad partners. In other words, specifically for the DT activity (and not the other two tasks), IBC
significantly differed between in-person and virtual dyads. Statistically significant differences at FDR-corrected
p < 0.05 are indicated by *. Variance is illustrated as the standard error of the means.
4.4 Preliminary Performance Analysis in Subsequent Creative-Innovation Task
Lastly, we were interested in getting a first glimpse of whether the DT activity effectively increased
performance in a subsequent creative innovation session. We conducted a preliminary analysis
of parts of the existing data. Specifically, we utilized data from task order 1 and task order 6 that
resulted from this study's randomized task order methodology (with N = 6 dyads per order across
both groups; Figure 7A). Dyads with task order 1 experienced the DT activity before the creative-
innovation task. In contrast, dyads with task order 6 experienced the problem-solving task before
the creative-innovation task. This preliminary analysis used the latter task order as a control
condition. We define task order 1 as the “priming condition” and task order 6 as the “control
condition”.
Two researchers rated the level of creative-innovation for all dyads to generate
performance measures of the creative-innovation task. Both raters had expertise in assessing
creative-innovation according to the Stanford Design School principles (authors S.B. and G.H.).
Specifically, the raters assessed the creative-innovation rating based on four subscales, including
fluency (i.e., the total number of elements in a design solution), originality (i.e., the statistical rarity
of the response across answers in this study), elaboration (i.e., the level of imagination and
exposition of detail), and accountability (i.e., the effectiveness of water conservation) as derived
from (Torrance, 1974). We obtained the ratings on a five-point scale ranging from 1 (“very low”)
to 5 (“very high”) and averaged the scores from these four subscales to get the final creative-
0.2
0.3
0.4
Inter-brain Coherence
In-person Virtual
*
A
B
13
Figure 7. Descriptive results of the preliminary analysis of performance in subsequent creative-
innovation task. (A) Our study methodology comprised six different task orders across dyads due to the
randomization of the three experimental tasks. (B) Descriptive findings indicate that the DT activity (here
labeled priming condition) could effectively increase performance in a subsequent creative innovation task
compared to the control condition. Horizontal lines represent the median values, and „x“ represent
the mean values.
innovation performance score. Inter-rater reliability index was good (ICC = 0.855). We extracted
the scores from dyads belonging to the priming condition and the control condition. We removed
outliers with more than two standard deviations from the mean, which resulted in data for N = 5
dyads in the priming condition and N = 6 in the control condition. Due to the low statistical power,
we refrained from executing formal statistical analyses and inspected descriptive statistics,
including effect sizes. As depicted in Figure 7B, the average task performance in the creative-
innovation task was higher for the priming condition than the control condition, with a moderate
effect size of Cohen’s d = 0.500. These descriptive results could suggest that the DT activity was
effective in increasing performance in the subsequent creative-innovation task, compared to a
preceding problem-solving task. Subsequent correlation analyses between the performance
score and each creative ability score (i.e., AUT fluency and AUT originality from section 4.1)
across all N = 11 dyads were not significant (p > 0.223). This additional preliminary finding
suggests that the observed descriptive difference in performance score could be attributed to the
DT activity rather than differences in creative ability traits between dyads in the two conditions.
Future research needs to formally test the hypothesis that the DT activity, compared to a control
task (e.g., problem-solving task), increases performance in a subsequent creative-innovation
task.
5. Conclusion
This chapter presented a DT activity to increase interpersonal closeness and creative innovation
in in-person and virtual design thinking teams. We derived the DT activity from a Nonviolent
Communication exercise frequently used to increase interpersonal closeness between
N= 6 dyads across both conditions
N= 6 dyads across both conditions
Problem-solving task
Task Order 1
Task Order 2
Task Order 3
Task Order 4
Task Order 5
Task Order 6
Creative-innovation task Priming condition Control condition
4
0
1
2
3
Creative-innovation
task performance
DT activity
N= 5 N= 6
A
B
14
individuals. We tested the effectiveness of the DT activity through an empirical study that
considered both in-person (N = 18 dyads) and virtual interaction settings (N = 18 dyads). The
study results provide evidence that the DT activity, in contrast to two other collaborative control
tasks (i.e., problem-solving and creative innovation tasks), effectively increased measures of
interpersonal closeness (i.e., connectedness, trust, likability, and other-in-self) in both in-person
and virtual interaction settings. Functional NIRS neuroimaging results demonstrated that the DT
activity elicited inter-brain coherence in regions associated with prosocial behavior. However, our
findings also indicate that conducting the DT activity in person could be more conducive to this
prosocial inter-brain coherence pattern than the virtual interaction setting. Finally, preliminary
results indicated that the DT activity could effectively increase team performance in a subsequent
creative-innovation task. Future research needs to validate these preliminary findings. We hope
this chapter provides practitioners and educators alike with a novel DT activity to increase
interpersonal closeness in in-person and virtual design thinking teams.
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