# ”When He Feels Cold, He Goes to the Seahorse”—Blending Generative AI into
Multimaterial Storymaking for Family Expressive Arts Therapy

Di Liu  School of Design, SUSTechShenzhenChina<EMAIL_ADDRESS>,  Hanqing
Zhou  School of Design, SUSTechShenzhenChina<EMAIL_ADDRESS>and
Pengcheng An  School of Design, SUSTechShenzhenChina<EMAIL_ADDRESS>
(2024)

###### Abstract.

Storymaking, as an integrative form of expressive arts therapy, is an
effective means to foster family communication. Yet, the integration of
generative AI as expressive materials in therapeutic storymaking remains
underexplored. And there is a lack of HCI implications on how to support
families and therapists in this context. Addressing this, our study involved
five weeks of storymaking sessions with seven families guided by a
professional therapist. In these sessions, the families used both traditional
art-making materials and image-based generative AI to create and evolve their
family stories. Via the rich empirical data and commentaries from four expert
therapists, we contextualize how families creatively melded AI and traditional
expressive materials to externalize their ideas and feelings. Through the lens
of Expressive Therapies Continuum (ETC), we characterize the therapeutic
implications of AI as expressive materials. Desirable interaction qualities to
support children, parents, and therapists are distilled for future HCI
research.

Expressive arts therapy, storymaking, family, children, generative AI, human-
AI interaction.

††journalyear: 2024††copyright: acmlicensed††conference: Proceedings of the
CHI Conference on Human Factors in Computing Systems; May 11–16, 2024;
Honolulu, HI, USA††booktitle: Proceedings of the CHI Conference on Human
Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI,
USA††doi: 10.1145/3613904.3642852††isbn: 979-8-4007-0330-0/24/05††ccs: Human-
centered computing Empirical studies in HCI

Figure 1. (a) Character Making; (b) Scene/Object Making; (c) Story Making and
Storytelling; (d) Story Sharing and Reflection; (e) Setup Display of Family
Expressive Arts Therapy Activity.

In Figure a, an orange octopus toy is transformed into a cartoon character
octopus image, and a yellow chick created using clay is transformed into a
cute yellow chick image. In Figure b, a colorful castle built using different
colors of Lego is displayed. Additionally, a forest scene created using
brightly colored cloth collage is transformed into a beautiful forest. Figure
c illustrates a father and his son telling stories together using AI-infused
multi-material. In Figure d, the father and his son are shown at home sharing
the creation of physical storybooks, and children are seen sharing their own
storybooks with others in kindergarten. Figure e uses simple drawings to
depict the layout of activity scenes.Parents and children collaborate using
physical materials to create artifacts together, while the therapist observes
their creative process. When family-created artifacts and verbal descriptions
of the family are fed into the generative AI as prompts, children and parents
can choose to discuss them together. The final storybook is taken home and
shared with parents.

##  1\. Introduction

Family communication plays a pivotal role in co-constructing and negotiating
meanings, shaping identity, and influencing the dynamics of parent-child
relationships (Braithwaite et al., 2017). It can also support children’s
psychological well-being and overall development (KavehFarsani et al., 2020).
However, family communications can be hindered or disrupted by many issues,
such as excessive technology use (Chin Derix et al., 2022), parental
work–family conflict (Morr Loftus and Droser, 2020), and undesirable
communication patterns (Ritchie and Fitzpatrick, 1990). This could result in
significant and lasting negative effects, including increased family tension
or conflict (Shin et al., 2021), mental health issues of children (Barrett et
al., 2001), and behavioral problems and at-risk behaviors of the family unit
(Xiao et al., 2011). Hence, it is essential to enhance the understanding of
family dynamics and foster effective family communication.

Family expressive arts therapy, facilitated by expressive art therapists,
engages family groups in integrative and multi-modal expressive and
constructive tasks—e.g., drawing, playing, storytelling, or collage-
making—which can help break down barriers of communication and develop a
collaborative approach to explore family dynamics and strengthen family
relationships (Malchiodi, 2013; Kwiatkowska, 1967; Levick and Herring, 1973).
Storymaking has been one of such therapeutic activities frequently leveraged
by therapists with family groups, especially children and parents (Friedland,
2010; Miller, [n.d.]). In a storymaking-based expressive arts therapy session,
therapists usually guide family members to co-create therapeutic stories that
externalize their inner thoughts, reflect their shared experiences, and
encourage mutual understanding through the integration of art-making and
storytelling. Despite these benefits for families, research in Human-Computer
Interaction (HCI) has accumulated little knowledge about how to support
families and therapists in storymaking-based expressive arts therapy sessions.

Nonetheless, outside the settings of expressive arts therapy, a substantial
body of studies focus on supporting storytelling and storymaking for children
and families (Zhang et al., 2022a; Dietz et al., 2021; Rubegni and Landoni,
2014; Panjwani, 2017). As distinguished by prior research, storytelling
focuses on the act of narrating a story, whereas storymaking refers to
creating a story by integrating the inventive modes of storytelling and
crafting (Panjwani, 2017). Much research in HCI has explored how to support
storytelling to facilitate various purposes, such as remote communication
(Raffle et al., 2010, 2011), language learning (Kory and Breazeal, 2014; Druin
et al., 2009), physical fitness (Saksono and Parker, 2017), and mathematics
learning (Alexandre et al., 2010), to name but a few. On the other hand, many
studies also encompassed children’s storymaking: creating physical or digital
stories to, for instance, promote children’s creativity (Zarei et al., 2021;
Lu et al., 2011), emotional expression learning (Schlauch et al., 2022; Ryokai
et al., 2012), or computational thinking and programming (Dietz et al., 2021,
2023). Among them, relatively a small number of studies concerned how to
support children and their families to collaborate in crafting stories. As an
example, Torben et al. developed a tangible storytelling system to aid long-
distance relationships between grandparents and grandchildren through crafting
(Wallbaum et al., 2018). Ricarose et al. examined the benefits and challenges
of involving youth and families in creating stories using the computational
constructionkit (Roque et al., 2021). While above mentioned research yielded
important insights, relatively less work has addressed family storymaking in
co-located, multilateral settings (a common setup in family expressive therapy
sessions). To the best of our knowledge, there is a lack of research into the
implications of supporting both the family (children and parents) and the
therapists when using storymaking in the settings of expressive arts therapy.

Materials occupy an essential presence in expressive arts therapy as they
afford different expressive properties that can evoke specific experiences
during the act of art-creating (Lazar et al., 2018; Regev and Snir, 2017).
While the properties of traditional physical art-making materials have been
extensively examined in expressive therapy studies (Kagin and Lusebrink, 1978;
Malchiodi, 2022), it is yet to be explored whether and how digital media,
including the emerging generative AI techniques, could be utilized as
materials for expressive arts therapy. In recent years, the concept of “AI as
a design material” has presented promising and novel prospects for designers
or design-oriented research in HCI (Dove et al., 2017; Holmquist, 2017). In
particular, with the advent of image-based generative AI tools like Dall·E 2
(OpenAI, [n.d.]), Stable Diffusion (Diffusion, [n.d.]), and Midjourney
(Midjourney, [n.d.]), some studies have delved into the exploration of
integrating text-to-image models as design materials into design practices
(Kulkarni et al., 2023; Tholander and Jonsson, 2023). These studies revealed
the potential properties of generative AI as design materials to propel the
creativity of (both amateur and professional) designers, suggesting an
unaddressed opportunity to explore the properties of generative AI when used
as expressive materials in expressive arts therapy.

Therefore, corresponding to the above-mentioned opportunities, the present
study set out to address a three-fold research question:

  * •

RQ1: how would families engage in AI-infused multimaterial storymaking in
expressive arts therapy?

  * •

RQ2: how would image-generative AI be leveraged as expressive materials in
family expressive arts therapy?

  * •

RQ3: how would future design support parents, children and therapists in
family expressive arts therapy?

To this end, we conducted family storymaking based expressive arts therapy
activities with a professional therapist based on an ongoing family expressive
arts therapy activity. We report our findings based on five-week sessions
involving 7 groups of families with 18 participants (10 parents, 8 children)
and interview data with the parents. Further, we conducted a discussion with 4
expert therapists in the form of a focus group in order to gather commentaries
about our data from a more diverse therapeutic perspective. Our findings
contextualize the creative process of the families and the therapeutic meaning
behind it. Through the lens of Expressive Therapies Continuum (ETC), we
characterize the therapeutic implications of the generative AI as expressive
materials. This paper provides relevant desirable interaction qualities to
support children, parents and therapists for future HCI research.

This paper contributes (i) empirical understandings on how to support story-
making based expressive arts therapy using the generative AI; and (ii) design
insights about desirable interaction qualities for children , parents, and
therapists, and design implications for HCI systems to support AI-infused
family expressive arts therapy.

##  2\. Background and Related Work

###  2.1. Storymaking in Expressive Arts Therapy

Expressive arts therapy has been proven to be an effective intervention to
understand family dynamics and foster family communication (Kwiatkowska, 1967;
Harvey, 1990; Lai, 2011). It refers to an integrative and multi-modal
intervention incorporating multiple art-making forms to achieve personal
growth and social transformation (Malchiodi, 2003; Levine and Levine, 1998).
Within expressive arts therapy, the focus lies on the process of creation
rather than the product of creation. Its benefits have been evident across
people of all ages (Rubin, 1999; Du et al., 2024). In an expressive arts
therapy session, an expressive arts therapist observes and encourages clients
to trigger personal growth and explore the thought through creative processes
of expression, including drawing, movement, drama, play, and storytelling.

Notably, storymaking, as a form of expressive arts therapy that combines
various types of creative and expressive tasks, has been commonly leveraged
with families (Friedland, 2010; Miller, [n.d.]; Harpaz, 2016; Matthews and
Doherty, 2011; Brosnan et al., 2006). For example, Lai et al. utilized
expressive arts therapy to enhance mother-child relationships between abused
mothers and their children and facilitate their personal transformation (Lai,
2011). Such therapeutic storymaking often incorporates art-making techniques
(e.g., drawing, clay manipulation, and collage-making) with storytelling
(Friedland, 2010; Neill, 2003). In the process of family members’ art-making,
therapists can provide a comfortable and safe space where parents and children
utilize physical expressive materials as languages for social, physical, and
spiritual wellness (Lazar et al., 2018); in addition, during their therapeutic
narrative creating process, the characters they created serve as metaphors,
projecting theirs own inner thoughts (Perrow, 2008). When developing story
plots, therapists would guide participants to build stories’ tension by
setting obstacles to encourage participants to solve problems (Perrow, 2008).
However, there is a lack of knowledge about the role of technology in family
expressive arts therapy.

In storymaking-based expressive arts therapy, clients tend to interact with
diverse expressive materials. Material interaction plays a pivotal role in
expressive arts therapy, facilitating self-expression and therapeutic healing
via creative expression (Lazar et al., 2018; Hinz, 2019). The therapists are
trained to understand the properties of various materials and their potential
therapeutic impacts. The Expressive Therapies Continuum (ETC) framework offers
valuable insights for addressing this aspect (Hinz, 2019). ETC serves as a
valuable tool for categorizing and organizing how clients interact with
expressive materials as they process information and form images (Kagin and
Lusebrink, 1978). It involved three horizontal levels (Kinesthetic/Sensory,
Perceptual/Affective, and Cognitive/Symbolic) of information processing, which
is bipolar or complementary, along with a vertical creative level as the
integration of any or all of the levels (Lusebrink, 2015).

The current practices of expressive arts therapy mainly rely on traditional
materials. Few studies introduced digital materials, and little is known about
how to leverage generative AI as expressive materials to support family
expressive arts therapy.

###  2.2. Storytelling and Storymaking in HCI

Storymaking as expressive arts therapy, remains scarcely studied in HCI.
However, a large body of HCI research has explored technologies supporting
children or families’ storytelling and storymaking outside the settings of
expressive arts therapy (Santos et al., 2020; Alexandre et al., 2010; Zhang et
al., 2022b; Sylla et al., 2015; Saksono and Parker, 2017). Storytelling and
storymaking offer distinct avenues for creative expression, with storytelling
enabling personal narrative representation and storymaking facilitating the
creation of physical representations to reflect and convey our experiences and
observations (Panjwani, 2017). The HCI domain has witnessed a surge of
interest in designing systems involving storytelling for facilitating various
applications beyond entertainment, such as social engagement (Sargeant and
Mueller, 2014; Raffle et al., 2010), development of literacy (Kory and
Breazeal, 2014; Michaelis and Mutlu, 2017), and social-emotional learning
(Santos et al., 2020). For example, a companion robot for children learning
new vocabulary through a storytelling game (Kory and Breazeal, 2014). Saksono
et al. explored using storytelling to encourage families to reflect on factors
influencing children’s physical activity (Saksono and Parker, 2017).

On the other hand, HCI research has designed applications and systems to
support children to create multimedia story content (e.g., text, audio or
photo), in order to facilitate their computational thinking and programming
(Dietz et al., 2023, 2021), collaboration skills (Rubegni and Landoni, 2014),
creativity (Zarei et al., 2020), and gender stereotype awareness (Rubegni et
al., 2019, 2022). For instance, StoryDrawer (Zhang et al., 2022b) supports
creativity and visual storytelling through co-drawing. Rubegni et al.
presented a collaborative digital storytelling tool to help children notice
the negative gender stereotypes (Rubegni et al., 2022). Moreover, a relatively
smaller body of research has focused on the storymaking by family members. The
StoryBox (Wallbaum et al., 2018) is a tangible system facilitating the long-
distance, asynchronous sharing of co-created images, written messages, and
audio between children and their grandparents. Moreover, Roque et al. explored
the opportunities and limitations arising from involving youth and their
families in the creation and sharing of stories using a computational
construction kit (Roque et al., 2021). Also, Yu et al. examined family
dynamics during family joint storymaking, focusing on the negotiation
practices among family members (Yu et al., 2023).

An emerging stream of storymaking systems also featured the integration of
physical and digital experiences for children. These tools have been
successfully leveraged to support various aspects of learning and skills
development, such as narrative development (Budd et al., 2007; Sylla et al.,
2015), emotional learning (Cai, 2023; Ryokai et al., 2012), and fantasy play
and storytelling (Cassell and Ryokai, 2001). For example, PageCraft is an
interactive storytelling that can connect physical media and digital media by
transforming children’s real-world play into text and visuals displayed on a
screen (Budd et al., 2007). However, many applications in the realm of
storymaking rely on pre-established story templates or a structured framework
which may inadvertently limit the scope of creativity (Schlauch et al., 2022).
Several studies set out to address this constraint by facilitating children’s
story creation through connecting physical and digital environments (Rubegni
and Landoni, 2018; Schlauch et al., 2022). As shown by prior research,
introducing physical materials grants children extra developmental benefits in
creative process (Resnick, 2017; Kirsh, 2013). For the same reason, when used
in family expressive arts therapy, storymaking often relies on various
physical materials. However, HCI research has sparsely explored how to support
co-located multimaterial storymaking in family expressive arts therapy. And
relevant understanding is yet to be established on whether and how generative
AI could be integrated as a form of expressive materials in this context.

###  2.3. Child or Family Engagement with AI

In HCI, there is a substantial body of research exploring how to design
technologies to promote children’s and families’ AI literacy (Long et al.,
2023; Adisa et al., 2023; Druga et al., 2022). In addition, some studies have
explored how to utilize AI algorithms in designed systems to ease children’
daily activities, such as medical diagnosis (Mohanta and Mittal, 2020),
emotion recognition (Baldovino et al., 2019) or speech recognition (Wöllmer et
al., 2011). Furthermore, a large number of studies have shown conversational
agents and embodied robotic interfaces as a collaborative partner and playmate
to facilitate children’s learning and skill development, such as question
answering behavior (Lee et al., 2023), science or math learning (Xu et al.,
2022b), social play (Pantoja et al., 2019),and growth mindset (Park et al.,
2017). For example, Ying et al. demonstrated that a conversational agent has
the potential to boost children’s engagement in narrative-relevant
vocalizations, diminish unrelated vocalizations, and elevate story
comprehension (Xu et al., 2022a). In particular, some of studies introduced
conversational AI integrating storytelling strategies. For example, Kory et
al. have shown that using a social robot narrating a story in a game could
enhance children’s early language learning (Kory and Breazeal, 2014). Also,
StoryCoder (Dietz et al., 2021) uses a voice agent to teach Computational
Thinking (CT) concepts. However, while above studies focused on child-facing
AI interfaces, some studies also involved families.

Families as an essential factor of children’s development, also play a
significant role in children’s interaction with technology (Cagiltay et al.,
2023; Beneteau et al., 2020). In contrast to the substantial body of research
focused on children, relatively a smaller proportion of research explored how
conversational agents could support both children and their family in, for
instance, joint reading (Xu et al., 2023a; Zhang et al., 2022a), family
communication (Beneteau et al., 2019, 2020), and mathematical learning (Xu et
al., 2023b). Namely, Beneteau et al. explored using smart speakers at home to
support parent-child communication and augment parenting practices (Beneteau
et al., 2020). Zhang et al. presented a human-AI storytelling system which can
enhance children’s engagement in the storytelling process through parent
involvement (Zhang et al., 2022a). These studies have yielded valuable
insights into the design of conversational AI to support children and family.

Besides conversational AI, the image generative AI models, such as Recurrent
Neural Network (RNN) (Grossberg, 2013) or Generative Adversarial Networks
(GAN) (Goodfellow et al., 2014), has also initiated its exploration into
supporting children’s creative activities. Many studies have explored how RNN-
based models can be used for child-AI co-sketching to support children’s
creativity (Zhang et al., 2022b; Ali et al., 2020, 2021; Zhang et al., 2023).
For example, Magic Draw serves as a collaborative drawing game to cultivate
children’s figurative creativity through verbal interactions between children,
a robot, and a tablet (Ali et al., 2020). Also, Bio Sketchbook, an interactive
tool, helps children observe and document biodiversity, enhancing their nature
connection and observation skills (Zhang et al., 2023). Furthermore, with the
recent development of Diffusion models (Ho et al., 2020), it can present a
promising opportunity for the expansion and innovation of image applications.
A recent study has demonstrated the efficacy of diffusion model-based image
generation tools in facilitating personalized and adaptive visual storytelling
tailored for children (Han and Cai, 2023). However, prior work has rarely
explored on how Diffusion models can be employed as family co-creative
support. Further, few studies focus on how Diffusion models incorporate into
family expressive arts therapy.

##  3\. Context Study

As a preparation for the later stage, we conducted a context study using semi-
structured online interviews with two professional expressive arts therapists.
The context study served two purposes: first, to concretely understand the
current practice of family expressive arts therapy; second, to discuss whether
image-based generative AI could potentially support families and therapists in
the context. Both therapists came with over 5 years of expertise in practice.
In the interviews, they detailed their existing approach to family expressive
arts therapy sessions. Following that, they were presented with several image-
based generative AI tools and were asked for their thoughts on whether and how
these tools could be used in their practice.

As revealed by the therapists, families typically enroll in family expressive
arts therapy because parents seek a deeper understanding of their children,
particularly the facets not readily apparent to them. They also aim to
discover improved communication methods that can bolster their child’s growth
and maintain strong parent-child bonds. Contrary to some assumptions, family
expressive arts therapy is not exclusive to families grappling with
significant relationship challenges or mental health concerns of members. In
fact, a majority of their clientele consists of typical, everyday families.
This therapeutic intervention offers families a valuable platform to
comprehend one another and themselves better. It also helps them reflect on
how their interactions and communication shape their relationships. As noted
by one of the therapists from our context study, she said: “whether an
individual experiences a positive or negative family environment has varying
effects on their emotional state. In the role of a family member, when someone
is not in a ‘healthy’ state, it often relates to their interactions within the
family. Therefore, there are situations where it is crucial for family members
to empathize and understand one another. When family members foster greater
understanding of each other’s feelings and needs, it invariably leads to
positive outcomes”.

As outlined by the therapists, family expressive arts therapy typically
comprises the following phases: Preparation, Art Creation (including
character-making, scene-making, and story-making), and Storytelling and
Reflection (refer to Table 1). In their regular sessions, therapists draw from
a diverse set of art resources and integrate therapeutic principles like
projection, positive psychotherapy, play therapy, and narrative therapy. A
variety of traditional materials are employed to enhance the family’s
expression (for outcome examples, see Figure 2).

Figure 2. Family expressive arts therapy activities conducted by a therapist:
(a) drawing; (b) collage.

Figure 2 contains two pictures. The first picture shows a mother making
gestures with her daughter, showing her relationship with her mother; the
second picture shows a child using collage to describe his school playground.

Table 1. Common Process of Family Expressive Arts Therapy. Stage |  Description |  Therapeutic Meaning
---|---|---
Preparation |  The therapist initiates a dialogue with the client to understand their current feelings and needs, then collaborates to set session goals. |  • Establishing trust and comfort;
| Art Creation
---
(Character-making,
Scene-making,
Story-making)
Clients typically engage in developing characters, scenes and stories, using a variety of expressive materials, and the therapist usually observe them during the entire process. |  • Facilitating nonverbal communication; • Allowing for energy release; • Building a safe space; • Facilitates projecting one’s feelings.
Storytelling and Reflection |  The therapist discusses the artworks with the clients, and allows the clients to tell stories through performances and narratives etc. Meanwhile, the therapist also ask various questions. |  • Fostering connection between life and story; • Exploring their creativity; • Facilitating their self-reflection.

Upon being introduced to the image-based generative AI tools, the therapists
envisaged their possible integration into the family expressive arts therapy.
They believed that AI holds great potential if it can blend into, instead of
replacing physical materials. Namely, they considered that AI might lower the
creative threshold for families. And the rich variations of AI-generated
images might enrich families’ nonverbal expressions of ideas and feelings. AI
might be combined with different materials, such as using family-created
artifacts as prompts for AI and using AI-generated images as elements for
collage-making. These inputs from the therapists valuably clarified the
current practice of family expressive arts therapy and were instrumental in
shaping our study design.

##  4\. Methods

Our research objective is to explore how parents and children engage in AI-
infused multimaterial storymaking for expressive arts therapy (RQ1), how
generative AI can be leveraged as expressive materials in this context (RQ2),
and gather implications about how to support children, parents, and therapists
in family expressive arts therapy (RQ3). Therefore, we conducted five weeks of
AI-infused, multimaterial therapeutic storymaking sessions with seven families
guided by a professional therapist, T1 (see Table 3). These sessions were
based on T1’s existing practice as introduced above.

###  4.1. Family Recruitment

To recruit family groups, the therapist distributed digital recruitment flyers
through her client channels. In addition, the research team also distributed
the flyers through social networks. The recruitment flyer outlined our
activity’s aim as facilitating parent-child communication and strengthening
their relationship. This aligns with the predominant needs expressed by the
therapist’s clients and the overarching objective of family-centered
expressive arts therapies, as noted in (Kerr, 2011). The flyer described the
activity as “collaboratively crafting stories with your children using a suite
of engaging digital software”, without mentioning the incorporation of
generative AI. Parents informed their children based on same information.
Finally, we recruited 7 family groups, comprising a total of 18 participants
(8 were children aged 4-7, 7 were mothers, and 3 were fathers). Table 2 shows
the specific participant demographics of the 18 participants from 7 family
groups, all families were from the city of ShenZhen. Our protocol received
approval from the institutional research ethics board, and all names mentioned
in this paper have been replaced with pseudonyms. Also, before participating
in the activity, participants diligently read and acknowledged the informed
consent form by appending their signatures. All families willingly took part
in without compensation; the therapist was compensated with her regular hourly
rate.

Table 2. Demographics of Participant Families: Family Number indicates the specific family to which the participant belongs. ID | Family Number | Role | Gender | Age | Educational Level
---|---|---|---|---|---
P1 | F1 | Mother | F | 38 | Bachelor
P2 | F1 | Daughter | F | 6 | Pre-school
P3 | F2 | Mother | F | 40 | Master
P4 | F2 | Son | M | 7 | Primary
P5 | F3 | Mother | F | 40 | Bachelor
P6 | F3 | Father | M | 42 | Bachelor
P7 | F3 | Daughter | F | 7 | Primary
P8 | F3 | Son | M | 4 | Pre-school
P9 | F4 | Mother | F | 35 | Master
P10 | F4 | Daughter | F | 6 | Pre-school
P11 | F5 | Mother | F | 34 | Master
P12 | F5 | Father | M | 35 | Master
P13 | F5 | Son | M | 5 | Pre-school
P14 | F6 | Mother | F | 45 | Master
P15 | F6 | Father | M | 48 | Doctor
P16 | F6 | Son | M | 6 | Pre-school
P17 | F7 | Mother | F | 39 | Doctor
P18 | F7 | Son | M | 7 | Primary

###  4.2. Materials and Procedure

####  4.2.1. Materials

A multitude of materials can afford diverse expressive properties to promote
clients’ expression through making (Lazar et al., 2018). Thus, we introduced a
diverse array of physical expressive materials, including colored pencils,
colored markers, paint sticks, clay, non-woven fabric, yarn, drawing paper,
and LEGO ® classic (see Figure 5 c). Meanwhile, we encouraged children and
their parents to bring children’s favorite toys to our activities and
incorporate these toys into their own stories, thereby imbuing their creative
expressions with a personalized touch.

In addition to physical expressive materials, we introduced one of the most
popular image-generative AI tools, Midjourney (Midjourney, [n.d.]), as a
research probe due to several advantages: (1) customization and easy-to-use:
it provides a broad range of customization features and a highly user-friendly
interface (Portakal, [n.d.]). (2) speed and efficiency: it quickly generates
diverse high-quality images without prolonged prompt setup (Portakal, [n.d.]).
In our study, we primarily utilized visual arts co-created by family members
through the manipulation of physical materials as image prompts for generating
AI images. Additionally, we enabled parents, children, and the therapist to
employ their own verbal descriptions as text prompts. The incorporation of
both verbal and non-verbal forms holds significant importance in the context
of expressive arts therapy (Malchiodi, 2003).

In order to quickly generate AI images during the activities, we prepared the
Midjourney prompt guidelines based on our study in advance. We referred to
(Pathak, [n.d.]) for guidelines on Midjourney prompt writing. For character
and object generation, we use “image URLs + subjects + descriptors of subjects
+ style descriptors + white background + parameters (aspect ratio: 3:2)”; for
scene generation, we use “image URLs + subjects + descriptors of subjects +
style descriptors + parameters (aspect ratio: 16:9)”. Examples of the specific
prompt guidelines can be found in APPENDIX.

####  4.2.2. Procedure

Between April and July 2023, each family participated in five storymaking
sessions guided by T1. Before the activities, the therapist conversed with
families to gain insights into the needs and goals of families (serving as the
Preparation phase in Table 1). These sessions, each an hour long, were spaced
at least a week apart. This grants the time necessary for the therapeutic
intervention to unfold and also enables us to gather participants’ insights
over an extended period. While the significance of long-term therapeutic
approach is underscored in research (Greenwood et al., 2007), it is
infrequently accommodated in HCI studies. Figure 4 a shows the participation
of each family in the five sessions.

Figure 3. Illustration of how families combined analog materials and
generative AI in their creative process.

This figure shows the AI-infused multimaterial storymaking study process. From
the left we can see parents and children took the lead in the creative process
through physical art-making, such as Lego or their own toys, and verbal
communication. The researcher helped the family document the artifacts they
co-created into photos, and used them as input images for generative AI. The
family’s verbal articulation about their artifacts was used as text prompts.
Four images were generated each time, and the family could choose the one they
preferred, or provide the researcher with feedback for content or style
adjustments to create more variations. They could also modify their artifact
or iterate their verbal articulation as updated AI inputs for regeneration.
Such (re-)generation cycles could run many times to grant families flexibility
and autonomy in exploring abundant variations until they identify the most
suitable visual expression in terms of both content and art style.

During each session, in addition to the therapist and the family, a researcher
was providing technical support, including operating the generative AI.
Primarily, parents and children took the lead in the creative process through
physical art-making and verbal communication, as Figure 3 shows. The
researcher helped the family document the artifacts they co-created into
photos, and used them as input images for generative AI. The family’s verbal
articulation about their artifacts was used as text prompts. Four images were
generated each time, and the family could choose the one they preferred, or
provide the researcher with feedback for content or style adjustments to
create more variations. A tablet was provided to the family to view and select
generated images on the spot. They could also modify their artifact or iterate
their verbal articulation as updated AI inputs for regeneration. Such
(re-)generation cycles could run many times to grant families flexibility and
autonomy in exploring abundant variations until they identify the most
suitable visual expression in terms of both content and art style.

AI-generated images were employed as intermediate expressive materials,
instead of final products, as shown in Figure 3. With the researcher’s help,
these AI images were materialized into printed scenes, character paper
cutouts, and physical tokens for further co-creation. Families could then
combine these materialized AI generations with other analog materials for
further AI-infused multimaterial storymaking both within and beyond the
therapy sessions.

The therapist’s role concerns facilitating family co-creation and encouraging
their verbal communication and expression. An activity framework was planned
based on the therapist’s current practice to aid parents and children in their
developmental journey (see Figure 5 a). These activities, as described below,
were distributed in varying proportions throughout the five sessions and were
not conducted in a strict sequential order:

Character Making. In this activity, the expressive arts therapist could guide
parents and children to try different physical expressive materials or use own
toys to create story characters that might help to project their thoughts and
feelings through personal metaphor (Perrow, 2008). Once they were created, the
researcher employed a mobile phone to take photos, which were subsequently
uploaded to Midjourney following image pre-processing. Subsequently, AI-
generated images were created based on the verbal descriptions provided by the
family members or the therapist. Then, parents and children could choose
desirable images from four variations. Finally, the therapist also encouraged
family members to name the characters, which was a strong assertion of one’s
presence and agency (David-Weill, 2020).

Scene/Object Making. In this activity, children and parents could make
stories’ objects and scenes by drawing, building Lego, kneading clay, and
collaging according to their own interests. The therapist guided family
members to infuse their personal life experiences into the fabric of the
story’s scenes and objects, thereby offering insight into various aspects of
one’s life and outlook.

Story Making and Storytelling. In this activity, parents and children co-
created story plots. According to a construction model for therapeutic story
(Perrow, 2008) following a three-part framework of ‘metaphor’, ‘journey’ and
‘resolution’, family members facilitated by the therapist created their own
story plots through collages and narratives. This activity maintained a
relatively open structure, leaving abundant space for creativity, and thus
children and parents are encouraged to take a proactive role in this activity.

Story Sharing and Reflection. In this activity, parents and children shared
their own storybooks created by the generative AI tool, and the therapist
could engage in parent-child discussions by asking questions to facilitate
their reflection.

####  4.2.3. Backstage Preparation

Throughout the entire process, our researchers undertook backstage
preparations for the sessions. First, retouching tools were employed to
perform tasks such as cutting out, mirroring, and refining characters and
objects. These characters and objects were then arranged in diverse sizes on
A4 paper and subsequently printed (see Figure 5 b (6)). Also, AI-generated
scene images were printed after a session. These paper cutouts of AI generated
content were employed as expressive materials in the next session. In order to
probe the continued, real-life impact of storymaking artifacts outside the
therapeutic sessions, we offered family-created, AI-generated character tokens
for children to take home after the sessions (see Figure 5 b (7)). Finally,
following the handmade multimaterial storybook frames and finalized storylines
co-created by the families in the sessions, our researchers and the therapist
used retouching tools to organize and arrange digital storybooks. These were
later printed out for each family. The examples of the storybooks are detailed
in APPENDIX.

Figure 4. Participation status of family members in 7 groups of families

Figure 4 shows participation status of family members in 7 groups of
families.The activity comprises seven distinct family groups, each
participating in a series of five-week sessions. Family 1 consists of a mother
and daughter, Family 2 involves the current son, Family 3 includes both
parents along with a son and daughter, Family 4 comprises a mother and
daughter, Family 5 consists of a mother, father, and son, Family 6 comprises a
mother, father, and son, and Family 7 involves a mother and son.

Figure 5. Study setup: (a) overview of the four activities; (b) diverse
expressive materials (1-5: LEGO, colored clay, painting mediums, yarn, non-
woven fabric; 6: paper cutouts of AI; 7: character tokens); (c) activity
participants(mother: left, children and therapist: right).

Figure 5 shows three pictures. The leftmost picture shows an overview of the
four activities, including character making, scene/object making,
storytelling/storymaking, sharing and reflection; the middle picture shows
diversity physical materials and AI generated materials. These include 1-5:
LEGO, colored clay, painting mediums, yarn, non-woven fabric; 6: paper cutouts
of AI; 7: character tokens; the rightmost picture shows activity participants
(mother: left, children and therapist: right ), mother and child are telling
stories using AI-generated paper cutouts.

####  4.2.4. Data Collection and Data Analysis

All sessions were audio- and video-recorded. At the end of each session, we
conducted a 5-minute interview, mainly to collect the experiences of parents
and children about the session. After the third session, an intermediate
interview planned for thirty minutes was conducted with each family to collect
their feedback and experiences halfway through the study. Upon concluding all
the sessions, we held a one-hour final interview with each family, in which
the outcome artifacts from all five sessions, including analog artworks and
AI-generated images, were used as stimuli. We also encouraged the families to
send us images and comments via instant messaging applications to share their
additional thoughts or how they engaged with the storymaking artifacts outside
the sessions. At the end of the intermediate and final interviews, we invited
the therapist to join the discussion to share her observations and
suggestions.

Our analytical focus was on the interactions between families and AI-infused
multimaterials and their therapeutic meanings of AI. All the interview data
were transcribed verbatim. Following a thematic analysis approach (Braun and
Clarke, 2006), two researchers conducted collaborative inductive coding. They
initially annotated the transcript to identify relevant quotes, key concepts,
and preliminary patterns in the data. These findings were further developed
through regular discussions, leading to a detailed coding scheme aligned with
the research objectives. Quotes were then coded and clustered into a hierarchy
of emerging themes, continually reviewed, and refined in recurrent meetings,
where exemplar quotes were also selected for presenting each theme and sub-
theme.

Alongside this, the team reviewed and annotated the session videos, keeping
both the research questions and the thematic analysis in perspective. We
collected the video segments that could act as evidence or exemplars for the
thematic analysis results, especially those highlighting behaviors of interest
among children, parents, and therapists. In addition, we supplemented our
analysis with photographic documentation of family-created storymaking
artifacts from the sessions, and utilized relevant expressive arts therapy
theories to deepen our insights into the data.

To further enrich our data interpretation with broader therapeutic insights,
we conducted a two-hour expert review session with four therapists (T1-T4; T1
directed all storymaking sessions) whose demographics and expertise are
detailed in Table 3. We provided a comprehensive presentation with images of
both the artifacts and the process of the activities. Representative video
clips from our analysis were also showcased. Therapists were prompted to pose
questions and offer commentary to both researchers and to each other. The
discourse was primarily anchored around our research questions. In line with
our earlier approach, we employed the thematic analysis method, as referenced
in (Braun and Clarke, 2006), to dissect the therapists’ commentaries.

Table 3. Demographics of Participant Therapists: Experience refers to the number of years engaged in expressive arts therapy; The Number of Case refers to cases related to family therapy ID | Age | Gender | Experience | Education Level | Major | The Number of Case
---|---|---|---|---|---|---
T1 | 48 | F | 5 | Master | Expressive Arts Therapy | 57
T2 | 32 | F | 7 | Master | Art Psychotherapy | 100+
T3 | 39 | F | 9 | PhD | Art Therapy | 100+
T4 | 33 | F | 4 | Master | Expressive Arts Therapy | 50+

##  5\. Findings

###  5.1. Outcomes and Process of Family Engagement in AI-infused
Multimaterial Storymaking (RQ1)

In this section, we offer an overview of how the children and parents engaged
in storymaking-based expressive arts therapy combining generative AI and
analog materials RQ1. This overview helps us contextualize the creative
process of the families and the therapeutic meaning behind it. As illustrated
in Figure 6, their journey has been structured in four major activities:

Figure 6. Outcomes and process of family engagement in AI-infused
multimaterial storymaking in four major activities.

Figure 1 portrays a family employing a palette of vibrant colors, specifically
blue and green, to craft an eight-legged blue-ringed octopus on paper.
Simultaneously, an AI-generated cartoon image emerges, featuring a one-eyed
rendition of the captivating creature. In Figure 2, a child’s artistic
expression unfolds as spontaneous brushstrokes and formalized lines converge
to give life to a regal purple Transformers. AI generated a cartoon purple
Transformers, harmonizing with the child’s imaginative strokes. In Figure 3, a
child explores the realm of colorful structures, utilizing playful hues such
as red, blue, yellow, and black. The juxtaposition of a snail adorned with
blue headphones, alongside its AI-generated counterpart with oversized eyes
and matching headphones, showcases the embodiment of a childlike aesthetic.
Figure 4 captures the child’s uninhibited use of differently colored clay(a
hedgehog bedecked with a yellow rope knot.). Figure 5 features a green
watermelon-shaped toy car, mirrored by an AI-generated image that seamlessly
complements the child’s creation. Figure 6 presents a menacing green dinosaur,
mouth agape, brought to life through AI wizardry. Figure 7 unfolds a
delightful scene where children, through collage, express the joyous tapestry
of their kindergarten life. The children used soft pastel-colored non-woven
fabric to make the scene of the kindergarten which placed two symmetrical
trees at the entrance of the kindergarten. Different AI-generated characters
of paper cutout are neatly arranged together. In Figure 8, a child utilized
collage to depict a blue-ringed octopus dwelling in the profound, shadowy
depths of an oceanic cave surrounded by vibrant seaweed. Figure 9 employs dark
tones and scenes to evoke a profound emotional resonance, depicting blue
clouds, pouring rain, yellow trucks, and black roads—a visual testament to
heavy, depressing, or gloomy feelings. Figure 10 showcases a child’s artistry
with an eclectic blend of colors, fashioning a symmetrical and balanced Lego
castle and clay park. Figure 13 shows a child telling a story to his parents.
He uses artificial intelligence paper cutouts and blue cardboard to
immersively tell stories that happen under the sea. Figure 14 shows two
siblings sharing their own stories with each other. Figure 15 shows the child
happily playing with the Transformers he brought from home and the character
tokens generated by AI and improvising the story. Figure 16 presents a role-
playing activity which a child, aided by AI-generated character cutouts,
engages in role-playing with their mother, placing the character cutout on
their forehead. Figure 16 shows that the daughter and mother were playing
roles. The daughter was immersed in telling what happened in the story by
placing the AI-generated paper cutout on her forehead. Figure 17 shows
children using body performance to tell stories about Godzilla and
Transformers with their parents. Figures 18 and 19 depict heartwarming moments
through sharing physical storybooks with their father in their home. In Figure
20, a child is depicted integrating AI-generated character tokens with
personal toys at home, facilitating interactions between the AI-generated
characters and their toys. Figures 21 and 22 illustrate the imaginative
prowess of children as they craft analogous characters from colored clay
inspired by AI-generated character tokens. Moving forward to Figures 23 and
24, these snapshots capture the creative journey of children meticulously
crafting their own storybooks using a blend of artificial intelligence
materials and traditional art supplies. This process serves as a meaningful
connection between their past and future energies through the medium of
artistic creation.

Character Making. Most children and parents used drawing or clay-kneading
combined with the generative AI to create their characters (see Figure 6 1, 2,
3 and 4). Some children also incorporated their toys as story characters,
echoing the idea of externalized metaphors (Perrow, 2008). For example, P8
used a dinosaur toy as an obstacle metaphor (see Figure 6 6). At the same
time, certain story characters could project children’s emotional and inner
thoughts: “[…] a consistent character […] could be regarded as a projection of
the child’s own self […] For the child, the primary focus is on how they
project these characters into their own stories (T3)”.

Scene or Object Making. Besides drawing (see Figure 6 9 and 10), LEGO
®-building (see Figure 6 11), and clay-kneading (see Figure 6 12), children
made their own scenes by mixing the paper cutouts of AI-images with physical
materials (wool, colored clay or non-woven fabric). For instance, P10 mixed
the AI-image cutouts with non-woven fabric to make collages, which emerged as
a common way for scene-making across families ( Figure 6 7). In constructing
scenes/objects, most children added their experienced real-life scenarios,
such as hospitals or kinder gardens into the image-prompts or artifacts. As
noted by related theory (Hinz, 2019), their arrangement and structuring of
scenes could reflect their emotional experiences from those scenarios.

Storymaking and Storytelling. As an emerging creative example, P13 created
stories using a blue cardboard to represent the underwater world, on which he
moved the character cutouts of both AI images and drawings to act out his
stories on-the-spot (see Figure 6 13). Role-play was frequently used by the
therapist to promote storymaking. For example, T1 prompted P1 and P2 to
exchange their character paper cutouts, allowing them to converse and develop
the story while swapping their roles (see Figure 6 16), offering potential
benefits of perspective taking (Jennings, 2005; Ahmadpour et al., 2023). P18
created stories by playing with character tokens and personal toys (see Figure
6 15), which could enable children to communicate to self and make meaning of
their experiences (Schaefer, 2011). Finally, bodily performance was founded in
our sessions (see Figure 6 17), which has been deemed to facilitate embodied
exploration, rehearsal, and demonstration of story ideas or creative slotuions
(Jones, 1991).

Sharing and Reflection. Besides reading and discussing their storybooks during
the sessions, children also shared, developed, and re-narrated their stories
outside or after the sessions. Namely, many children reviewed their storybooks
with family members at home (see Figure 6 18 and 19); P13 proudly shared his
storybook and making process in a kindergarten weekly sharing session (see
Figure 1 d). As P11 added: “[…] When P13 brought up the topic of AI storybooks
with fellow children, they didn’t know what he was talking about. […] But he
told his friends with pride ‘I am going to AI today!”’ Moreover, children
improvised new stories by playing with character tokens and their toys at home
and made new crafts using the tokens (see Figure 6 20, 21 and 22). Children
used AI-generated materials to continue crafting new storybooks at home (see
Figure 6 23 and 24). P10 used both paper cutouts and materials from life:
“After the Dragon Boat Festival […] I took out the paper cutouts from the
drawer and encouraged her to make a storybook about it […] I saw her cutting
these papers. Then, I told her that there was foam in the express package, and
she said that this foam could be used to make characters pop up (P9)”.

###  5.2. Examining AI-infused Material Interactions through the Lens of ETC
(RQ2)

In this section, we concretely examine how generative AI—when seen as
expressive materials used along with other analog materials—could support the
material interactions along different dimensions of the Expressive Therapies
Continuum (RQ2). Material interactions play a pivotal role in the therapeutic
outcomes and the overall experience of the clients (Lazar et al., 2018). As a
foundational theoretical framework, Expressive Therapies Continuum (ETC)
describes four dimensions along which clients interact with materials to
process information and form images from simple to complex (Hinz, 2019). We
employed ETC as a theoretical lens to examine AI-infused material interactions
concretized by our data, to inform future usage of generative AI for
expressive arts therapy (see Figure 7).

Figure 7. AI-infused material interactions from the lens of Expressive
Therapies Continuum (ETC).

Figure 1 shows the scene of children hitting the clay heavily with their hands
to make a sound, thereby achieving a cathartic effect. Figure 2 shows a child
using scissors cutting out AI printed yellow seahorse character. In Figure 3,
a child was consistently arranging boards with wood-textured surfaces,
revealing the occlusion relationship between the boards. The AI then generates
corresponding images featuring mountain peaks, drawing inspiration from the
wood-textured planks. In Figure 4, a soft, translucent toy is depicted. The AI
has generated a crystal-clear cartoon hamster character, drawing inspiration
directly from this particular toy. Figure 5 shows a combination of different
vibrant colors, rule-breaking shapes and form distortions, which evoked
children’ emotion. Figure 6 shows a huge green snake alongside a small snake
(AI cutout) with exaggerated tears to depict fear. Figure 7 shows a child
organizing the LEGO® with a high degree of form potential in a visual order
(own garage and house).In Figure 8, a child arranged a row of AI characters
within a classroom setting adorned with an abundance of yellow flowers. Figure
9 shows a scene that took place in a kindergarten. A group of AI-generated
characters were playing outdoors. Suddenly a small animal was injured. The
child employed problem-solving skills to address various injuries that arise
within her storybook. Figure 10 shows the scene that took place at the racing
track. child employed AI-printed collages to distribute banana to different
characters logically through selection, organization and calculation.Figure 11
shows the child creating a purple fish with big eyes, his own green toy and
AI-generated cartoon images, an omelette jellyfish and a yellow seahorse. They
use these characters as self-symbols.Figure 12 shows the child using handwork
and artificial intelligence to create a little rabbit character lying on a bed
full of flowers. AI helped generate a little rabbit wearing a pink skirt and a
pink bow. This little rabbit was featured in her story. Used as a self-symbol.
At the same time, this character is integrated into her real life in the form
of a symbolic physical token. Figure 13 shows a child held multiple colored
pens and let body movements guide the creation of colored traces on the paper
without specific intent, no specific shape. The child then used sensory
perception to liken them to tornadoes. Figure 14 shows the child placed
cutouts of cartoon-style houses and mountains with diving platforms in a
pleasing order atop a printed background. The child then creatively turned
this paper collage into a “stage” to hold the clay characters (a green stripe
little snake and a little purple snake) celebrating their family gathering
with joy and contentment. Figure 15 shows the baby purple snake crafted and
piloted a magical plane on a quest to help its green snake mother find a
missing diamond with wings.

Kinesthetic/Sensory Level. At the Kinesthetic/Sensory Level, the processing of
information commences at a preverbal stage (Hinz, 2019). The Kinesthetic
component encompasses the sensations that provide individuals with information
about bodily rhythms, movements, and actions (Hinz, 2019). The Sensory
component encompasses information derived from visual, auditory, and tactile
channels (Hinz, 2019). On the Kinesthetic component, we found that children
engaged in physical manipulation and handling of various materials through
movement and actions, such as pounding clay with their hands (P4, see Figure 7
1), cutting out printed AI-generated objects/characters (P13, see Figure 7 2),
moving rhythmically with acrylic standees of AI characters (P18), pushing (P2,
P4, P16), stabbing and cutting clay (P4), and cutting non-woven fabric (P2,
P10, P13). According to related theories, these activities can facilitate
individuals’ release of energy, physical arousal, and tension (Luria et al.,
2020). It also promotes relaxation for clients (Slater, 2004). As noted by P5,
the move of shaping the clay for character making (as inputs for AI) was
“quite relaxing”. On the Sensory component, we found that families engaged the
sensory qualities of various materials through tactile, visual, and auditory
elements. And they intended to bring some of the appreciated visual or
textural qualities into the AI images. For example, P4 input a board with
wooden texture (see Figure 7 3), and also P17 input what she described as a
soft, translucent texture of a toy (see Figure 7 4). According to related
theories (Lusebrink et al., 1990), these activities can enhance broader
attention to the present moment, encourage self-soothing, and express inner
sensation.

Perceptual/Affective Level. The Perceptual/Affective Level concerns
information processing and image formation either verbally or nonberbally
(Hinz, 2019). The Perceptual component features the regular arrangement,
ordering, or completion of form elements (Hinz, 2019). On the Affective
component, information processing and image formation can be mediated by
emotional or raw expressions using unbalanced proportions or vibrant colors
(Kagin and Lusebrink, 1978). On the Perceptual component, we found that family
members tended to create images through ordered arrangement, and regular
patterns using structural materials (e.g, wood, LEGO ®). For instance, P16
organized the LEGO ® bricks into a clear structure to create a building (see
Figure 7 7). Children also created regular formations of multiple characters
on their collages (P4, P10, and P16), e.g., P10 formed a row of AI characters
in the classroom scene (see Figure 7 8). Such perceptual aspects in expressive
making could increase structural awareness and foster a satisfying internal
state (Ulman, 2001; Hinz, 2019). On the side of the Affective component, we
found that some children picked vibrant or strong colors in their clay-
kneading or collages (P4, P8, P16 and P18). P8 mobilized different vibrant
colors and rule-breaking shapes in his clay artifact to reflect his joyful
state (see Figure 7 5). P7 drew a huge snake alongside a small snake (AI
cutout) with exaggerated tears to depict fear (see Figure 7 6). Such affective
aspects bring therapeutic benefits by allowing families to explore and access
emotions (Hinz, 2019).

Cognitive/Symbolic level. The Cognitive/Symbolic level is the most complex and
sophisticated, involving planning, cognitive action, and intuitive recognition
(Hinz, 2019). The Cognitive component involves deliberate planning,
logical/realistic thinking, problem-solving, and storytelling (Lusebrink,
2015). The Symbolic component involves the intuitive, mythical, and self-
relevant concept creating, and the articulate expression and resolution of
symbolic elements (Kagin and Lusebrink, 1978). On the Cognitive component, we
found that children could plan and sequence their story plots with their
parents through narratives and collages (P2, P7, P10, P13, P16, and P18). F16
employed AI-generated paper cutouts to select, organize, calculate, and
distribute food to different characters logically through the medium of
collage (see Figure 7 10). P10 utilized problem-solving skills to address the
injury of a character in her story (see Figure 7 9). These cognitive aspects
in storymaking can benefit planning, cause-and-effect thinking, and problem-
solving skills (Hinz, 2019). On the Symbolic component, we found that all
children created self-relevant characters to connect stories and individual
experiences through metaphoric symbols. For instance, P2 created a little
rabbit character using handcrafting and AI, which was used as a self-symbol in
her stories. Meanwhile, this character was incorporated into her actual life
in the form of a symbolic physical token (see Figure 7 12). Each member of
Family F5 had their own character as a self-symbol, and the tortoise toy seen
as a friend by P13 was also added into the story through AI (see Figure 7 11).
P11 mentioned that the most impressive experience was that the child made a
“purple fish” out of colored clay: “P13 said at the time that he turned into a
fish”. P11 added, “he said that the seahorse is the mother and the jellyfish
is the father”. Such symbolic aspects help children realize personal meaning
and enable parents to understand their children through personal symbols
(Kagin and Lusebrink, 1978).

Creative level. The Creative level involves innovative and resourceful
interactions with the environment and expressive materials, leading to
creative expression and self-actualizing experiences (Hinz, 2019). It can
“bring forth something new” (Hinz, 2019) within the expressive process across
all levels of ETC. Using P4 and his family as an example, at the
Kinesthetic/Sensory Level, P4 held multiple colored pens and let body
movements guide the creation of colored traces on the paper without specific
intent. P4 then used sensory perception to liken them to tornadoes (see Figure
7 13); at the Perceptual/Affective level, P4 placed cutouts of houses in a
pleasing order atop a printed background. He then creatively turned this paper
collage into a “stage” to hold the clay characters celebrating their family
gathering with joy and contentment (see Figure 7 14); at the
Cognitive/Symbolic level, during the evolution of the story, P4 crafted and
piloted a magical plane on a quest to help his mother find a missing diamond
(see Figure 7 15), unveiling both the inventive and valiant facets within P4
as noted by the therapist. Such creative moments ignited along the process
could sparkle the experience of innovating and self-actualizing (Hinz, 2019).

###  5.3. Surfacing the Therapeutic Meanings of Generative AI as Expressive
Materials (RQ2)

In this section, we aim to explicate the therapeutic meanings of generative AI
as expressive materials in family expressive arts therapy. Our findings
revealed three themes (see Table 4): (1) AI as empowerment for families; (2)
AI as connection between physical and digital, life and stories; (3) AI as co-
creator.

####  5.3.1. AI as Empowerment for Families

We found that employing AI as expressive materials holds two forms of
empowerment for family expressive arts therapy:

Lowering the Creative Threshold and Increasing Creation Efficiency. We found
that AI could lower the creative threshold by enhancing the aesthetic quality
of creation. For instance, P1 elucidated the appeal of AI-generated outcomes
that exceeded expectations, especially for children: “P2 said that the tool
was so magical, which made the rabbit so beautiful”. This helped children
boost expressive confidence and focus on creative expression rather than art-
making skills: “children may become more confident […] knowing that the
quality of their drawing didn’t matter since AI can enhance images (P17)”. T1
also explained why AI can enhance expressive confidence: “they might be less
concerned about the aesthetic perfection of their creation. This could
diminish the feeling of intimidation and heighten their engagement”.
Furthermore, AI increased families’ creation efficiency. For example, as P3
appreciates, “if I were to create an oil painting like this, it would demand a
lot of time and effort. Yet, exceptional results can be rapidly delivered just
by using two wooden blocks”. Increased efficiency could facilitate clients’
improvisation and creative tendencies (Barclay Goldstein, 1999).

Unconditionally Accepting Families’ Imagination and Affording Endless
Variations. First, AI could unconditionally accept the imaginative concepts of
families as prompts. For example, P11 noted that: “he might envision such a
scene in his mind but struggle to articulate it due to his current language
capability. Nevertheless, these images support him to imagine”. As P14
experienced, “I can’t turn the things in my head into a specific look that I
want, but AI can help.” Similarly, to P1, “the images here feel directly
generated from what I imagined […] which is quite magical.” Such unconditional
embracing of families’ imaginations could foster their creative self-
expression, and psychological self-healing and renewal (McNiff, 1992).

Second, AI can provide endless variations and hence offer families abundant
expressive possibilities: “AI presents many options but they all fall under a
specific category (P3)”. When facing the varying options generated by AI, some
children: “engaged in discussions with their parents to make joint choices […]
This revealed the interaction between parents and children during this
selection process (T1)”. In addition to rich options, P17 mentioned that AI
might create surprises when merged with traditional materials: “manipulating
colored clay or constructing with Lego can be even more unpredictable,
yielding unexpected surprises. What you end up with might not exactly match
your initial concepts, that’s perfectly acceptable”. The rich creative
possibilities are deemed as empowerment to exploration (Brändle et al., 2023).

Table 4. Summary of the Therapeutic Meanings of Generative AI as Expressive Materials. Themes |  Description |  Example Quotes
---|---|---
AI as Empowerment for Families |  Lowering the creative threshold and increasing creation efficiency; |  “children may become more confident […] knowing that the quality of their drawing didn’t matter since AI can enhance images (P17)”;
Unconditionally accepting families’ imagination and affording endless variations. |  “I can’t turn the things in my head into a specific look that I want, but AI can help (P14)”.
AI as the Connection between Physical and Digital, Life and Stories |  Fusing and harmonizing analog and digital artifacts; |  “once I created an artifact, and P4 crafted another, it allowed us to combine both creations into a unified image (P3)”;
Generating symbols that can permeate life and stories. |  “she has immersed herself in this role because […] she relates her current state to the character of the little rabbit (P1)”;
AI as Co-creator |  Family-AI mutual interpretations; |  “what fascinates me is that he not only selected the AI-image but also interpreted its unexpected part as jeweled bananas (T4)”;
Family-AI comprise and authorship. |  “initially, we probably had a preconceived notion, but when AI-generated images deviated from our expectations, we found this variation to be acceptable (P17)”; “AI provided several images and allowed them to choose one that closely mirrored their own creation. This may be considered as respecting their ideas (P5)”.

####  5.3.2. AI as Connection between Physical and Digital, Life and Stories.

In this study, we found that AI as expressive materials can foster the
connection between the physical and digital world, as well as real life and
stories, in twofold meanings:

Fusing and Harmonizing Analog and Digital Artifacts. First, through generative
AI, artifacts made by children and parents with various physical materials
could be merged into one scene: “once I created an artifact, and P4 crafted
another, it allowed us to combine both creations into a unified image (P3)”.
The therapeutic meaning of AI lies in its ability to “harmonize the style of
images. For instance, we can combine crayons and colored pencils to create
together, achieving a seamless integration (T2)”. AI images were never
intended as end products in our sessions. Therapists pinpointed that AI could
“shuttle”back and forth between the physical and the digital world. Physical
artifacts can be blended into the digital world through AI generation;
meanwhile, AI-generated images were also used as materials in physical
artmaking: “The AI-generated images were not necessarily final outcomes, and
they could be brought to the 3D physical world for a new round of creating
(T4)”. Thus, it could foster the continuity of their human creations:
“children can witness that their artworks have different dimensions. AI can
make these artworks reused and then recreated repeatedly. I personally think
it is very attractive (T2)”.

Generating Symbols that Can Permeate Life and Stories. First, as presented
earlier, AI helped children integrate personal relevance into their own
stories, such as their family members and toys. For instance, as believed by
P17, the toys brought into the story by generative AI, would increase
children’s connection with the story: “he loves toys very much. When these
toys were integrated into his stories, he might perceive them differently
[…]”. Children might use personal toys to represent their inner world and
external experiences symbolically (Harvey, 1990). Second, generative AI helped
children construct self-symbols in their stories: “she has immersed herself in
this role because […] she relates her current state to the character of the
little rabbit (P1)”. The therapist explained that self-symbols can help
children and parents observe and reflect on their inner qualities: “P1 should
utilize the ‘little rabbit’ in new stories to probe the child’s life
experiences or create new challenges in the stories to amplify her
adaptability and other strengths (T1)”.

On the other hand, the therapists pinpointed that the physical embodiment of
AI-generated symbols, such as paper cutouts or character tokens, might serve
as transitional objects. Transitional objects are typically considered as an
item a child is strongly attached to in life (Winnicott et al., 1951). T4
clarified the definition of transitional objects in the context of expressive
arts therapy: “when clients leave the therapy studio, they can take their
creations, which helps them reflect back on their experience. It bridges the
gap between the therapeutic environment and the real world, enhancing the
transfer of therapeutic benefits and personal growth into their everyday
lives”. As an example from our participants, P17 reported the character tokens
became part of P18’s play routines: “he used those standees as his toys and
played along with other toys”. This suggests that materialized AI generations
have the potential to be transitional objects, which are believed to offer a
sense of comfort, security, and emotional support to a child (Winnicott et
al., 1951).

####  5.3.3. AI as Co-creator.

We found that generative AI, as agential materials, were not only used by
families but also “collaborated” with them, as surfaced by two aspects:

Family-AI Mutual Interpretations. First, generative AI, by nature, interprets
human input (prompts) to generate outcomes. P3 was amazed by how AI had
interpreted some highly abstract inputs: “P2 made a pile of mud and put it
there, and AI could even create specific characters, which was quite
impressive.” Reversely, we found how AI generations served as inputs to
families, prompting their creative interpretations. Commenting on P16’s case,
T4 pointed out how a meaning-making process emerged in such interpretation:
“what fascinates me is that he not only selected the AI-image but also
interpreted its unexpected part as “jeweled bananas”. He was deeply involved
in meaning-making […] I’d consider that moment to be highly significant.” The
families’ creative interpretation of AI was incorporated into their artmaking
process: “I may be able to re-create stories directly based on the AI-
generated images, which was quite interesting […] For example, I didn’t make
trees initially, but when I saw the trees generated by AI, I was inspired to
integrate this idea (P3).” Such mutual interpretations reflect a back-and-
forth conversation between the family and the generative AI tool to
collaboratively shape the creative process and outcomes.

Family-AI Compromise and Authorship. Interestingly, when the AI-generated
images did not appear to align with the family-created input, most children
would work with the AI’s outcomes. For example, P17 explained that:
“initially, we probably had a preconceived notion, but when AI-generated
images deviated from our expectations, we found this variation to be
acceptable. ”. The compromise might mean that children can embrace the
imperfections of AI-generated images: “when it comes to children, one point we
may need to pay attention to is why the children think the artifacts are not
perfect, and then how the children can accept this imperfection and still live
with the artifacts. I think this is a relatively subtle part (T2)”. Such
compromise might foster a sense of acceptance and self-compassion (Dreikurs,
1959).

Human-AI authorship is crucial within the context of expressive arts therapy.
T4 employed the connection between the creator and the creation in expressive
arts therapy to stress its significance: “I find myself intrigued by the
dynamics of authorship between the creator and the AI-generated images. In
expressive arts therapy, a client creates a drawing, and regardless of its
aesthetic appeal, they often say, ‘this is my artwork’. However, when AI
generates an image that they find beautiful, will they similarly claim
authorship with confidence, ‘this is my creation,’ when sharing it with
others?”. In our study, many parents mentioned that children thought they made
the story themselves: “she created this story herself, and she also came up
with this character (P1)”. P5 explained that providing more choices can help
establish human-AI authorship: “AI provided several images and allowed them to
choose one that closely mirrored their own creation. This may be considered as
respecting their ideas”.

##  6\. Discussion

###  6.1. Generalizing Desirable Interaction Qualities for Children, Parents,
and Therapists in Therapeutic Storymaking (RQ3)

Few HCI studies focused on storymaking-based expressive arts therapy in the
context of family. Therefore, one of our research objectives is to
contextually understand how to support families and therapists in this
context. Based on our empirical findings, we discuss and generalize the
desirable interaction qualities (Höök and Löwgren, 2012; Wakkary et al.,
2016), to aid future research and practice in similar domains (Höök and
Löwgren, 2012; Wakkary et al., 2016). Summary of the desirable interaction
qualities can be found in APPENDIX.

####  6.1.1. Desirable Qualities for Children

Four interaction qualities can be distilled to support children:

Diverse Materials for Creative Exploration and Expression. As related to the
Kinetic/Sensory level of ETC, offering diverse materials can benefit
children’s self-regulation and motor skills: e.g., cutting out paper or
manipulating clay in Figure 7 1 2). ETC argues for the significant therapeutic
value of (analog) material interactions (Hinz, 2019), which cannot be easily
replaced by digital interaction. Embodied interaction with rich materials
could also enrich children’s non-verbal expression. Materials serve as a
medium for emotional expression for children who may not express their
feelings through verbal communication (Wikström, 2005). Most importantly, our
data showed combining analog materials with AI materials promised huge
creative empowerment for children. The rich artifacts in Figure 7 concretize
how AI-infused multimateriality facilitated their expressing of feelings and
self-actualization (Manheim, 1998), which are the core therapeutic values for
children.

Personal Relevance. Personal relevance is an essential quality for children’s
engagement. We found that many children tended to identify themselves or their
family members as story characters in their family stories (e.g, Figure 7 11).
These characters are the symbolic instruments for children to project inner
emotional states and externalize inner conflicts through stories (Jennings,
2005). Children’s personal toys were also integrated into their stories,
potentially serving as comforting and empowering tools for self-expression and
their emotional connection to their stories (Kottman, 2014).

Sense of Accomplishment. The sense of accomplishment came from artifacts co-
created with AI which exceeded children’s expectations. The process of
crafting physical artifacts for AI input and choosing from AI-generated
variations encouraged children to assert ownership, feeling as if the
creations were their own rather than the AI’s. Moreover, the sense of
accomplishment also came from that children could share their own storybooks
with family members or their peers (e.g., Figure 1 d). Such family sharing
enhances the sense of family togetherness and unity, benefiting children’s
growth and learning (Christensen et al., 2019).

Renarration and Recreation beyond the Therapeutic Sessions. In our study, many
children took the AI-generated materials home and continued making new stories
at home (e.g, Figure 6 24). They utilized not only the paper cutouts but also
physical materials from daily life (e.g., Figure 6 23). This suggests a
valuable quality of our activities that helped break down the boundaries
between the therapeutic environment and real life. This encourages continued
creative self-explorations and self-expression to take place after the
therapeutic interventions (Panjwani, 2017).

####  6.1.2. Desirable Qualities for Parents

Three qualities were discovered to support parents, which can be further
amplified by future HCI systems:

Discovering New Aspects of Children. First, many parents appreciated that the
artifacts and process of their family storymaking helped uncover children’s
demands for parents. Through interacting with or through story characters
symbolizing the family members, parents could gain insights into how children
view these relationships and the dynamics at play (Kwiatkowska, 1967).

Also, parents discovered children’s less noticeable life experiences through
connecting stories and life (e.g, P10’s kindergarten experiences, see Figure 6
7). Storytelling is a powerful tool to help parents make sense of children’s
life experiences and identities (Rubegni et al., 2019). Finally, parents
uncovered their children’s strengths through making stories. For example, P3
was surprised to recognize the heroic valiant characteristic within P4 (see
Figure 7 15). As T1 suggests, parents could thoughtfully create new stories
with children to continue reinforcing these observed strengths.

Reflection in Therapeutic Storymaking. We found that during the storymaking,
some parents meaningfully reflected on their roles and their family
interactions in the past. Two parents became aware of their dominant
supervisory role during the activities. Such reflection can improve their
family roles and family flexibility (Olson, 2000). Additionally, some parents
realized they tended to focus excessively on the intricacy of the storylines
crafted by children. After discussions with the therapist, a few parents noted
they should learn to appreciate the rawness or genuineness of the stories,
which align with their children’s age and lived experiences.

Storymaking as Family Meaning Co-constructing. Several parents mentioned that
the storybooks co-created with their children could become part of their
family memory archive (see Figure 6 18). As T1 envisioned, if storymaking
becomes a family ritual over an extended period, parents would be able to
“witness the growth of children (T1)” over time, and these stories can
“reflect what the children care about at the moment (T1)” by compiling a
series of family stories just like a family photo album. In our study, several
families indeed used paper cutouts or character tokens of AI-generations at
home for making new stories. This suggests the potential value of promoting
family interaction (Christensen et al., 2019) and the sense of togetherness
(Wajskop and Peterson, 2015) when storymaking can become a family ritual.

####  6.1.3. Desirable Qualities for Therapists

Three interaction qualities are desirable when supporting therapists:

Observing the Strengths and Challenges of Children and Families. Therapists
constantly try to observe the strengths of the children via storymaking
activities, and utilize specific techniques to reveal these strengths to both
children themselves and their parents while steering the process. According to
positive psychotherapy theory (Rashid, 2015), such a strength-based approach
can enable therapists to identify and capitalize on children’s strengths,
granting resources for children to face the challenges in life. Therapists
also try to gain insights into family interaction dynamics and their
challenges in communication and relationship through the process and outcome
artifacts of the family’s joint storymaking (Kerr, 2011). For example, P13
explicitly projected himself, his mother, and his father to a purple fish, a
seahorse, and a jellyfish. His story offered T1 insights into their family
dynamics: “when the purple fish felt cold, he went to the seahorse. The
jellyfish does not have a home […] He simply drifts along (T1)”. T1 thereby
confirms the child’s strong attachment to the mother and the sense of
disconnection of the father due to the father’s limited availability for
family. Also, T2 identified family interaction issues by observing a mother’s
frowning responses to the artifacts her child presented.

Moderating Family Communication through Storymaking. First, therapists often
need to facilitate communication through role-playing. During the activity, T1
encouraged the family members to name the characters and play the story
characters created by themselves to express their inner thoughts. For example,
T1 facilitated P1 and P2 to take on their created characters to communicate in
the playground scene (see Figure 6 16). Children might express their thoughts
more comfortably through role-playing, leading to open and honest
conversations (Ahmadpour et al., 2023; Matthews et al., 2014). Further,
therapists commonly need to initiate perspective-taking plays to enhance
mutual understanding among family members. T1 encouraged the child to take on
the role of the elephant mother created by his mother to act out what the
angry elephant mother would say to the baby elephant using AI-image cutouts
during the activities. Facilitating perspective-taking can help families
overcome egocentric tendencies, promote mutual understanding, and foster
empathy (Corsini, 2017).

Offering Families a Playful and Safe Space. Therapists have a substantial need
to afford a playful space for family storymaking. Family storymaking is “a
process of play (T3)”, and play “allows us to better release our personality
so that we can be ourselves (T3)”, which is similar to previous research
findings (Hubbard et al., 2021). We found that the therapist intended to offer
diverse playful creative tasks from crafting to dramatic play. Children
enjoyed playing and performing using character tokens, personal toys, or body
movement (see Figure 6 15 and 17). Also, T1 could help parents return to a
child-like mindset by providing diverse analog materials (see Figure 1 e). For
instance, P5 noted that despite she bought clay for her child before, she had
never used it herself; and during the session, she was impressed by how
relaxed she felt when interacting with it. And her relaxation also positively
influenced her child’s emotional state. Further, therapists value the
importance of affording a safe space where participants feel comfortable while
engaging in the creative process and expressing their thoughts (Lazar et al.,
2018). In our study, a safe space was interpreted as “a loving environment
(P3)”, where a child can feel that “everyone accepted him and encouraged him
to express himself freely without concerns (P3)”.

###  6.2. Design Implications (RQ3)

Besides the desirable interaction qualities, we also formulate a set of design
implications with the purpose of inspiring future HCI systems targeting AI-
infused, multimaterial storymaking for family expressive arts therapy (RQ3).

Implication 1: Supporting Materialization of Generative AI in Family-AI
Engagement. The diverse range of examples gathered through the four levels of
ETC illustrates that children combined diverse analog materials and AI
materials to craft stories. Prior research has shown that AI might wield
significant influence at higher-level components, such as affective (Wang et
al., 2023) or cognitive components (Han and Cai, 2023). However, our study,
applying Expressive Therapies Continuum (ETC), revealed new insights into
family-AI interaction design, applicable beyond therapy contexts. For
instance, it has been revealed that by enabling physicalization or
materialization of AI-generated contents, we could enrich the sensorial and
kinesthetic qualities of family-AI interactions, which could not only aid
children’s motor-sensory skills but also induce mental soothing effects
(Lusebrink et al., 1990) and positive parental involvement (Yu et al., 2021).
Moreover, looking through the creative dimension of ETC, we found that such
materialization of AI generated contents could boost families’ creative
potential by allowing them to combine analog materials with AI materials in
physical artmaking activities. These insights could be leveraged beyond the
expressive therapy context to a broader range of applications which means to
support comforting and enjoyable family-AI co-creative tasks, through
tangible, embodied, or mixed reality interfaces.

Utilizing a therapeutic perspective, we also uncovered for the HCI community
how tangible character tokens created in family-AI storymaking can act as
transitional objects (Winnicott et al., 1951). These objects can offer
children continued companionship beyond the creative activity, holding the
potential to aid children’s self-empowerment journey in everyday life. This
could inspire future child-AI systems beyond the therapy contexts to leverage
the developmental benefits of child-AI co-created characters as both digital
transitional objects (Koles and Nagy, 2016), and physical transitional
objects, for example, embodied by customized tangible toys, robotic systems
(Luria et al., 2020), or wearable companions (Özcan et al., 2016), in order to
more ubiquitously grant children with emotional and developmental support in
daily surroundings (Luria et al., 2020).

Implication 2: Supporting Constructing Self-symbols for, and with Children. In
our study, we emphasized the paramount importance of crafting story characters
using AI that are intricately connected to the concept of self-symbols (e.g,
Figure 7 11). The AI-generated images of characters were based upon the
children’s artifacts or toys, and they were strongly appreciated for enabling
high-quality, coherent characters that were seamlessly blended into diverse
story scenes with a harmonious presence. These characters were found to be
used as children’s self-symbols or projections of family members, which can
help children authentically reflect in the stories on the qualities inherent
to their identities (Hinz, 2019). We thereby suggested that future research
could intentionally integrate story-relevant avatars created through the
generative AI to probe children’s mental projection (Zarei et al., 2021, 2020)
in daily lives, which can help them to be better understood by their parents
and therapists. These avatars might be applied in educational games for
children to increase personal relevance or overcome mental challenges in the
learning process (Lee-Cultura et al., 2020; Koles and Nagy, 2016). Moreover,
the avatar can be designed to serve as a conversational agent, providing
companionship and fostering growth alongside children (Xu et al., 2022c,
2023a).

Implication 3: Supporting Moderation of Family Communication via Storymaking.
We found that the therapist frequently need to employ role-playing and
perspective-taking to moderate the communication within families. Engaging in
role-playing and perspective-taking can help parents and children comfortably
and empathically communicate via story characters, strengthening their
understanding of each other’s thoughts and feelings (Shuttleworth, 1980). The
future HCI design could enable interactive therapeutic systems to leverage and
augment role-playing and perspective-taking through technology-mediated
interactions. To encourage therapeutic role-playing (Matthews et al., 2014),
the system can engage with parents and children in various role-playing
scenarios using human-AI co-created story characters. To facilitate
perspective-taking, we suggest that the system encourages parents to actively
take on the role of the help-seeker while the children can take on the role of
problem-solver or caretaker, fostering children’s inner growth and parents’
empathy with children. Moreover, the system can introduce different conflict
points within the story plots where parents and children need to switch roles
of characters and make collective efforts. For instance, think of a
collaborative VR game combining storymaking and escape room, requiring parents
and children to co-create stories and play each other’s roles to proceed.

Implication 4: Supporting Family Meaning Co-constructing and Family Memory
Archiving via Storymaking. In our findings, we found that the storybooks co-
created by the families could become a meaningful part of their family memory
archive. This echoes previous research which has demonstrated that sharing
stories as well as creating stories can help to co-construct family meaning
(Jones and Ackerman, 2018; Wallbaum et al., 2018). In the future, an AI-
infused multimaterial storymaking system can be designed to intentionally
support parents and children recording, renarrating and reliving
multidimensional life experiences, such as kindergarten activities, family
traveling, or other recreational activities. Also, future work could broadly
explore meaningful forms of interactions or outcomes artifacts for family
memory archiving and revisiting, such as stop-motion animation, short videos,
mobile wallpapers, 3D photos, mementos, or interactive storybooks. Further, a
built-in online community component can facilitate the storage and exchange of
family memories related to the collaborative storymaking process, fostering
connections both within and across families and affording a platform for the
ongoing evolution of their shared narratives.

###  6.3. Limitations and Future Opportunities

There are several limitations in our study. First, generative AI might not
always produce preferred outcomes due to inherent uncertainties in AI. To
counter this, we afforded multiple cycles of generation and regeneration,
allowing families to iteratively explore different outcomes. This involved
adjusting their input images (photos of their artifacts) and verbalization
(used for text prompts) until satisfactory results were achieved, sometimes
requiring several iterations. While this highlights a limitation in current
generative AI technology, it also presents a future opportunity to enhance
user experience through HCI approaches. For example, developing a more
intuitive input interface could facilitate easier uploading and pre-processing
of image inputs and modification of text prompts. A well-designed interface
with structured prompting questions could potentially reduce the number of
iterations needed to achieve desired results. Furthermore, this limitation can
be reframed as a design opportunity to encourage family communication and
children’s expressive skills. The need for both image and verbal inputs, and
the family’s discussion around AI-generated outcomes, can be intentionally
designed to foster children’s verbal expression and family communication. This
may not only aid in expressive arts therapy but also support overall child
development and strengthen family relationships.

Another important aspect regards the safe use of generative AI. We selected
Midjourney from various available alternatives because it has a robust
mechanism for preventing the output of inappropriate, misleading, or
unsuitable content (Team, 2022). While we did not encounter unsuitable images,
there were occasional minor issues with counterfactual or unconventional
elements in the AI-generated images. For instance, a cartoon snake might be
depicted with feet. While this issue is common in current generative AI
technologies, future systems could consider incorporating additional prompts
in the back end to avoid specific types of errors, or, intentionally focusing
on generating less realistic, more cartoonish styles to avoid discomfort or
uncanny effects from photo-realistic images with errors. Interestingly, our
study also found that these counterfactual elements can spark creativity in
children. For instance, a child used an AI-generated image of a banana with
unexpected droplet-like features to invent a “diamond banana” concept in his
story. This suggests that the unpredictability of AI can sometimes be a source
of creative inspiration. However, it is crucial to recommend that future
research collaborate closely with parents, therapists, children, and other
stakeholders to ensure the safe use of generative AI with children and develop
design principles for age-appropriate generative AI interface, minimizing
potential risks while maximizing creative opportunities (Wang et al., 2022).

Here we reflect on how our study might contribute to a few ongoing
conversations in HCI. A key issue in HCI research is enabling better family
communication and relationships through emerging technologies. Our study
highlighted how family expressive arts therapy offers novel avenues for
creating family-oriented technologies. This includes integrating multiple
forms of expressive activities in HCI designs to foster playful, therapeutic
interactions between family members. Techniques widely used in family therapy,
such as role-playing (Matthews et al., 2014) or perspective-taking (Ohtaka and
Karasawa, 2019) among family members, could inspire future technology designs
for facilitating family engagement and mutual understanding. Our study also
concretized the value of family storymaking not just for children’s learning
but for preserving family memories and jointly constructing family meaning
over time (Jones and Ackerman, 2018). Additionally, we surfaced the exciting
possibilities of combining generative AI with embodied or physical interaction
experiences. Lastly, along with the emerging discussion about family
engagement with AI, our study surfaced a relevant and concrete understanding
of the needs and experiences of families using AI for creative expression.
This contributes valuable, practical design insights for future initiatives.

##  7\. Conclusion

In this study, we set out to empirically explore how to utilize image-based
generative AI as expressive materials and how to support the needs of
children, parents and therapists in the context of family expressive arts
therapy. In doing so, we collaborated with a professional therapist to conduct
five-week expressive arts therapy sessions involving 18 participants from 7
different family groups. Our findings highlighted that emerging outcomes and
process of storymaking-based expressive arts therapy combining generative AI
and analog materials. Through the lens of ETC, we characterize the therapeutic
meanings of generative AI as expressive materials. Our work contributes to a
nuanced understanding of desirable interaction qualities of children, parents
and therapists, and provides design implications regarding supporting
storymaking based expressive arts therapy.

###### Acknowledgements.

We are grateful to all the collaborating therapists for their generous
support. Our special thanks are extended to Therapist Jia Liu for her
remarkable dedication and invaluable contribution to this research. Our
appreciation also goes to all the participating families for their time and
efforts in the participation. This work is supported by the National Social
Science Fund of China (NSSFC) Art Grant: No. 22CG184.

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