This paper explores the concept of physical materiality within interactive storytelling, focusing on Tangible Narratives (TN). Building upon the material turn, it discusses the critical role physical artefacts play in shaping user experience, narrative impact, and meaning making. It presents key conceptual frameworks that offer structured approaches for analysing the distinct roles of interactions, users and artefacts in TN, focusing on critical dimensions like diegesis, embodiment, narrative function, and user position. The paper illustrates these frameworks by showing how the incorporation of physicality influences key aspects of the narrative experience through various examples. It reflects on the current state of the field and the interdisciplinary significance of tangible storytelling, emphasising its potential to inform the design practice and deepen the understanding of interaction phenomena. The paper concludes by identifying future research, including further phenomenological inquiry into embodied narrative experience and authoring methodologies.
We introduce the term “distant coding” to describe the trend toward agentic programming in the context of interactive digital narrative pedagogy. The paper reviews these trends and offers two case studies of Interactive Digital Narrative (IDN) development that was created for courses by the authors and which embody the principles we have integrated into our own teaching practice. As programming capabilities increase, it is important to carefully navigate the tension between creativity, necessary knowledge and discovery and to avoid excessive reliance on tools even as they become more capable of independent and even autonomous development of IDNs.
This scoping review examines how narrative features and game mechanics intersect to shape emotional engagement, motivation, and health outcomes in serious games designed for children and adolescents. Analyzing 18 empirical studies published between 2015 and 2025, this review identifies recurring patterns across narrative genres, plots, structures, and character archetypes, and highlights how game mechanics are systematically integrated with narrative to construct coherent, engaging, and developmentally appropriate storytelling experiences. To synthesize the findings, we introduce the Narrative–Mechanic–Outcome matrix, a design-facing tool that maps how specific narrative–mechanic configurations are associated with different engagement and behavioral outcomes. The matrix enables researchers and developers to position their design strategies within an evidence-informed context and consider potential underexplored intersections. Findings highlight the importance of aligning narrative tone and mechanic complexity with developmental stages, particularly when addressing sensitive health topics such as mental health or identity. This study contributes both a conceptual vocabulary and a NMO matrix to reference future design and evaluation of narrative-driven serious games for youth health promotion.
How can generative AI (GenAI) be integrated in educational practices? This paper describes an approach combining problem-based learning with the creation of Interactive Digital Narratives (IDNs) using GenAI, applied during a training school for which the concrete task was to represent Malta’s complex Neolithic history. After introducing the topic, the concept of IDN, and GenAI tools, the educational journey continued by interweaving contextual information such as site visits with iterative design steps facilitating trainees to create their own IDN projects. This approach was applied during a five-day course, resulting in four IDNs incorporating the specific perspectives of the respective teams. The paper describes the pedagogical approach as well as the different ways the trainee teams found to address the limitations and challenges of current GenAI tools.
Representing uncertain history through Interactive Digital Narratives offers interactors the opportunity to challenge the grand narrative through engagements with the historical record. A gap in the literature exists in the evaluation of IDNs’ ability to teach interactors how to navigate historical uncertainty, while a demand for diegetic procedural knowledge learning exists. We propose an evaluation framework that helps determine the effectiveness of an IDN to deliver knowledge in the context of historical uncertainty and seek to evaluate not only the acquisition of declarative knowledge but also procedural knowledge learning needed to handle such conflicting perspectives. This evaluation framework is supported by a VR IDN implementation of a prehistoric complex, presenting alternative interpretations based on published research upon which the interactor is invited to answer questions about the historical site. Validation through cultural heritage experts supports the IDN’s ability to empower interactors to question the grand narrative and take an active role in the interpretation of the site.
The stories we tell about the future shape our collective imagination of technology, ecology, and multispecies coexistence. Here we present a design research pipeline that operationalizes thematic insights from speculative fiction to create interactive digital narratives (IDNs) for exploring human–plant–computer futures. Using a corpus of ten science-fiction works, we conducted a thematic analysis to identify recurring patterns in plant representation, interaction types, functional roles, and ethical themes. These insights informed a structured ideation process, storyworld design, and low-fidelity prototyping of interactive concepts, culminating in an augmented tabletop role-playing game that integrates VR immersion and AR-based plant interaction. This reproducible pipeline establishes a novel pathway for designing IDN systems directly from speculative narratives, enabling the creation of interactive artefacts that embed multispecies ethics and ecological storytelling into their core design.
Adolescents often describe their mobiles as comforting and stressful, reflecting a dependency that impacts their well-being. Responding to this challenge, Dotykáče, a digital storytelling web app and workshop programme, invites teenagers to reflect on their mobile use. Inspired by autoteatro—where audiences become performers by following scripted instructions—Dotykáče adapts this performative model to one that personifies the phone as a character, encouraging teenagers to externalise and re-examine their habits and emotional attachments. Grounded in performative principles and developmental psychology, the programme guides teenagers through staged encounters: revisiting daily gestures, exchanging phones, and ultimately defining their relationship with their device. A pilot study with Czech teenagers (ages 15–19) demonstrated strong engagement. It prompted moments of realisation, such as recognition of compulsive consumption of online content, awareness of unhealthy physical postures, and reassessment of emotional bonds with devices. These preliminary insights suggest that performative, narrative-based approaches offer a powerful complement to digital well-being education.
AI models that perform classification and prediction tasks are commonly assessed using established quantitative metrics, but evaluating text-based generative models presents unique challenges. These models generate novel, unpredictable content, often requiring more nuanced evaluation methods that go beyond rigid quantitative scores. In this paper we present a framework that can aid with the evaluation of narrative generation approaches that target screenplays as their output. Screenplays offer formatted metadata and are widely accessible, making them well-suited for automated data analysis and comparison. Our framework provides a diverse set of qualitative and quantitative evaluation metrics, including syntactic complexity, sentiment analysis, part-of-speech distribution, and character presence visualizations, to assess narrative coherence and character dynamics. We also show how our framework can be used to determine differences in human-authored and computationally generated screenplays, and provide an outlook at how this analysis can be used to improve computational approaches.
Dominant accounts of interactive storytelling, long wedded to seamless immersion, struggle to explain the appeal of titles like Honkai: Star Rail that flaunt fourth-wall ruptures yet deepen attachment. We contend that this paradox signals a design philosophy best described as Reflexive World-Building. Crucially, this reflexivity is not a theatrical aside but a modality of realism: by openly staging its own constructedness, the game remaps lived coordinates—work–time discipline, risk governance, platformized affect—into playable form. In this sense the “wall” is less a surface to be smashed than a seam through which social experience continually threads, including pressures that animate contemporary Chinese youth cultures. Across character design, interface paratexts, and core mechanics, Honkai: Star Rail deploys meta-narrative and self-reference not as narrative failure but as a deliberate rhetoric of recognition—an Invitation to Conspiracy that converts the player from a passive immersant into a knowing co-conspirator. Immersion is thereby relocated: from the mimetic demand to “believe” a world to the relational experience of being seen by it. Our analysis systematizes this shift, articulating how reflexive cues can operate in concert to sustain a durable ludic contract grounded in shared literacy rather than fragile illusion. The resulting framework moves beyond the immersion paradigm while retaining its affective aims, offering practical insight for crafting narratively complex experiences that speak to media-savvy publics without forfeiting realism’s bite.
Teaching ethics is a complex topic that demands critical thinking and extends beyond dichotomous right-or-wrong judgments. To address this challenge, we developed an open learning environment based on a Visual Novel (VN) design, enabling teachers to create interactive digital narratives through which students can actively engage in the learning process. The primary contribution of this work is a strategy that orchestrates interactive scenarios of VNs with structured discussions. This structured discussion operates as a pedagogical strategy to foster reflection and dialogue during the journey. An extra challenge of this work is how to evaluate our orchestrated approach. It entails combining the analysis of players’ log events, as a journey graph that models students’ strategy, with interactions with peers, which may lead to reconsidering decisions.
Two fundamental challenges in locative Augmented Reality (AR) storytelling are collecting data about places and the lived experiences within them, and using this data to produce compelling narratives that are experienced within their original context or in new contexts. This paper introduces a multi-phased methodology that helps creators directly address both challenges. Our primary contribution is a detailed process for (1) collecting lived socio-spatial experiences and analyzing spatial configurations from a source community (e.g., a high school) using diverse, complementary methods; and (2) collaboratively synthesizing this data, with experts in situated theatre and architecture, to produce immersive AR narratives that are highly reflective of their source environment. We further show how collecting both experiential and spatial data facilitates deploying these source-based narratives in different target environments (e.g., another school or a university building). A study with 48 participants indicated that universal themes from source-synthesized stories can resonate in different contexts when the stories are deployed using our method. However, challenges remain when transferring narratives to different contexts, including contextual dissonance and complexities when applying spatial analysis metrics for adaptive deployment. This research provides a replicable methodology for the design and deployment of locative AR narratives rooted in real-world settings.
This paper describes an approach to resurrect the ASAPS IDN authoring system using generative AI. ASAPS was originally written in Actionscript 2, an obsolete scripting language. Starting with a discussion of the ASAPS authoring tools’ original status, architecture and why it fell into obsolescence, the paper proceeds by detailing the process resurrecting the project focusing on the limitations and capabilities of current GenAI tools. Finally, lessons learned along the way are presented, hoping to inspire future work in digital preservation.
The emergence of generative artificial intelligence (AI) has introduced new possibilities for human–AI collaboration in storytelling, spanning domains such as literature, education, media, games, and multimodal systems. However, current research remains fragmented, with few attempts to synthesize co-creative practices across these fields. This study presents a scoping review of 44 peer-reviewed publications (2020–2025), using Arksey and O’Malley’s framework to examine how AI-assisted storytelling is conceptualized, implemented, and evaluated. Through domain-based analysis, we identify distinct trajectories: literary systems focus on authorship and narrative coherence; educational applications emphasize engagement, creativity, and language development; game-based systems highlight adaptive narratives and player agency; media and film studies examine authorship and workflow transformation; and multimodal platforms enable accessible visual storytelling. Across these domains, AI is increasingly positioned as a creative collaborator, supporting ideation, personalization, and co-authorship. Yet challenges remain, including narrative inconsistency, limited user control, and questions surrounding authorship and agency. This review highlights the need for inclusive design principles, clearer conceptual frameworks for co-creativity, and interdisciplinary approaches to address ethical, cultural, and practical concerns. By mapping current trends and tensions, the paper offers a foundation for future research and responsible development of AI-assisted storytelling systems.
Dramatic arcs have long served as a critical lens for understanding narratives, charting rises and falls in tension and emotion throughout plot progression. Video games are unique in that the dramatic arcs present in their narrative are driven not only by aesthetics but also by the interaction and feedback produced by diverse interactive systems. Player actions, emergent outcomes, and systemic changes in game state create experiential arcs that dovetail with more straightforward narrative approaches. These arcs often take on forms more abstract than those found in conventional storytelling. This abstraction, combined with the unpredictability of emergent game systems, complicates a designer’s critical work of tuning such systems for desired dramatic arcs in their games. This work introduces an iterative design process using Playtrace Arc Search (PAS), a tool that leverages gameplay traces and designer-defined metrics to visualize and evaluate dramatic arcs. Using a turn-based RPG simulation testbed as a case study, we show how designers can rapidly identify global systemic arc patterns and search for local narrative structures. Our method also helps reconcile quantitative gameplay data with qualitative player feedback. Our approach highlights actionable design strategies for balancing game system-driven narrative against common dramatic arc patterns.
We present a case study that artistically adapts a model of emergence observed in video feedback to the design of an emergent narrative system for live performance incorporating generative artificial intelligence. We describe a methodological analogy between the creation of emergent visual patterns in video feedback and emergent narrative patterns created through narrative feedback. We explore emergent narrative through dialogical feedback loops between the improvised speech of human performers and textual summaries generated by a large language model. In this approach, the LLM is positioned as a signal path for narrative emergence rather than as a unitary source of narrative content. We encourage further artistic and theoretical exploration of narrative feedback by artists working with emergent narrative in socially interactive performance and audiovisual synthesis.
This article explores how extended reality (XR) reconfigures narrative focalisation by embedding the user within the perceptual frame of a storyworld. Drawing on foundational narrative theory as well as more recent scholarship, it analyses Notes on Blindness: Into Darkness (dirs. Arnaud Colinart, Amaury La Burthe, Peter Middleton, and James Spinney, 2016), Goliath: Playing With Reality (dirs. Barry Gene Murphy and May Abdalla, 2021) and Turbulence: Jamais Vu (dir. Ben Andrews, 2023) to show how voiceover, sensory stimuli, and user interaction co-create a shared field of perception in these XR works. Narration in this context is shown to be variable and relational, blending first and second-person strategies. Focalisation emerges as embodied, contingent, and interactive- no longer confined to text or image alone. This challenges traditional distinctions between narrator, character, and audience, positioning the user as a kind of co-focaliser. The article argues that XR invites an expansion of focalisation theory to accommodate hybrid modes of perception and highlights the medium’s potential for telling embodied and marginalised stories through immersive experience.
This paper presents a further exploration of a mixed initiative comic-making method that combines hand-drawn imagery with AI-generated visuals in a turn-taking, interactive manner. Initially developed within a personal artistic practice, the method was later tested in broader settings to understand how it might function as a public, co-creative method. As a first step, a pre-study was conducted at a public AI art exhibition, where casual participants were invited to engage with the method by producing short visual narratives. Based on insights from this initial engagement, a structured workshop was carried out where participants created comics with the same method by alternating between analogue sketching and AI-assisted generation using a publicly available image generation tool appropriated for the task by the authors. Participants provided written reflections on their experience. The resulting comics and responses were collected and clustered to explore emerging patterns in narrative form and participant perception. This paper documents both phases – the pre-study and the workshop – and outlines the steps of the method and presents the comics created with it. Drawing from participant reflections, the paper highlights themes that arose in relation to the process. In particular, we examine how the authors’ method operates outside their studios in situated contexts and in relation to casual creative practices.
Mental health is a critical aspect of overall well-being, yet stigma and misinformation remain prevalent, particularly among college students who face unique stressors. The rising incidence of mental health conditions, exacerbated by the COVID-19 pandemic, underscores the need for accessible support systems. Digital mental health interventions, such as narrative-based games, offer a scalable, affordable, and engaging approach to promote mental health education. This study combines visual novels with Large Language Models (LLMs) to create a digital intervention aimed at improving mental health literacy by addressing literacy on depression and misconceptions about depression. We developed a visual novel using LLM-generated narratives and conducted a mixed-methods study with 28 college students, assessing the game’s impact at pre-test, post-test, and one-week follow-up, along with narrative transportation. Results showed no significant change in depression literacy, likely due to high baseline scores, but misconceptions of depression significantly decreased and were maintained at follow-up. Participants reported moderate to high narrative transportation. Qualitative findings emphasised emotional engagement, stigma reduction, the perceived value of digital tools, and participants’ scepticism regarding AI-generated narrative authenticity.
Extended Reality (XR) is increasingly adopted for collaborative work, yet immersive storytelling and co-creation are often examined in isolation. This paper presents a conceptual review of XR systems where narrative structures and multi-user creation intersect. It introduces a four-dimensional framework encompassing Platform Affordances, Narrative Control, Participant Agency, and Adaptive Mediation. We position narrative not as an added layer but as a mechanism for organising collaboration. In this paper, we (i) synthesise how presence, interactivity, and authorship are operationalised across existing systems; (ii) define indicators for classifying XR co-creative experiences along the four dimensions; and (iii) outline directions for empirical validation, including comparative studies of control–agency trade-offs. We illustrate the framework by mapping representative platforms and sketching hybrid designs that balance authored coherence with emergent improvisation. Ethical considerations in AI-supported mediation, such as authorship, transparency, and accessibility, are also discussed. The framework offers a structure for comparative research and the design of XR systems where storytelling enables co-creative practice.
With more than 111.8 million daily active users worldwide, Roblox is the main virtual world platform by number of users. Although the platform policies explicitly ban political content, content with political references (to political figures, entities, ideologies) is prevalent and easy to locate. That makes Roblox an ideal case to study how new immersive virtual worlds enable emergent new modes of political participation and politically oriented narratives. In particular, given that the majority of users are children and teenagers, the study of political content in Roblox can help expand current knowledge on how emergent media technologies shape youth political participation and expression. In this work-in-progress paper, we intend to present an ongoing digital ethnography in Roblox. Particularly, we present the iterative creation of a dataset with political content which reveals different ways of political expression including prosocial behaviors such as protests as well as extremist violent hate speech. From an Interactive Digital Narrative (IDN) perspective, this approach offers an opportunity to explore how IDN might incorporate political content and spark political participation among children, teens, and youth. To achieve this aim, we draw on the IDN literature to address and represent complex societal issues (Koenitz, Barbara Eladhari, 2022) as well as political internet games (Neys Jansz, 2010), and political participation (Durotoye et al., 2025; Vaccari and Valeriani, 2021).
