Role-Taking & Literacy Interventions

• Role-taking and literacy-based interventions are strategies that promote cognitive development and skill acquisition through game-based, narrative, and scaffolding methods.
• They integrate role adoption and targeted metacognitive supports using participatory design and iterative co-creation to enhance domain-specific literacies.
• Assessment employs quantitative and qualitative metrics, including SEM, IRT, and performance logs, to evaluate intervention efficacy and behavioral change.

Role-taking and literacy-based interventions together comprise a suite of strategies to promote critical skill development, cognitive awareness, and behavioral change across educational, technological, and sociotechnical domains. “Role-taking” refers to processes in which learners, users, or participants actively adopt new perspectives or social roles—such as assuming the character in a narrative, the position of a fact-checker, or the agent in human–AI interaction. “Literacy-based interventions” incorporate targeted instructional or metacognitive supports that help participants acquire domain-specific literacies (e.g., reading, media, visualization, or AI literacy). These approaches are frequently integrated through game-based, narrative, scaffolding, and metacognitive frameworks and assessed via metrics rooted in psychological, educational, or computational theories. Their effectiveness depends on context, methodology, engagement design, and the depth of user participation.

1. Methodological Foundations: Game Design, Narrative, and Participatory Action

Literacy-based interventions are commonly operationalized via participatory design and action-research methodologies. For example, Vocalnayno (Scott, 2013) adopts iterative co-design, engaging teachers, teaching assistants, parents, and pupils to identify barriers to reading assessment and co-create a game intervention. Mechanics center on reading aloud to burst on-screen bubbles, with performance logged and linked to game progression, directly motivating reading practice through in-game rewards.

In visualization literacy development (Huynh et al., 2020), narrative-focused role-playing games embed quantitative assessment into the structure of a fantasy adventure. Learners undergo both decontextualized and narrative-formatted literacy tasks, with game engagement augmented via dialogue, exploration portals, and contextual feedback, supporting the “stealth learning” paradigm. Participatory immersion is shown to increase motivation and affective investment, though not always yielding marked improvements in core skill acquisition.

Parent–child joint reading platforms exemplify participatory literacy design in digital contexts, leveraging conversational voice agents and interleaved turn-taking systems to foster collaborative engagement (Vargas-Diaz et al., 2024). Technical interfaces use drag-and-drop character assignment and on-screen dialogue cues, transforming passive reading into reciprocal role-play, balancing listening and speaking roles for literacy reinforcement.

2. Role-Taking: Mechanisms and Impact Across Domains

Role-taking is employed as both a motivational tool and a cognitive scaffold. In educational games, a learner assuming the role of a protagonist is exposed to pedagogic challenges contextualized within a dramatic arc (Huynh et al., 2020). Highlighting the active character, facilitating exploration, and presenting feedback through a narrative lens all support role internalization and sustained attention.

The impact of role-taking extends to social engineering and behavioral interventions. In mixed factorial experiments targeting trust and risk-taking, intervention groups enacted persuader and persuadee roles, guided through structured reflection on persona selection and scenario justification (Supti et al., 27 Sep 2025). However, short-term role rehearsal failed to yield significant reductions in bias toward appearance cues, suggesting that role-taking’s transformative potential is contingent on immersive and repeated engagement.

Within misinformation interventions, role-taking is posited as an amplifier of media literacy: individuals acting as fact-checkers or trusted peers demonstrate higher commitment to verifying information (Heuer, 14 Jan 2025). Embedded role-play within literacy frameworks (group discussion, peer review, drama) is theorized to deepen information evaluation and support scalability across contexts.

3. Literacy-Based Intervention Design: Scaffolding, Feedback, and Metacognition

Effective literacy-based interventions integrate scaffolding and formative assessment principles. Game environments like Vocalnayno (Scott, 2013) and narrative RPGs (Huynh et al., 2020) record granular reading or visualization activity, enabling dynamic feedback and individualized learning adjustments. Scaffolding manifests in stepwise prompts, immediate activity feedback, and adaptive structuring of increasingly challenging content (Jin et al., 2024).

Learning analytics research emphasizes “feedback literacy” as a tripartite construct: critical appreciation of feedback, translation/sensemaking, and affect management (Tsai, 2022). Systems transition from static dashboard products to process-oriented loops, with teachers and students cocreating meaning from analytics outputs. LaTeX representations formalize relationships as in

$FL = \alpha \, CA + \beta \, TS + \gamma \, AM$

where $CA$ is critical appreciation, $TS$ is translation/sensemaking, and $AM$ is affect management.

AI literacy interventions highlight metacognitive supports such as deliberate friction (prompting users to reflect at critical stages), bi-directional intervention (addressing both input formulation and output interpretation), and adaptive scaffolding based on engagement patterns (Lim, 23 Apr 2025). Visualization maps and prompt refinement tools are implemented to expose and mitigate human, statistical, and systemic biases in human-AI workflows.

4. Assessment and Measurement: Objective, Predictive, and Statistical Models

Quantitative metrics and predictive models are central to evaluating the effectiveness of literacy-based interventions. Reading interventions capture correctness of phonics/word articulation, with exploratory metrics for gaze duration and speech confidence (Scott, 2013). AI literacy tasks utilize structural equation modeling (SEM), tracing direct and mediated effects of literacy on compliance using formulas such as:

$$\text{MAD} = |\text{AI}_{\text{pred}} - \text{User}_{\text{pred}}|$$

A negative path coefficient in SEM reflects algorithm aversion among high-literacy users (Kühl et al., 2024).

Performance-based instruments like GLAT (Jin et al., 2024) use IRT-derived 2PL models to infer latent literacy traits, demonstrating superior predictive validity for GenAI-supported task performance compared to self-reported measures:

$$\text{AI-assisted score} = \beta_0 + \beta_1 \times \text{GLAT-literacy} + \ldots$$

Additional strategies include regression models for comprehension improvement under chatbot interventions (Jin et al., 2024), ENA (Epistemic Network Analysis) mapping for dialogue codes, and difference formulas to assess bias in social engineering settings:

$$\text{Bias}_{\text{Risk or Trust}} = \text{Rating}_{\text{Factor A}} - \text{Rating}_{\text{Factor B}}$$

5. Negative Results, Limitations, and Controversies

Empirical findings indicate that short-term, standalone role-taking or literacy interventions may not produce significant behavioral change in deeply ingrained cognitive biases, particularly in risk and trust contexts involving demographic cues (Supti et al., 27 Sep 2025). Despite robust factorial design and validated measures, neither rehearsal, reflection, nor basic literacy instruction yielded appreciable reduction in cue-based judgments. This suggests entrenched status quo and cognitive load effects may require more immersive, extended, or multifaceted approaches.

Similar caveats are presented in the context of misinformation: while media literacy and role-taking are endorsed as scalable and generalizable interventions, limitations such as generic implementation (“pseudo-magic bullet” critiques), user rejection, and potential overconfidence are acknowledged (Heuer, 14 Jan 2025). Diversity and group dynamics have emerged as moderators of reflective impact in GenAI literacy games, with homogeneous groups sometimes failing to surface latent biases (Ma et al., 17 Sep 2025).

6. Implications for Practice and Future Research

Role-taking and literacy-based interventions remain foundational for sustainable, scalable development of domain-specific literacies. The empirical evidence points toward the need for extended, adaptive, and context-sensitive engagement strategies. Multi-modal scaffolding, participatory reflection, personalized feedback, and deliberate design of social interaction play prominent roles in recent research. The ongoing expansion of digital literacy contexts—including AI, misinformation, and collaborative analytics—will require increasingly sophisticated intervention design, rigorous assessment models, and nuanced understanding of group and individual dynamics.

Frameworks such as the Phase Model of Misinformation Interventions (Heuer, 14 Jan 2025) situate literacy efforts within a temporal continuum, emphasizing the importance of early, preventive education. Interdisciplinary consensus supports the scalability and persistent relevance of literacy-based approaches, albeit with measured recognition of their limitations.

7. Summary Table: Intervention Types and Assessment Strategies

Domain	Role-Taking Mechanism	Literacy Assessment/Formalism
Reading development	Narrative games, feedback	Correct reading vocalization, gaze metrics
Visualization	Narrative RPG, protagonist	Pre/post chart tests, qualitative feedback
AI literacy	Metacognitive scaffolds	SEM, MAD, GLAT-IRT models
Misinformation	Peer fact-checker, dialogue	Phase Model, media literacy measures
Social engineering	Persuader/persuadee roles	Bias difference ratings, RM-ANOVA

Role-taking and literacy-based interventions encompass a diverse set of methodologies unified by reciprocal engagement, context-aware feedback, and performance-linked metrics. Their design and implementation require continued refinement to address persistent biases, maximize equitable learning outcomes, and support robust adaptation in rapidly evolving sociotechnical landscapes.