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Record W4411558205 · doi:10.1145/3713043.3737388

“Whispers of Hope”: A Narrative-Driven, Immersive, Digital Game to Foster Hope and Emotional Growth in Children

2025· article· en· W4411558205 on OpenAlexaff
Devasena Pasupuleti, Zareen Hasna Chowdhury, Shyamli Suneesh, Sreeja Sri Ramoji, Shruti Chandra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsNarrativeMultimediaComputer sciencePsychologyVideo gameHuman–computer interactionArtLiterature

Abstract

fetched live from OpenAlex

In response to the growing psychological challenges children face, this paper presents "Whispers of Hope", a narrative-centered, webbased game integrated with Augmented Reality (AR), designed to cultivate hope, empathy, and emotional resilience in children aged 7 to 11. Drawing upon Snyder's Hope Theory, the game integrates interactive storytelling, reflective daily affirmations, and curated uplifting news to encourage goal-directed thinking and emotional growth.Through a combination of narrative immersion, socio-emotional learning, and accessible AR technology, the system supports the development of core psychological traits, including self-esteem, optimism, and perspective-taking, that contribute to a hopeful mindset.Preliminary user testing indicates high levels of engagement and perceived emotional relevance, suggesting its promise as a novel, child-centered tool for fostering hope through digital play.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.265
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractno

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