Design and Evaluation of a Culturally Adapted Signing Avatar Framework (CASAF) for deaf communities in Pakistan: a Technology Acceptance Model approach

Background Deaf and Hard-of-Hearing (DHH) individuals in Pakistan face persistent communication barriers, limiting equitable access to digital content, education, and public services. While globally, virtual signing avatars have emerged as a scalable accessibility tool, their adoption in low-resource and linguistically diverse contexts remain underexplored. Methods This study investigates acceptance of signing avatars with cultural adaptations among 475 DHH participants engaged in special education across Pakistan using an extended Technology Acceptance Model (TAM). Key constructs including perceived usefulness, ease of use, trust, user experience, and design quality were evaluated through a structured questionnaire. Results Results indicate that while DHH users hold positive attitudes towards avatar-based solutions, preference for human interpreters remains dominant due to concerns around avatar realism, gesture accuracy, and cultural contextualization. The findings offer localized insights and practical implications for inclusive digital accessibility tools, particularly in South Asian contexts. Conclusions The study contributes to the adaptation of Technology Acceptance Model for Signing Avatars (TAMSA) to Pakistan’s unique socio-cultural and landscape, providing evidence-based recommendations for culturally sensitive digital assistive technologies.

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Publication Details

Journal
PeerJ Computer Science
Published
2026-08-24
DOI
https://doi.org/10.7717/peerj-cs.3953
Primary Topic
Hearing Impairment and Communication
Type
article
Field-Weighted Citation Impact
0.00
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article

Design and Evaluation of a Culturally Adapted Signing Avatar Framework (CASAF) for deaf communities in Pakistan: a Technology Acceptance Model approach

Memoona Malik, Inayat Ur Rehman, Shahid Kamal, Fasee Ullah et al.
PeerJ Computer Science
Hearing Impairment and Communication
article

Design and Evaluation of a Culturally Adapted Signing Avatar Framework (CASAF) for deaf communities in Pakistan: a Technology Acceptance Model approach

Memoona Malik, Inayat Ur Rehman, Shahid Kamal, Fasee Ullah, Samera Batool, Abdul Mateen, Sehrish Afzal, Rubina Adnan
article en

Abstract

Background Deaf and Hard-of-Hearing (DHH) individuals in Pakistan face persistent communication barriers, limiting equitable access to digital content, education, and public services. While globally, virtual signing avatars have emerged as a scalable accessibility tool, their adoption in low-resource and linguistically diverse contexts remain underexplored. Methods This study investigates acceptance of signing avatars with cultural adaptations among 475 DHH participants engaged in special education across Pakistan using an extended Technology Acceptance Model (TAM). Key constructs including perceived usefulness, ease of use, trust, user experience, and design quality were evaluated through a structured questionnaire. Results Results indicate that while DHH users hold positive attitudes towards avatar-based solutions, preference for human interpreters remains dominant due to concerns around avatar realism, gesture accuracy, and cultural contextualization. The findings offer localized insights and practical implications for inclusive digital accessibility tools, particularly in South Asian contexts. Conclusions The study contributes to the adaptation of Technology Acceptance Model for Signing Avatars (TAMSA) to Pakistan’s unique socio-cultural and landscape, providing evidence-based recommendations for culturally sensitive digital assistive technologies.

PeerJ Computer ScienceVol. 12
COMSATS University Islamabad (PK), Multimedia University (MY), Universiti Teknologi Petronas (MY), Federal Urdu University (PK)
Quality Education
Openalex Percentile: Top 4%
Hearing Impairment and Communication
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Design and Evaluation of a Culturally Adapted Signing Avatar Framework (CASAF) for deaf communities in Pakistan: a Technology Acceptance Model approach — Memoona Malik, Inayat Ur Rehman, et al. · PeerJ Computer Science (2026) | TGRS Research Map | TGRS