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Empirical evidence of AI-enabled accessibility in digital gastronomy: Development and evaluation of the Receitas +Power Platform

datacite.subject.fosEngenharia e Tecnologia
dc.contributor.authorSerra, Paulo
dc.contributor.authorOliveira, Ângela
dc.contributor.authorFidalgo, Filipe
dc.contributor.authorSerra, Bruno
dc.contributor.authorInfante, Tiago
dc.contributor.authorBaião, Luís
dc.date.accessioned2026-01-08T16:43:13Z
dc.date.available2026-01-08T16:43:13Z
dc.date.issued2025
dc.date.updated2026-01-07T15:21:44Z
dc.description.abstractThis study explores how artificial intelligence can promote accessibility and inclusiveness in digital culinary environments. Centred on the Receitas +Power platform, the research adopts an exploratory, multidimensional case study design integrating qualitative and quantitative analyses. The investigation addresses three research questions concerning (i) user empowerment beyond recommendation systems, (ii) accessibility best practices across disability types, and (iii) the effectiveness of AI-enabled inclusive solutions. The system was developed following user-centred design principles and WCAG 2.2 standards, combining generative AI modules for recipe creation with accessibility features such as voice interaction and adaptive navigation. The evaluation, conducted with 87 participants, employed the System Usability Scale complemented by thematic qualitative feedback. Results indicate excellent usability (M = 80.6), high reliability (Cronbach’s α = 0.798–0.849), and moderate positive correlations between usability and accessibility dimensions (r = 0.45–0.55). Participants highlighted the platform’s personalisation, clarity, and inclusivity, confirming that accessibility enhances rather than restricts user experience. The findings provide empirical evidence that AI-driven adaptability, when grounded in universal design principles, offers an effective and ethically sound pathway toward digital inclusion. Receitas +Power thus advances the field of inclusive digital gastronomy and presents a replicable framework for human–AI co-creation in accessible web technologies.eng
dc.description.sponsorshipThis work was funded by National Funds through the Foundation for Science and Technology (FCT), I.P., within the scope of the project UIDB/05583/2020 and DOI identifier https://doi.org/10.54499/UIDB/05583/2020.
dc.description.versionN/A
dc.identifier.citationSERRA, Paulo [et al.] (2025) - Empirical evidence of AI-enabled accessibility in digital gastronomy: Development and evaluation of the Receitas +Power Platform [preprin). Gastronomy. DOI: 10.3390/gastronomy4010002
dc.identifier.doi10.3390/gastronomy4010002en_US
dc.identifier.slugcv-prod-4647455
dc.identifier.urihttp://hdl.handle.net/10400.11/10441
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAccessible web design
dc.subjectArtificial intelligence
dc.subjectInclusive digital gastronomy
dc.subjectSystem usability evaluation
dc.titleEmpirical evidence of AI-enabled accessibility in digital gastronomy: Development and evaluation of the Receitas +Power Platformeng
dc.typeresearch article
dspace.entity.typePublication
oaire.citation.titleGastronomyen_US
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameMarques Oliveira
person.familyNameFidalgo
person.givenNameAngela Cristina
person.givenNameFilipe
person.identifier.ciencia-id471B-8360-6CF9
person.identifier.ciencia-idBC11-DFB7-A451
person.identifier.orcid0000-0003-0172-4679
person.identifier.orcid0000-0001-7326-9957
person.identifier.scopus-author-id55810696000
rcaap.cv.cienciaid471B-8360-6CF9 | Ângela Cristina Marques de Oliveira
rcaap.rightsopenAccessen_US
relation.isAuthorOfPublication743a5c35-45ff-4434-bd00-b2c14691ba19
relation.isAuthorOfPublication489eda06-3ade-4c15-a54e-fee91030518a
relation.isAuthorOfPublication.latestForDiscovery743a5c35-45ff-4434-bd00-b2c14691ba19

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