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Author: search.filters.author.Patricia Acosta-VargasLanguage: search.filters.language.English

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    Item type:Publication,
    Web Accessibility in the Portals of the Countries in the Latin American Index of Artificial Intelligence
    (2025)
    Patricia Acosta-Vargas
    ;
    Gloria Acosta-Vargas
    ;
    Belén Salvador-Acosta
    ;
    Jadán Guerrero, Janio  
    This study assesses the web accessibility of portals from the Latin American Artificial Intelligence Index (ILIA) countries, emphasizing the digital inclusion of users with disabilities. Using the Web Content Accessibility Guidelines (WCAG 2.2) as a reference point, the study focuses on the four principles of accessibility: perceptibility, operability, comprehensibility, and robustness. The results show that 43.20 % of the sites met the (minimum) contrast requirements, and 26.48 % met the navigability W3C recommendations. Chile (ranked first, score 73.07) presented 15 contrast issues and six errors overall, demonstrating a firm adherence to accessibility. Brazil (ranked second, with a score of 69.30) showed six contrast issues and eight errors, indicating a solid performance. However, Cuba and Venezuela had significant problems, with 25 and 34 errors, respectively. In contrast, Uruguay ranked high with no errors in contrast and perceptibility, highlighting its leadership in web accessibility in the region. These findings provide valuable insights for policymakers and developers looking to improve accessibility and digital inclusion across Latin America's digital infrastructure.
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    Music Education with Artificial Intelligence for Inclusive and Sustainable Early Childhood Learning
    (2025)
    Margarita Roldan-Cardona
    ;
    Marcos Chacón-Castro
    ;
    Jadán Guerrero, Janio  
    ;
    Luis Salvador-Ullauri
    ;
    Patricia Acosta-Vargas
    This study aims to evaluate the impact of a didactic strategy that incorporates generative artificial intelligence (AI) into music education, supporting oral language development in preschool children and promoting inclusive and sustainable early childhood learning. Using an action-research approach, a mixed-methods design was applied to assess the performance of 15 children aged 3 to 6 years, divided into experimental and control groups. The experimental group participated in AI-supported activities using tools such as Genially, Educaplay, and Wordwall, whereas the control group employed traditional methods. Quantitative data from pre-and post-tests, as well as qualitative observations, revealed that AI-enhanced sessions improved motivation, pronunciation, and engagement, particularly among children aged 5 and 6 years old. Although statistical tests showed no significant differences between groups, the intervention demonstrated pedagogical effectiveness by increasing interest and participation. The novelty of this work lies in applying generative AI in early music education to personalize learning and reduce inequality, aligning with several Sustainable Development Goals (SDGs 3, 4, 9, and 10). The findings offer valuable insights into designing inclusive educational experiences through the integration of ICT and AI, highlighting the need to enhance teacher training in emerging digital pedagogies and promote accessible music-based learning in diverse educational settings.
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