Avilés-Castillo, Fátima
Preferred name
Avilés-Castillo, Fátima
Main Affiliation
Ambato
Email
faviles@indoamerica.edu.ec
ORCID
0000-0002-0184-8893
Scopus Author ID
57845057800
26 results
Now showing 1 - 10 of 26
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Item type:Publication, Smart Learning for Dyscalculia: Cognitive Support with a Pedagogical Approach(Springer Nature Switzerland, 2026); ; ; This study explores the impact of the cognitive rehabilitation of dyscalculia, assessing its effectiveness in improving mathematical competencies and its potential as a complementary tool in educational and therapeutic settings. Preliminary results suggest a significant improvement in numerical performance, highlighting the importance of technology in inclusive education. Smart Learning for Dyscalculia represents an innovative pedagogical approach that combines adaptive technologies with inclusive educational strategies to support learners who experience persistent difficulties in mathematical cognition. Dyscalculia often affects numerical processing, pattern recognition, and problem-solving skills, leading to increased anxiety and reduced confidence in formal learning contexts. To address these challenges, Smart Learning environments integrate intelligent tutoring systems, interactive applications, and serious games designed to provide personalized guidance, real-time feedback, and dynamic scaffolding. From a pedagogical perspective, this approach emphasizes student-centered learning by recognizing individual rhythms, strengthening working memory, and promoting motivation through gamification and challenge-based tasks. Immediate feedback and progressive difficulty levels foster critical thinking, while reducing frustration and promoting a sense of achievement. The role of the teacher remains essential, as educators act as facilitators who interpret data from smart systems, adapt strategies, and provide socio-emotional support to ensure equitable learning outcomes. This cognitive support framework not only leverages technology to mitigate mathematical learning barriers, but also advances inclusive education by aligning innovation with pedagogical intentionality. Ultimately, Smart Learning for Dyscalculia contributes to the development of essential mathematical competencies, ensuring that students with diverse needs can participate fully and effectively in academic and everyday contexts. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impact of mixed reality on the care of the elderly: a scoping review(Springer Science and Business Media LLC, 2026-07-06); ; Palacios-Navarro, GuillermoPopulation aging requires innovative technological strategies that promote autonomy, functionality, and well-being in old age. In this context, mixed reality (MR), a technology that integrates physical and digital elements in a shared and interactive real-time environment, emerges as a promising alternative. To analyze the current state of evidence on the use of MR in the care of older adults, including its theoretical and practical implications. Scientific articles were reviewed in Scopus, Web of Science, PubMed, IEEE Xplore, and EBSCO. Data from 15 studies were organized into an analytical matrix to identify methodological and impact patterns. MR interventions have shown promising preliminary results in physical rehabilitation, cognitive stimulation, emotional well-being, and social interaction by combining sensory feedback, functional tasks, and meaningful experiences. The included studies represent heterogeneous MR configurations along the virtual reality continuum, including transparent or pass-through optical viewers, VR-HMD-based systems with real-world interaction, and sensor- or projection-based platforms. Rather than demonstrating superiority over virtual or augmented reality, the evidence suggests specific advantages related to contextual awareness, physical interaction, and cognitive-motor-affective integration. These features were associated with potential improvements in mobility, executive functions, motivation, positive emotions, and social presence, supporting an interpretive cognitive-motor-emotional framework and the design of safe, meaningful, and context-sensitive interventions. MR shows promising potential for the care of older adults by improving cognitive, motor, emotional, and social outcomes. However, current evidence remains preliminary due to small sample sizes, methodological heterogeneity, a scarcity of comparative studies, and a lack of longitudinal evidence. © The Author(s) 2026. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Performance and Real-World Variability of Predictive Maintenance Models for Vehicle Fleets(2024); ; Elena Blanco-RomeroThis study presents a comprehensive evaluation of predictive maintenance models for vehicle fleets, detailing a sequence of systematic steps to ensure model performance and address real-world variability. The process begins with database creation and data preprocessing, where relevant maintenance records are filtered, and datetime columns are converted to facilitate time-based calculations. Grouping and aggregation techniques are then applied to count occurrences of specific maintenance activities and identify common failure types. For model training, we define a neural network architecture comprising dense and dropout layers to mitigate overfitting, compile the model with suitable loss functions and optimizers, and train it using the prepared data. The trained model, along with the scaler and encoder, is saved for future use. To augment the dataset, synthetic data is generated using the Faker library and random distributions, with added noise to mimic real-world variability. Preprocessing steps are reapplied to this synthetic data to ensure consistency. By implementing this neural network, we achieved a sensitivity of 0.93 and an ROC of 0.71. Following these detailed steps, we develop a robust predictive maintenance model that effectively identifies failures and non-failures, ultimately enhancing the reliability and efficiency of vehicle fleet management.27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Influence of continuous navigation modes on the immersive experience in a virtual supermarket(2026); ; 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predictive Maintenance in Industrial Robotics Using Big Data: Techniques, Challenges, and Opportunities(2024); ; 14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Defect Reduction in Textile Manufacturing: A Review(2025); The textile industry faces continuous challenges in reducing defects during manufacturing, as quality inconsistencies can lead to financial losses, reduced efficiency, and diminished consumer confidence. Addressing this issue requires a combination of methodological and technological approaches that optimize production while minimizing waste. This review examines various strategies for defect reduction, focusing on process improvement methodologies, predictive technologies, and sustainable practices. A systematic analysis of 12 studies highlights the effectiveness of structured quality management approaches in identifying and eliminating defect sources. Additionally, predictive models based on artificial intelligence have demonstrated significant potential in real-time defect detection and prevention, improving overall product quality. However, challenges such as machinery rigidity and the high variability of textile products complicate the implementation of these strategies. Sustainable manufacturing practices and specialized workforce training have also been identified as key factors in enhancing defect management, as they contribute to resource conservation, waste reduction, and improved working conditions. The findings suggest that a comprehensive approach, integrating advanced process optimization techniques, predictive analytics, and sustainable production methods, is essential for improving efficiency and quality in textile manufacturing. This integration not only reduces defects but also strengthens competitiveness in an industry increasingly driven by quality, sustainability, and technological innovation. The OSF registration can be accessed at: https://doi.org/10.17605/OSF.IO/NAMWY. © 2025 IEEE.14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards Smart Agriculture: An Overview of Big Data in the Agricultural IndustryAgriculture is currently undergoing progressive diversification and expansion, as demonstrated by the wide range of research topics and methodologies being employed. The growing need for technology to enhance agricultural processes is increasingly evident and prominently highlighted in recent studies. To assess the influence of Big Data on agriculture and its potential to advance Smart Agriculture, this bibliometric study was conducted. The research consolidates bibliometric data from the Scopus database, using the Bibliometrix package to identify trends in this field. The findings show a growing annual publication rate, indicating increasing interest in the integration of data analysis methodologies within agriculture. The collaborative nature of the research, combined with a high citation rate per document and diversity of key terms, underscores the importance of this field and its potential contribution to achieving Smart Agriculture. The convergence of Big Data, the Internet of Things, and agriculture is particularly noteworthy, as these technologies are improving decision-making and efficiency in the agricultural sector. Despite certain limitations, this study highlights the transformative potential of these advancements and suggests areas for future research, thus laying the groundwork for a more sustainable, productive, and intelligent agricultural future.21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Organizational communication in change management: A narrative review(2026); ; 78 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimizing Natural Language Processing: A Comparative Analysis of GPT-3.5, GPT-4, and GPT-4oIn the last decade, the advancement of artificial intelligence has transformed multiple sectors, with natural language processing standing out as one of the most dynamic and promising areas. This study focused on comparing the GPT-3.5, GPT-4 and GPT-4o language models, evaluating their efficiency and performance in Natural Language Processing tasks such as text generation, machine translation and sentiment analysis. Using a controlled experimental design, the response speed and quality of the outputs generated by each model were measured. The results showed that GPT-4o significantly outperforms GPT-4 in terms of speed, completing tasks 25% faster in text generation and 20% faster in translation. In sentiment analysis, GPT-4o was 30% faster than GPT-4. Additionally, analysis of response quality, assessed using human reviews, showed that while GPT-3.5 delivers fast and consistent responses, GPT-4 and GPT-4o produce higher quality and more de-tailed content. The findings suggest that GPT-4o is ideal for applications that require speed and consistency, while GPT-4, although slower, might be preferred in contexts where text accuracy and quality are important. This study highlights the need to balance efficiency and quality in the selection of language models and suggests implementing additional automatic evaluations in future research to complement the current findings.18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Ethical and Social Challenges in Virtual Reality: A Bibliometric Analysis(2024); ; 12
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