Yánez Rueda, Hugo
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Yánez Rueda, Hugo
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Ambato
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hugoyanez@uti.edu.ec
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57345706900

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Qualitative and Quantitative Pathways in Educational Research: A Systematic Review

2024 , Mora Rosales, José , Zurita Álava, Susana , Yánez Rueda, Hugo , Becerra García, Eulalia

The present study aimed to know the qualitative and quantitative paths in educational research A methodology of a systematic review (RS) of literature of basic type was used, descriptive exploratory study of diverse publications with both qualitative and quantitative approaches, resulting from thorough and procedural research, in various databases of recognized quality such as Scopus, Google Scholar and Dialnet As results after the application of the PRISMA flowchart and the verification of the inclusion and exclusion criteria, 20 documents were analyzed in both English and Spanish, published between 2019 and 2023. As a conclusion, it was specified that the qualitative and quantitative paths in educational research are directed towards innovative, reflective, collaborative and critical thinking research. Likewise, educational researchers should be prepared in conceptual, procedural, attitudinal and functional terms to face the emerging challenges, as a consequence of the dynamic and changing situation of the needs and expectations of world society.

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Methodological innovation for the teaching of TIC in Higher Education

2021 , Morales-Urrutia E.K. , Ocaña J.M. , Yánez Rueda, Hugo , Naranjo A.F.N.

The inclusion of technology in the different academic spaces of higher education education has allowed the educational process to take another course and for both teachers and students to adapt to these changes and even more so to those that have been experienced around the pandemic of COVID-19. This study shows the methodological approach for the micro-curricular organization of the Information and Communication Technologies subject, based on didactic methodological strategies that seek to achieve learning achievements based on digital tools according to Bloom’s taxonomy. This research has been carried out in a public university in Ecuador with 207 first-semester students divided into 6 groups. Through the methodological application of its four phases: analysis, planning, design and implementation, and evaluation; favorable results have been obtained in meaningful learning achieved with students. As future work it is intended to apply this methodological approach in related subjects in higher education, thus exposing this approach to a process of continuous improvement. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

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Research Trends in Mixed Reality for Cognitive Aging: A Bibliometric Perspective

2026 , Yánez Rueda, Hugo

In recent years, research on mixed realityMixed reality technologies encompassing virtual reality and augmented reality has gained momentum in the context of aging and cognitiveCognitive aging health. This bibliometric analysisBibliometric analysis explores global trends in scholarly output related to applications for cognitive rehabilitation and support in older adultOlder adults populations. The study analyzed 75 documents indexed in Web of Science from 2009 to 2025, using VOSviewer for visualization and co-occurrence mapping. The temporal distribution of publications indicates a sustained rise from 2018 onward, with 2024 being the most prolific year, suggesting an academic consolidation of mixed reality as a valid approach to non-pharmacological intervention for aging-related decline. The co-occurrence analysis reveals three interrelated thematic clusters: (1) technological innovation, centered around keywords like virtual reality, augmented reality, and design, reflecting the evolution of immersive interfaces adapted to cognitive and physical limitations; (2) clinical and cognitive application, including rehabilitation, impairment, dementia, and alzheimer’s disease, highlighting the alignment of mixed realityMixed reality with neurodegenerative conditions; and (3) behavioral and lifestyle engagement, with terms such as physical activity, exercise, adherence, and quality of life, indicating a growing research trend that integrates embodied interaction with well-being and behavioral change. Notably, older adultsOlder adults emerge as the most connected term, acting as a central bridge between technology and health-related objectives. This convergence suggests a shift from purely exploratory work to user-centered, context-aware applications aimed at improving autonomy and engagement in aging populations. Future research should focus on comparative regional implementations, long-term effectivenessEffectiveness, and inclusive design to ensure equitable access and sustainable deployment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

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Smart Material Phase Classification Using Machine Learning on Ising Lattice Simulations

2026 , Yánez Rueda, Hugo , Yánez Arcos, Dayanara Lissette

Understanding and classifying phase transitionsPhase transitions in lattice-based systems remain central challenges in statistical physics and material science, particularly when conventional order parameters become ambiguous. Recent advances in machine learningMachine learning have shown promise in automating phase detection, yet many approaches either focus narrowly on identifying the critical temperature or rely on raw spin configurations, which can hinder interpretability and robustness. In this work, we develop a hybrid computational framework that integrates Monte Carlo simulations of the two-dimensional Ising modelIsing model with unsupervised machine learningMachine learning techniques to address these challenges. By extracting high-level thermodynamic observables—magnetization, energy, specific heat, and susceptibility—we construct a feature-rich dataset that captures both average behavior and fluctuation-driven response. Dimensionality reduction via Principal Component Analysis (PCA), followed by KMeans clustering, enables data-driven classification of ferromagnetic, paramagnetic, and antiferromagnetic regimes. The framework successfully identifies first-order transitions through hysteresis loops, resolves second-order critical phenomena near Tc ≈ 2.269, and detects the Néel transition in antiferromagnetic systems where traditional magnetization fails. These findings highlight the novelty of using thermodynamic observables for interpretable ML-based phase classification and demonstrate the potential of this approach for analyzing smart materialsSmart materials and adaptive technologies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

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Ethical Use of Generative Artificial Intelligence Among Ecuadorian University Students

2025 , Buele, Jorge , Ángel Ramón Sabando-García , Bosco Javier Sabando-García , Yánez Rueda, Hugo

Artificial intelligence has transformed educational environments by facilitating processes such as information retrieval, assisted writing, automated feedback, and personalized tutoring. Within university settings, the adoption of technologies capable of autonomously generating content has increased rapidly, becoming a common academic resource for students. However, this accelerated integration poses ethical challenges, particularly when such tools are used without a clear understanding of their implications. This study aimed to examine how students’ emotional attitudes (affective), understanding (cognitive), and practical use (behavioral) of AI relate to their ethical engagement with these technologies. A structured questionnaire was administered to 833 university students in Ecuador. The instrument showed excellent internal consistency (α = 0.992; Ω = 0.992), and the validity analyses confirmed that the dimensions measured distinct but related constructs. ChatGPT was reported as the most used tool (62.2%), followed by Gemini and Siri. The structural model indicated that emotional and cognitive dimensions substantially influenced ethical behavior (β = 0.413 and β = 0.567, respectively), whereas frequent use alone exhibited no significant effect (β = −0.128; p = 0.058). These results suggest that ethical engagement with AI is primarily driven by reflection and knowledge rather than habit. This study contributes to the literature by modeling how different learning dimensions shape ethical behavior in AI use and underscores the relevance of aligning academic practices with socially responsible uses of emerging technologies.

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Learning Natural Science Through Interactive Resources

2025 , Becerra García, Eulalia , Yánez Rueda, Hugo , Mora Rosales, José

Learning Natural Sciences through interactive resources enhances the understanding of complex concepts by offering visual and hands-on experiences. These tools allow students to explore natural phenomena, perform simulated experiments and visualize processes invisible in real life. Objective: Examine how interactive tools influence the retention of complex natural science concepts. Methodology: It follows a positivist paradigm, with a quantitative approach, a field study and a sample of 60 elementary school students to whom a questionnaire was applied to measure knowledge before and after applying the interactive resources. Results: A course was created within the Moodle virtual learning environment focused on improving the learning of Natural Sciences with interactive resources elaborated in the technological tools: powtoon, Phet Interactive Simulations and H5p Interactive with selected topics of natural sciences based on their pedagogical relevance and the capacity of concepts to be exploited with interactive simulators. Conclusions: Interactive resources were developed to improve natural science learning, with technological tools that made the contents more interactive, visual and accessible.

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