Pautas orientadoras para la implementación curricular de la asignatura Cálculo Diferencial del Plan Común de Ingeniería Civil en tiempos pospandémicos (Universidad Mayor, Chile)
Thesis Subjects > Teaching Ibero-american International University > Research > Doctoral Thesis Cerrado Español El proceso de enseñanza-aprendizaje en la educación superior es crucial para desarrollar competencias académicas, fomentar el pensamiento crítico y preparar a los estudiantes con habilidades necesarias para su éxito profesional y contribución a la sociedad. Es por ello, la importancia de adaptar el currículum y las metodologías para abordar las dificultades en el aprendizaje, en distintos escenarios, dado lo vivido en pandemia, sobre todo en el área de matemáticas; destacándose la relevancia en la transición hacia la sostenibilidad y la necesidad de transformar los modelos de gestión y gobernanza para alinearse con los objetivos de desarrollo sostenible. En este contexto se realizó una investigación en la Universidad Mayor, Chile; con el propósito de generar pautas orientadoras para la implementación curricular de la asignatura Cálculo Diferencial del Plan Común de Ingeniería Civil en tiempos pospandémicos. La investigación en general se diseñó a partir del paradigma pragmático, asumiendo una metodología mixta. La muestra estuvo compuesta por 368 estudiantes y 12 docentes; los estudiantes participaron respondiendo el cuestionario CEVEAPEU referidos a las estrategias de aprendizaje, y los docentes fue-ron los jueces expertos que valoraron las pautas orientadoras diseñadas. Los resultados y conclusiones más relevantes incluyen una visión holística del estado actual del tema, analizando estudios sobre el impacto de las estrategias de aprendizaje en el rendimiento académico. Por otro lado, se generaron las pautas orientadoras, con los resultados empíricos cuantitativos y pruebas estadísticas que demuestran un impacto positivo de algunas estrategias de aprendizaje sobre el rendimiento académico de los estudiantes. Finalmente, las pautas fueron valoradas de manera satisfactoria por los jueces expertos. metadata Vega Rojas, Mabel Rossana mail mabel.vega@doctorado.unini.edu.mx (2024) Pautas orientadoras para la implementación curricular de la asignatura Cálculo Diferencial del Plan Común de Ingeniería Civil en tiempos pospandémicos (Universidad Mayor, Chile). Doctoral thesis, UNSPECIFIED.
Full text not available from this repository.Abstract
El proceso de enseñanza-aprendizaje en la educación superior es crucial para desarrollar competencias académicas, fomentar el pensamiento crítico y preparar a los estudiantes con habilidades necesarias para su éxito profesional y contribución a la sociedad. Es por ello, la importancia de adaptar el currículum y las metodologías para abordar las dificultades en el aprendizaje, en distintos escenarios, dado lo vivido en pandemia, sobre todo en el área de matemáticas; destacándose la relevancia en la transición hacia la sostenibilidad y la necesidad de transformar los modelos de gestión y gobernanza para alinearse con los objetivos de desarrollo sostenible. En este contexto se realizó una investigación en la Universidad Mayor, Chile; con el propósito de generar pautas orientadoras para la implementación curricular de la asignatura Cálculo Diferencial del Plan Común de Ingeniería Civil en tiempos pospandémicos. La investigación en general se diseñó a partir del paradigma pragmático, asumiendo una metodología mixta. La muestra estuvo compuesta por 368 estudiantes y 12 docentes; los estudiantes participaron respondiendo el cuestionario CEVEAPEU referidos a las estrategias de aprendizaje, y los docentes fue-ron los jueces expertos que valoraron las pautas orientadoras diseñadas. Los resultados y conclusiones más relevantes incluyen una visión holística del estado actual del tema, analizando estudios sobre el impacto de las estrategias de aprendizaje en el rendimiento académico. Por otro lado, se generaron las pautas orientadoras, con los resultados empíricos cuantitativos y pruebas estadísticas que demuestran un impacto positivo de algunas estrategias de aprendizaje sobre el rendimiento académico de los estudiantes. Finalmente, las pautas fueron valoradas de manera satisfactoria por los jueces expertos.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | estrategias de aprendizaje; rendimiento académico; enseñanza superior; práctica pedagógica; cuestionario; educación para el desarrollo sostenible, enseñanza de las matemáticas; innovación educativa |
| Subjects: | Subjects > Teaching |
| Divisions: | Ibero-american International University > Research > Doctoral Thesis |
| Date Deposited: | 02 Dec 2024 23:30 |
| Last Modified: | 02 Dec 2024 23:30 |
| URI: | https://repositorio.unini.edu.mx/id/eprint/10168 |
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Detecting hate in diversity: a survey of multilingual code-mixed image and video analysis
The proliferation of damaging content on social media in today’s digital environment has increased the need for efficient hate speech identification systems. A thorough examination of hate speech detection methods in a variety of settings, such as code-mixed, multilingual, visual, audio, and textual scenarios, is presented in this paper. Unlike previous research focusing on single modalities, our study thoroughly examines hate speech identification across multiple forms. We classify the numerous types of hate speech, showing how it appears on different platforms and emphasizing the unique difficulties in multi-modal and multilingual settings. We fill research gaps by assessing a variety of methods, including deep learning, machine learning, and natural language processing, especially for complicated data like code-mixed and cross-lingual text. Additionally, we offer key technique comparisons, suggesting future research avenues that prioritize multi-modal analysis and ethical data handling, while acknowledging its benefits and drawbacks. This study attempts to promote scholarly research and real-world applications on social media platforms by acting as an essential resource for improving hate speech identification across various data sources.
Hafiz Muhammad Raza Ur Rehman mail , Mahpara Saleem mail , Muhammad Zeeshan Jhandir mail , Eduardo René Silva Alvarado mail eduardo.silva@funiber.org, Helena Garay mail helena.garay@uneatlantico.es, Imran Ashraf mail ,
Raza Ur Rehman
<a href="/17794/1/s41598-025-95836-8.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Accurate solar and photovoltaic (PV) power forecasting is essential for optimizing grid integration, managing energy storage, and maximizing the efficiency of solar power systems. Deep learning (DL) models have shown promise in this area due to their ability to learn complex, non-linear relationships within large datasets. This study presents a systematic literature review (SLR) of deep learning applications for solar PV forecasting, addressing a gap in the existing literature, which often focuses on traditional ML or broader renewable energy applications. This review specifically aims to identify the DL architectures employed, preprocessing and feature engineering techniques used, the input features leveraged, evaluation metrics applied, and the persistent challenges in this field. Through a rigorous analysis of 26 selected papers from an initial set of 155 articles retrieved from the Web of Science database, we found that Long Short-Term Memory (LSTM) networks were the most frequently used algorithm (appearing in 32.69% of the papers), closely followed by Convolutional Neural Networks (CNNs) at 28.85%. Furthermore, Wavelet Transform (WT) was found to be the most prominent data decomposition technique, while Pearson Correlation was the most used for feature selection. We also found that ambient temperature, pressure, and humidity are the most common input features. Our systematic evaluation provides critical insights into state-of-the-art DL-based solar forecasting and identifies key areas for upcoming research. Future research should prioritize the development of more robust and interpretable models, as well as explore the integration of multi-source data to further enhance forecasting accuracy. Such advancements are crucial for the effective integration of solar energy into future power grids.
Oussama Khouili mail , Mohamed Hanine mail , Mohamed Louzazni mail , Miguel Ángel López Flores mail miguelangel.lopez@uneatlantico.es, Eduardo García Villena mail eduardo.garcia@uneatlantico.es, Imran Ashraf mail ,
Khouili
<a href="/17569/1/Food%20Frontiers%20-%202025%20-%20Romero%E2%80%90Marquez%20-%20Olive%20Leaf%20Extracts%20With%20High%20%20Medium%20%20or%20Low%20Bioactive%20Compounds%20Content.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Alzheimer's disease (AD) involves β-amyloid plaques and tau hyperphosphorylation, driven by oxidative stress and neuroinflammation. Cyclooxygenase-2 (COX-2) and acetylcholinesterase (AChE) activities exacerbate AD pathology. Olive leaf (OL) extracts, rich in bioactive compounds, offer potential therapeutic benefits. This study aimed to assess the anti-inflammatory, anti-cholinergic, and antioxidant effects of three OL extracts (low, mid, and high bioactive content) in vitro and their protective effects against AD-related proteinopathies in Caenorhabditis elegans models. OL extracts were characterized for phenolic composition, AChE and COX-2 inhibition, as well as antioxidant capacity. Their effects on intracellular and mitochondrial reactive oxygen species (ROS) were tested in C. elegans models expressing human Aβ and tau proteins. Gene expression analyses examined transcription factors (DAF-16, skinhead [SKN]-1) and their targets (superoxide dismutase [SOD]-2, SOD-3, GST-4, and heat shock protein [HSP]-16.2). High-OL extract demonstrated superior AChE and COX-2 inhibition and antioxidant capacity. Low- and high-OL extracts reduced Aβ aggregation, ROS levels, and proteotoxicity via SKN-1/NRF-2 and DAF-16/FOXO pathways, whereas mid-OL showed moderate effects through proteostasis modulation. In tau models, low- and high-OL extracts mitigated mitochondrial ROS levels via SOD-2 but had limited effects on intracellular ROS levels. High-OL extract also increased GST-4 levels, whereas low and mid extracts enhanced GST-4 levels. OL extracts protect against AD-related proteinopathies by modulating oxidative stress, inflammation, and proteostasis. High-OL extract showed the most promise for nutraceutical development due to its robust phenolic profile and activation of key antioxidant pathways. Further research is needed to confirm long-term efficacy.
Jose M. Romero‐Marquez mail , María D. Navarro‐Hortal mail , Alfonso Varela‐López mail , Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Juan G. Puentes mail , Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es, Cristina Sánchez‐González mail , Jianbo Xiao mail , Roberto García‐Ruiz mail , Sebastián Sánchez mail , Tamara Y. Forbes‐Hernández mail , José L. Quiles mail jose.quiles@uneatlantico.es,
Romero‐Marquez
<a class="ep_document_link" href="/17570/1/eFood%20-%202025%20-%20Navarro%E2%80%90Hortal%20-%20Effects%20of%20a%20Garlic%20Hydrophilic%20Extract%20Rich%20in%20Sulfur%20Compounds%20on%20Redox%20Biology%20and.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Garlic is a horticultural product highly valued for its culinary and medicinal attributes. The aim of this study was to evaluate the composition of a garlic hydrophilic extract as well as the influence on redox biology, Alzheimer's Disease (AD) markers and aging, using Caenorhabditis elegans as experimental model. The extract was rich in sulfur compounds, highlighting the presence of other compounds like phenolics, and the antioxidant property was corroborated. Regarding AD markers, the acetylcholinesterase inhibitory capacity was demonstrated in vitro. Although the extract did not modify the amyloid β-induced paralysis degree, it was able to improve, in a dose-dependent manner, some locomotive parameters affected by the hyperphosphorylated tau protein in C. elegans. It could be related to the effect found on GFP-transgenic stains, mainly regarding to the increase in the gene expression of HSP-16.2. Moreover, an initial investigation into the aging process revealed that the extract successfully inhibited the accumulation of intracellular and mitochondrial reactive oxygen species in aged worms. These results provide valuable insights into the multifaceted impact of garlic extract, particularly in the context of aging and neurodegenerative processes. This study lays a foundation for further research avenues exploring the intricate molecular mechanisms underlying garlic effects and its translation into potential therapeutic interventions for age-related neurodegenerative conditions.
María D. Navarro‐Hortal mail , Jose M. Romero‐Marquez mail , Johura Ansary mail , Cristina Montalbán‐Hernández mail , Alfonso Varela‐López mail , Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Jianbo Xiao mail , Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es, Cristina Sánchez‐González mail , Tamara Y. Forbes‐Hernández mail , José L. Quiles mail jose.quiles@uneatlantico.es,
Navarro‐Hortal
<a class="ep_document_link" href="/17572/1/s12909-025-07070-5.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Background In recent years, medical education has increasingly embraced gamification as a method for teaching clinical skills. In Peru, social isolation resulting from the COVID-19 pandemic forced universities and academic institutions to restructure their teaching methods, while there are no reports about the impact of this strategies in Peruvian students. In this study we evaluated the feasibility and patterns of use of a novel video game based didactic activity in undergraduate students from a School of Medicine in Peru. Method We conducted a retrospective pilot study in medical students who used the Full Code Medical Simulation platform. We retrieved scoring data obtained from this platform for selected cases of clinical courses with an appropriate number of users [clinical medicine (CM) I (7 cases), CM II (17 cases), surgery I (6 cases) and surgery II (6 cases)]. cases)]. We also evaluated patterns of use and the association between academic performance and the Full Code scores. Results A total of 590 students were included in the study. We found a direct correlation between the student’s course grade and Full Code score in all courses (CM I: p < 0.001, CM II: p < 0.05, Surgery I: p < 0.05 and Surgery II: p < 0.05). CM II course students who dedicated more time to completing cases received better grades (p < 0.05). The pattern of use of Full code were similar in students regardless their academic performance. In addition, students with higher academic performance were more likely to have higher scores in the platform (p < 0.001). Conclusion The use of gamification in clinical simulation was highly feasible in students of medicine regardless their academic performance. Prospective and interventional studies are needed to assess if the Full Code platform directly affect the learning outcomes.
Maria Amalia Salafia mail , María Elena Perez-Ochoa mail ,
Salafia