Diseño de un programa de capacitación docente en estrategias didácticas y técnicas de aprendizaje colaborativo (TAC) como herramienta de perfeccionamiento docente en beneficio de la comunidad educativa Frau Klier.
Thesis
Subjects > Education
Ibero-american International University > Teaching > Final Master Projects
Ibero-american International University > Teaching > Master's Final Projects
Closed
Spanish
El contexto mundial y la docencia en general, han propuesto nuevos retos en el año 2020, el efecto pandemia ha evidenciado falencias puntuales sobre las estrategias de los docentes para poder llegar al estudiantado de una manera asertiva, es por esta razón que como herramienta de perfeccionamiento y desarrollo continuo como profesionales y sobre todo como seres humanos que brinden calidad y calidez en la Unidad Educativa Frau Klier se ha propuesto en este proyecto, diseñar un programa de capacitación sobre estrategias y técnicas de aprendizaje colaborativo para la mejora del desempeño de los docentes de la Institución Educativa Frau Klier del distrito La Delicia , cantón Quito, provincia Pichincha, país Ecuador .En este sentido se tomaron consideraciones que brinden un apoyo más especializado a los estudiantes, aplicando metodologías que se ajusten a sus necesidades priorizando las destrezas en lugar de los contenidos, principalmente innovando en las técnicas de aprendizaje para así lograr conseguir desde los docentes la tan anhelada calidad educativa. El programa Maestros 4.0 será el resultado de este estudio que abordará desde su núcleo el aprendizaje constructivista social , aprendizaje colaborativo y Técnicas de aprendizaje colaborativo; donde el tipo de investigación por su naturaleza y contexto limitado dentro de la Unidad Educativa Frau Klier del distrito La Delicia , cantón Quito , provincia Pichincha ,país Ecuador, donde el estudio será deductivo descriptivo-exploratorio teniendo un enfoque cualitativo , que por las aspiraciones, y sobre todo el objetivo general de la metodología planteada será de Investigación acción participativa (IAP),para mejorar las prácticas dentro de la institución. Utilizando instrumentos como Focus Group, encuestas y entrevistas. Los resultados evidencian la utilidad de las técnicas y estrategias en el proceso de aprendizaje colaborativo que muestran la necesidad institucional de mejorar profesionalmente a su claustro docente. Por lo tanto, se presenta una propuesta de innovación que articula dimensiones tecnológicas y presenciales del proceso enseñanza-aprendizaje, es así que, se manifiesta la relevancia de planificar acertadamente las metodologías, estrategias y técnicas para garantizar el aprendizaje colaborativo y comprender que los elementos organizativos, pedagógicos y tecnológicos deben converger con el único objetivo de transformar la educación.
metadata
Chavez Montero, Gabriel Enrique
mail
cefk_gabrielchavezm@hotmail.com
(2022)
Diseño de un programa de capacitación docente en estrategias didácticas y técnicas de aprendizaje colaborativo (TAC) como herramienta de perfeccionamiento docente en beneficio de la comunidad educativa Frau Klier.
Master's thesis, UNSPECIFIED.
Abstract
El contexto mundial y la docencia en general, han propuesto nuevos retos en el año 2020, el efecto pandemia ha evidenciado falencias puntuales sobre las estrategias de los docentes para poder llegar al estudiantado de una manera asertiva, es por esta razón que como herramienta de perfeccionamiento y desarrollo continuo como profesionales y sobre todo como seres humanos que brinden calidad y calidez en la Unidad Educativa Frau Klier se ha propuesto en este proyecto, diseñar un programa de capacitación sobre estrategias y técnicas de aprendizaje colaborativo para la mejora del desempeño de los docentes de la Institución Educativa Frau Klier del distrito La Delicia , cantón Quito, provincia Pichincha, país Ecuador .En este sentido se tomaron consideraciones que brinden un apoyo más especializado a los estudiantes, aplicando metodologías que se ajusten a sus necesidades priorizando las destrezas en lugar de los contenidos, principalmente innovando en las técnicas de aprendizaje para así lograr conseguir desde los docentes la tan anhelada calidad educativa. El programa Maestros 4.0 será el resultado de este estudio que abordará desde su núcleo el aprendizaje constructivista social , aprendizaje colaborativo y Técnicas de aprendizaje colaborativo; donde el tipo de investigación por su naturaleza y contexto limitado dentro de la Unidad Educativa Frau Klier del distrito La Delicia , cantón Quito , provincia Pichincha ,país Ecuador, donde el estudio será deductivo descriptivo-exploratorio teniendo un enfoque cualitativo , que por las aspiraciones, y sobre todo el objetivo general de la metodología planteada será de Investigación acción participativa (IAP),para mejorar las prácticas dentro de la institución. Utilizando instrumentos como Focus Group, encuestas y entrevistas. Los resultados evidencian la utilidad de las técnicas y estrategias en el proceso de aprendizaje colaborativo que muestran la necesidad institucional de mejorar profesionalmente a su claustro docente. Por lo tanto, se presenta una propuesta de innovación que articula dimensiones tecnológicas y presenciales del proceso enseñanza-aprendizaje, es así que, se manifiesta la relevancia de planificar acertadamente las metodologías, estrategias y técnicas para garantizar el aprendizaje colaborativo y comprender que los elementos organizativos, pedagógicos y tecnológicos deben converger con el único objetivo de transformar la educación.
| Document Type: | Thesis (Master's) |
|---|---|
| Keywords: | Técnicas de aprendizaje colaborativo (TAC), investigación acción participativa (IAP), metodologías de aprendizaje, calidad educativa. |
| Subject classification: | Subjects > Education |
| Divisions: | Ibero-american International University > Teaching > Final Master Projects Ibero-american International University > Teaching > Master's Final Projects |
| Deposited: | 20 Oct 2023 23:30 |
| Last Modified: | 20 Oct 2023 23:30 |
| URI: | https://repositorio.unib.org/id/eprint/904 |
Actions (login required)
 |
View Object |
<a class="ep_document_link" href="/28580/1/fphys-17-1835464.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Background: Recovery after a training session or match is a key factor in injury prevention and sports performance. The purpose of this systematic review was to analyze and consolidate the available scientific evidence from the main databases on the use of infrared thermography in the assessment of fatigue, injury risk factors, and recovery in soccer players.Methods: The literature search was conducted following the PRISMA guidelines and the PICOS model until June 30, 2025, in the main scientific databases (ScienceDirect, EMBASE, Web of Science (WOS), Cochrane Library, SciELO, MEDLINE/PubMed, SPORTDiscus, and Scopus). The risk of bias and methodological quality were assessed using the Cochrane Handbook guidelines and the PEDro scale.”Results: The initial literature search yielded a total of 510 records. After applying the inclusion and exclusion criteria, the final sample consisted of 20 studies, which were of high methodological quality. The results showed the effects of infrared thermography in assessing fatigue, identifying injury risk factors, and monitoring recovery processes in soccer players. The studies also systematically reported the characterization of the population, the assessment methods used, the variables analyzed, the methodological design, the main results, and the effects of the intervention.Conclusions: Infrared thermography shows promise as a valid, reliable, and non-invasive tool for assessing skin temperature, reflecting temperature changes in response to physiological processes. It allows for the analysis of structural or metabolic fatigue and thermal asymmetries. Therefore, thermography could be used to design individualized recovery protocols.
Yehinson Barajas Ramón mail , Julio Calleja-González mail , José Luaces-Carreño mail , Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es,
Barajas Ramón
<a href="/28581/1/Environmental%20burden%20of%20fish%20in%20healthy%20and%20sustainable%20diets.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Environmental burden of fish in healthy and sustainable diets
Fish is widely promoted as part of healthy dietary patterns. The aim of this review was to summarise current literature on the environmental footprint of fish and its role within sustainable diets. Fish generally represents a minor share of total dietary environmental impacts, contributing to a smaller proportion of greenhouse-gas emissions (GHGe), land and water use than meat and other animal products. Several modelling studies showed that substituting meat with fish or increasing fish intake within optimised dietary patterns can reduce environmental impacts, although the magnitude varies by country, diet type, and fish species. However, some analyses reported increased GHGe associated with higher fish intake, especially in models ensuring nutritional quality. Overall, fish consumption is compatible with achieving nutritionally adequate and lower environmental impacts, although optimal match between environmental boundaries and nutritional needs is not always possible. These findings suggest that fish can play a constructive role in sustainable diets when integrated thoughtfully within broader dietary shifts.
Alberto Dolci mail , Alessandro Scuderi mail , Evelyn Frias-Toral mail , Leonardo de Jesús Hernández Cruz mail leonardo.hernandez@unib.org, Andrea Di Mauro mail , Fabrizio Furnari mail , Alice Rosi mail , Francesca Scazzina mail , Giuseppe Grosso mail ,
Dolci
<a href="/28319/1/s41598-026-45575-1_reference.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
A novel approach for disease and pests detection in potato production system based on deep learning
Vulnerability of potato crops to diseases and pest infestation can affect its quality and lead to significant yield losses. Timely detection of such diseases can help take effective decisions. For this purpose, a deep learning-based object detection framework is designed in this study to identify and classify major potato diseases and pests under real-world field conditions. A total of 2,688 field images were collected from two research farms in Punjab, Pakistan, across multiple growth stages in various seasonal conditions. Excluding 285 symptoms-free images from the earliest collection led to 2,403 images which were annotated into four biotic-stress classes: blight disease (n = 630), leaf spot disease (n = 370), leafroll virus (viral symptom complex; n = 888), and Colorado potato beetle (larvae/adults; n = 515), indicating class imbalance. Several state-of-the-art models were used including YOLOv8 variants (n/s/m), YOLOv7, YOLOv5, and Faster R-CNN, and the results are discussed in relation to recent potato disease classification studies involving cropped leaf images. Stratified splitting (70% training, 20% validation, 10% testing) was applied to preserve class distribution across all subsets. YOLOv8-medium achieve the best performance with mean average precision (mAP)@0.5 of 98% on the held-out test images. Results for stable 5-fold cross-validation show a mean mAP@0.5 of 97.8%, which offers a balance between accuracy and inference time. Model robustness was evaluated using 5-fold cross-validation and repeated training with different random seeds, showing a low variance of ±0.4% mAP. Results demonstrate promising outcomes under the real-world field conditions, while, broader cross-region and cross-season validation is intended for the future.
Ahmed Abbas mail , Saif Ur Rehman mail , Khalid Mahmood mail , Santos Gracia Villar mail santos.gracia@uneatlantico.es, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Aseel Smerat mail , Imran Ashraf mail ,
Abbas
<a href="/28569/1/s12870-026-08847-6_reference.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
The Polyphagous Shot Hole Borer (PSHB) is a highly invasive beetle that has been spreading like an epidemic across agricultural and forestry landscapes in recent years. Its rapid and destructive spread has turned it into a major global threat, causing widespread damage that continues to grow with time. Countries like South Africa, the United States, and Australia have implemented extensive measures to control the spread of PSHB, including the establishment of specialized agricultural support centers for early detection. However, there is still a strong need to make PSHB detection more accessible, allowing even non-experts to easily identify infections at an early stage. Artificial Intelligence (AI) has shown great promise in plant disease detection, but a major challenge in the case of PSHB was the lack of a suitable dataset for training AI models. In the proposed work, we first created a dedicated dataset by collecting images of trees infected with PSHB. We applied a range of preprocessing techniques to refine the dataset and prepare it for AI applications. Building on this, we developed a novel AI-based method, where we trained a deep learning model using a multi-convolutional layer network combined with a Fourier transformation layer. Additionally, an attention mechanism and advanced feature extraction techniques were incorporated to further boost model performance. As a result, the proposed approach achieved an impressive top accuracy of 92.3% in detecting PSHB infections, showing the potential of AI to offer a simple, efficient, and highly accurate solution for early disease detection.
Rabbiya Younas mail , Hafiz Muhammad Raza ur Rehman mail , Gyu Sang Choi mail , Ángel Gabriel Kuc Castilla mail angel.kuc@uneatlantico.es, Carlos Eduardo Uc Ríos mail carlos.uc@unini.edu.mx, Imran Ashraf mail ,
Younas
<a href="/28572/1/s41598-026-47906-8.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Correction: Enhancing fault detection in new energy vehicles via novel ensemble approach
In the original version of this Article, Umair Shahid was incorrectly listed as a corresponding author. The correct corresponding authors for this Article are Imran Ashraf and Kashif Munir. Correspondence and request for materials should be addressed to ashrafimran@live.com and kashif.munir@kfueit.edu.pk.
Iqra Akhtar mail , Mahnoor Nabeel mail , Umair Shahid mail , Kashif Munir mail , Ali Raza mail , Irene Delgado Noya mail irene.delgado@uneatlantico.es, Santos Gracia Villar mail santos.gracia@uneatlantico.es, Imran Ashraf mail ,
Akhtar