Síncrono / asíncrono. Convergencia y alternancia en la enseñanza futura del diseño

Francisco Gerardo Toledo Ramirez (2023, [Capítulo de libro])

La cuarentena sanitaria de los últimos dos años (COVID-19) obligó a “rediseñar”, “digitalizar” o “virtualizar” nuestros cursos y estilos de enseñanza en tiempo récord para “adaptarlas” al “formato virtual a distancia” (online). La profusión de comillas en las líneas anteriores tiene la intención de señalar el carácter incierto o erróneo que ciertos términos-fetiche adquirieron en el proceso. Es importante desmitificar esas figuras de la expresión que se elevaron casi al nivel de pseudo-epistemes (presuntamente novedosas) para la enseñanza del Diseño. Ese tema lo abordo con mayor amplitud en una nueva investigación, recientemente registrada en la UAM. En este texto esbozo (en forma algo lúdica) pero seria y breve a la vez, la conveniencia de tal desmitificación y avanzo en el delineamiento de un modelo de la alternancia y convergencia de recursos pedagógico-didácticos síncronos y asíncronos, mediante la tecnología-red digital, como un elemento estratégico para la educación futura en Diseño.

The health quarantine of the last 2 years (COVID-19) forced us to “redesign”, “digitize” or “virtualize” our courses and teaching styles in record time to “adapt” them to the “virtual format” “at a distance” (online). The profusion of quotation marks in the previous lines is intended to indicate the uncertain or erroneous character that certain fetish-terms acquired in the process. It is important to demystify those figures of expression that have risen almost to the level of pseudo-epistemes (presumably novel) for teaching design. I address this topic more fully in a new investigation, recently registered at the UAM. In this text I outline (in a somewhat playful way) but serious and brief at the same time, the convenience of such “demystification” and I advance in the outline of a model of alternation and convergence of synchronous and asynchronous pedagogical-didactic resources, through technology. -digital network, as a strategic element for future design education.

Síncrono, asíncrono, virtualidad, presencialidad, diseño, remoto. Synchronous, asynchronous, virtuality, face-to-face, design, remote. Design--Study and teaching, Higher. Distance education. Blended learning. Universidad Autónoma Metropolitana. Unidad Azcapotzalco. División de Ciencias y Artes para el Diseño. Artes gráficas. Educación a Distancia. Aprendizaje combinado. NK1170 HUMANIDADES Y CIENCIAS DE LA CONDUCTA CIENCIAS DE LAS ARTES Y LAS LETRAS

Multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

Osval Antonio Montesinos-Lopez Jose Crossa Francisco Javier Martin Vallejo (2018, [Artículo])

Deep Learning Genomic Prediction Bayesian Modeling Shared Data Resources CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BAYESIAN THEORY RESOURCES DATA BREEDING PROGRAMMES

Statistical machine-learning methods for genomic prediction using the SKM library

Osval Antonio Montesinos-Lopez Brandon Alejandro Mosqueda González Jose Crossa (2023, [Artículo])

Sparse Kernel Methods R package Statistical Machine Learning Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION MACHINE LEARNING GENOMICS METHODS

A Novel Technique for Classifying Bird Damage to Rapeseed Plants Based on a Deep Learning Algorithm.

Ali Mirzazadeh Afshin Azizi Yousef Abbaspour_Gilandeh José Luis Hernández-Hernández Mario Hernández Hernández Iván Gallardo Bernal (2021, [Artículo])

Estimation of crop damage plays a vital role in the management of fields in the agricultura sector. An accurate measure of it provides key guidance to support agricultural decision-making systems. The objective of the study was to propose a novel technique for classifying damaged crops based on a state-of-the-art deep learning algorithm. To this end, a dataset of rapeseed field images was gathered from the field after birds¿ attacks. The dataset consisted of three classes including undamaged, partially damaged, and fully damaged crops. Vgg16 and Res-Net50 as pre-trained deep convolutional neural networks were used to classify these classes. The overall classification accuracy reached 93.7% and 98.2% for the Vgg16 and the ResNet50 algorithms, respectively. The results indicated that a deep neural network has a high ability in distinguishing and categorizing different image-based datasets of rapeseed. The findings also revealed a great potential of Deep learning-based models to classify other damaged crops.

rapeseed classification damaged crops deep neural networks INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Competencia socioemocional y toma de decisiones en el rendimiento académico de estudiantes universitarios

MAYRA DELGADO VILLALOBOS (2023, [Tesis de doctorado])

Las emociones sociales forman parte de la complejidad interna de una sociedad donde

confluyen niveles de estructura social: las interacciones entre sus individuos, los patrones

de relación entre ellos y sus principios de organización. Las emociones sociales subyacen

a esta complejidad e incluyen mecanismos de autorregulación que permiten a los

individuos desarrollar habilidades socioemocionales para evaluar cuándo y con quién

cooperar o competir, regular las respuestas emocionales y el comportamiento en

situaciones sociales, mantener relaciones de largo plazo, favorecer la prosocialidad y la

cohesión grupal. Estas habilidades son fundamentales en nuestros entornos culturales

dinámicos. Por ello, la OECD las considera habilidades del siglo XXI.

Desde una perspectiva interdisciplinar con énfasis en la cognición social, en la

presente investigación se revisó la importancia y la función de las emociones sociales, y

con base en los diferentes niveles de complejidad social se propone una distinción entre

habilidades y competencias socioemocionales. También se revisaron diversos enfoques

teóricos sobre estas competencias, así como la metodología para su evaluación en la

educación universitaria. Asimismo, se realizó un estudio exploratorio con un diseño

transversal y la muestra se conformó por 104 estudiantes universitarios. El modelo teórico

propuesto se probó mediante ecuaciones estructurales, encontrándose diferencias

significativas entre el compromiso académico y el rendimiento académico, la resiliencia

y el razonamiento.

Social emotions are part of the internal complexity of a society where levels of social

structure converge: the interactions between its individuals, the relationships patterns

between them and their organizational principles. Social emotions underlie this

complexity and include self-regulation mechanisms that allow individuals to develop

socioemotional skills to assess when and with whom to cooperate or compete, regulate

emotional responses and behavior in social situations, maintain long-term relationships,

promote prosociality and group cohesion. These skills are essential in our dynamic

cultural environments. For this reason, the OECD considers them 21st century skills.

From an interdisciplinary perspective with an emphasis on social cognition, this

research reviewed the importance and function of social emotions, and based on the

different levels of social complexity, a distinction between socio-emotional skills and

competencies is proposed. Various theoretical approaches to these competencies were

also reviewed, as well as the methodology for their evaluation in university education.

Likewise, an exploratory study was carried out with a cross-sectional design and the

sample consisted of 104 university students. The proposed theoretical model was tested

using structural equations, finding significant differences between academic commitment

and academic performance, resilience and reasoning.

HUMANIDADES Y CIENCIAS DE LA CONDUCTA PEDAGOGÍA cognición social, desarrollo socioemocional, competencias socioemocionales, evaluación socioemocional y aprendizaje socioemocional. social cognition, social-emotional development, social-emotional competencies, social-emotional assessment and social-emotional learning

Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval Cely Celene Ronquillo Chávez (2023, [Artículo, Artículo])

 

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates.

Acceso a la educación Aprendizaje en línea Educación a distancia Formación de docentes Tecnología educacional HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Access to education online learning distance education teacher education educational technology

Una articulación fundamental: la emancipación

Nicolás Amoroso Boelcke (2023, [Capítulo de libro])

El concepto, la circunstancia de la enseñanza que aquí abordaremos, tiene el propósito de restituir ciertas situaciones que corresponden al propio ejercicio de la instrucción y a aquellas otras que hablan del acontecer, por ello el trabajo. Tiene las variables tanto de la experiencia real como de las otras sobre las que se han escrito, una de ellas, al final, plantea una situación paradójica que se refiere a la del maestro ignorante que, básicamente, tiene como propósito mostrar que el conocimiento es algo que está en el alumno y que el docente debe limitarse a tratar de que aflore y se exprese de la mejor manera posible. Nos habla de la independencia y de las características que puede tener una educación rigurosa y rígida, en contraposición con una más flexible. Lo mismo sucede con el pensamiento desde nuestra América, de la educación dependiente a una educación libertaria.

The concept, the circumstance of the teaching that we will address here has the purpose of restoring certain situations that correspond to the exercise itself as those others that speak of the happening for it the work. It has the variables of real experience as of the others about which they have been written, one of them, in the end, poses a paradoxical situation that refers to that of the ignorant teacher that, basically, has the purpose of showing that knowledge is something that is in the student and that the teacher must limit himself to trying to bring it out and express itself in the best possible way. It tells us about independence and the characteristics that a rigorous and rigid education can have with a more flexible one and the same happens with the thought from our America, from dependent education to a libertarian education.

Emancipación, docencia, alumnos, investigación, juego. Emancipation, teaching, students, research, play. Interaction analysis in education. Microteaching. Teacher-student relationships. Transformative learning. Educational innovations. Análisis de interacción en la educación. Relaciones maestro-estudiante. Aprendizaje transformador. Cambio educativo. LB1034 HUMANIDADES Y CIENCIAS DE LA CONDUCTA PEDAGOGÍA TEORÍA Y MÉTODOS EDUCATIVOS

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Multimodal deep learning methods enhance genomic prediction of wheat breeding

Carolina Rivera-Amado Francisco Pinto Francisco Javier Pinera-Chavez David González-Diéguez Matthew Paul Reynolds Paulino Pérez-Rodríguez Huihui Li Osval Antonio Montesinos-Lopez Jose Crossa (2023, [Artículo])

Conventional Methods Genomic Prediction Accuracy Deep Learning Novel Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT BREEDING MACHINE LEARNING METHODS MARKER-ASSISTED SELECTION

Situated learning through local stories: positioning socio-ecological concerns, knowledge and practices in school

Rosa Guadalupe Mendoza Zuany Juan Carlos A. Sandoval Rivera Paula Martínez Bautista (2023, [Artículo, Artículo])

The article analyzes the importance of the local stories, which contain concerns, knowledge and practices to look after the socio-ecological environment, to trigger situated and pertinent teaching and learning processes in primary education in rural and indigenous contexts in Veracruz, Mexico. In particular, it focuses on the stories about care in the framework of a deep socio-ecological crisis in two Nahua communities of the Huasteca region. Interview-conversations were carried out with community actors in the two communities in which 32 stories emerged. The analysis allowed the identification of socio-ecological concerns of the community, characteristics of the stories that show their potential in the learning processes, as well as types of knowledge and practices that are rarely considered in the classroom, which are capable of being linked to curricular content, in order to contribute to reflection and action on the socio-ecological crisis of the communities.

aprendizaje narración de historias medio ambiente ambiente socio-cultural escuela rural CIENCIAS SOCIALES; HUMANIDADES Y CIENCIAS DE LA CONDUCTA CIENCIAS SOCIALES HUMANIDADES Y CIENCIAS DE LA CONDUCTA Learning story telling environment socio-cultural environment rural school