Search results for "learning"
showing 10 items of 6669 documents
Blended Learning als Spielfeld für Learning Analytics und Educational Data Mining
2020
Der Einsatz digitaler Lernformate im Blended Learning bietet demnach Chancen in mindestens zwei Bereichen. Zum einen konnen digitale Lernformate direkt die Lernprozesse von Studierenden gunstig beeinflussen, ihre Leistungen verbessern und zudem positive Effekte auf vielen weiteren Ebenen wie der Motivation oder des Selbstkonzeptes bewirken. Zum anderen generieren digitale Lernformate eine Fulle von Daten in vielfaltiger Gestalt. Studierende erzeugen bei der Arbeit mit digitalen Werkzeugen Nutzungsdaten, wie Verweildauern und Aktivitatsprofile, sie produzieren Leistungsdaten aus digitalen Aufgaben, sie hinterlassen Textbeitrage in Foren und Chats. All diese Daten konnen genutzt werden, um mi…
El proyecto de investigación social como instrumento integrador de la praxis para los futuros/as trabajadores/as sociales
2015
El presente trabajo muestra los resultados de una investigación-intervención aplicada a los alumnos de cuarto curso de Grado en Trabajo Social. En este documento se articula una metodología de enseñanza colaborativa, significativa y crítica a partir de las evidencias de la práctica del Trabajo Social. Como conclusiones de este estudio se justifica el uso de la metodología Blended Learning en el espacio universitario. Se evidencia como con la participación y cooperación colectiva se favorece el desarrollo de competencias investigadoras, y se señala el proyecto de investigación social como herramienta que permite vincular las prácticas externas del alumnado con los elementos teóricos de la di…
Exploring the work in the blogosphere: the paradox of collaborative learning
2016
Amb l’objectiu de solucionar diversos problemes que sorgiren en la posada en practica d’una experiencia d’innovacio basada en la creacio d’una blogosfera, es porta a terme una investigacio educativa i qualitativa a partir de la col·laboracio docent i de les opinions de l’alumnat. A mes dels aspectes positius, es detectaren dificultats amb la gestio del treball en equipo i de familiaritzacio amb la ferramenta a les que els propis estudiants proposaren diverses solucions. Abordar aquesta circumstancia de forma col·laborativa i donant veu a l’alumnat ha permes que l’experiencia concloguera exitosament, resultant ser una bona practica educativa.
Constructivism in Science Education: The Need for a Clear Line of Demarcation
2003
Some voices have recently begun to question the constructivist positions, which have been considered the most important contribution of the last decades in science education. It could be thought then, that the“constructivist consensus” might just be a new fashion that would once again lead us back to the immovable reception model of science learning. This questions, at the same time, the idea of an advance in the field of science education towards the construction of a coherent body of knowledge.
New trends in science education
1996
I intend to review the main contributions from the impressive developments made in science education research during the last decade. These developments have made the construction of a coherent body of knowledge possible allowing us to expect a significant improvement in the science teaching/learning process. I shall refer, in particular, to the new trends in science education research, both in the domain of science learning and science teacher‐training.
Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete
2022
Reinforced concrete bond strength deterioration is one of the most serious problems in the construction industry. It is one of the most common factors impacting structural deterioration and the major cause of premature decadence of reinforced concrete structures. Therefore, developing an accurate model with the lowest variance and high reliability for the bond strength of corroded reinforced concrete is very important. The current work evaluates the efficiency of convolution-based ensemble learning algorithms. To address these issues, convolution-based ensemble learning models are developed using a database collected from the previous experimental studies of relative bond strength for corro…
Processing of rock core microtomography images: Using seven different machine learning algorithms
2016
The abilities of machine learning algorithms to process X-ray microtomographic rock images were determined. The study focused on the use of unsupervised, supervised, and ensemble clustering techniques, to segment X-ray computer microtomography rock images and to estimate the pore spaces and pore size diameters in the rocks. The unsupervised k-means technique gave the fastest processing time and the supervised least squares support vector machine technique gave the slowest processing time. Multiphase assemblages of solid phases (minerals and finely grained minerals) and the pore phase were found on visual inspection of the images. In general, the accuracy in terms of porosity values and pore…
Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study
2014
International audience; Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of a fall detection system based on such a smart camera, which allows to reduce the development time compared to standard approaches. Founded on a supervised classification approach, we propose a HW/SW implementation to detect falls in a home environment using a single camera and an optimized descriptor adapted to real-time t…
Alternating model trees
2015
Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose a method for growing alternating model trees, a form of option tree for regression problems. The motivation is that alternating decision trees achieve high accuracy in classification problems because they represent an ensemble classifier as a single tree structure. As in alternating decision trees for classification, our alternating model trees for regression contain splitter and prediction nodes, but we use simple linear regression functions as opposed to constant predicto…
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
2012
During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…