Search results for "e learning"
showing 10 items of 2703 documents
Personal variables, motivation and avoidance learning strategies in undergraduate students
2014
Abstract This study examines the relationships among students' personal variables, their initial motivation and the avoidance learning strategies they used during the teaching/learning process followed in the Educational Psychology subject matter. The sample comprised 195 Spanish undergraduate students who studied Educational Psychology. A questionnaire was administered at the beginning of the academic year to measure students' personal variables and their initial motivation, while another was administered at the end of the academic year to measure students' involvement in their learning process through the avoidance strategies they used. The data analysis was done by using structural equat…
The pineal complex in Roman high avoidance and Roman low avoidance rats.
1990
Previous studies have shown that the pineal gland of Roman high avoidance (RHA/Verh) rats is larger than that of Roman low avoidance rats (RLA/Verh). In the present study measurement of enzyme activities (serotonin-N-acetyl-transferase, hydroxyindole-O-methyltransferase) revealed that pineals of RHA/Verh rats are twice as active in melatonin production than pineals of RLA/Verh rats. Indoleamine content was also higher in RHA/Verh rats, whereas noradrenaline content was the same in both lines. When values were expressed per mg protein, these differences disappeared except for N-acetyl-serotonin and noradrenaline which were higher or lower in RHA/Verh rats, respectively. Both lines had higher…
Mapping landscape canopy nitrogen content from space using PRISMA data
2021
Abstract Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively. Moreover, the high-priority mission candidate Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is expected to globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. Thanks to the provision of contiguous visible-to-shortwave infrared spectral data, hyperspectral missions open enhanced …
Active learning strategies for the deduplication of electronic patient data using classification trees.
2012
Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…
Active Learning for Monitoring Network Optimization
2012
Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Discovering single classes in remote sensing images with active learning
2012
When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…
Improving active learning methods using spatial information
2011
Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning. © 2011 IEEE.
Strategies for Active Learning to Improve Student Learning and Attitudes Towards Physics
2021
Over the last several years, active learning methods and strategies have received considerable attention from the educational community and are commonly presented in the related literature as a credible solution to the reported lack of efficacy of more “traditional” educative approaches. Research has shown that a possible factor is the strongly contextualized nature of active learning that focuses on the interdependence of situation and cognition. In this paper, we report the results of a Symposium with different contributions in the field of research on active learning. We start with a system analysis of the mental processes involved in learning physics which explains how active learning i…
Active Learning Methods and Strategies to Improve Student Conceptual Understanding: Some Considerations from Physics Education Research
2020
Active learning methods and strategies are credited to be an important means for the development of student cognitive skills. This paper describes some forms of active learning common in Physics Education and briefly introduces some of the pedagogical and psychological theories on the basis of active learning. Then, some evidence for active learning effectiveness in developing students’ critical cognitive skills and improving their conceptual understanding are examined. An example study regarding the effectiveness of an Inquiry-based learning approach in helping students to build mechanisms of functioning and explicative models, and to identify common aspects in apparently different phenome…