907 resultados para Motivation. English learning task. Interactive Whiteboard
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INTRODUCTION: Inhibitory control refers to our ability to suppress ongoing motor, affective or cognitive processes and mostly depends on a fronto-basal brain network. Inhibitory control deficits participate in the emergence of several prominent psychiatric conditions, including attention deficit/hyperactivity disorder or addiction. The rehabilitation of these pathologies might therefore benefit from training-based behavioral interventions aiming at improving inhibitory control proficiency and normalizing the underlying neurophysiological mechanisms. The development of an efficient inhibitory control training regimen first requires determining the effects of practicing inhibition tasks. METHODS: We addressed this question by contrasting behavioral performance and electrical neuroimaging analyses of event-related potentials (ERPs) recorded from humans at the beginning versus the end of 1 h of practice on a stop-signal task (SST) involving the withholding of responses when a stop signal was presented during a speeded auditory discrimination task. RESULTS: Practicing a short SST improved behavioral performance. Electrophysiologically, ERPs differed topographically at 200 msec post-stimulus onset, indicative of the engagement of distinct brain network with learning. Source estimations localized this effect within the inferior frontal gyrus, the pre-supplementary motor area and the basal ganglia. CONCLUSION: Our collective results indicate that behavioral and brain responses during an inhibitory control task are subject to fast plastic changes and provide evidence that high-order fronto-basal executive networks can be modified by practicing a SST.
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Glucose-dependent insulinotropic polypeptide (GIP) is a key incretin hormone, released from intestine after a meal, producing a glucose-dependent insulin secretion. The GIP receptor (GIPR) is expressed on pyramidal neurons in the cortex and hippocampus, and GIP is synthesized in a subset of neurons in the brain. However, the role of the GIPR in neuronal signaling is not clear. In this study, we used a mouse strain with GIPR gene deletion (GIPR KO) to elucidate the role of the GIPR in neuronal communication and brain function. Compared with C57BL/6 control mice, GIPR KO mice displayed higher locomotor activity in an open-field task. Impairment of recognition and spatial learning and memory of GIPR KO mice were found in the object recognition task and a spatial water maze task, respectively. In an object location task, no impairment was found. GIPR KO mice also showed impaired synaptic plasticity in paired-pulse facilitation and a block of long-term potentiation in area CA1 of the hippocampus. Moreover, a large decrease in the number of neuronal progenitor cells was found in the dentate gyrus of transgenic mice, although the numbers of young neurons was not changed. Together the results suggest that GIP receptors play an important role in cognition, neurotransmission, and cell proliferation.
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The purpose of this study was to analyse pupils’ English grammar acquisition from competitive and cooperative approaches. After searching a wide range of authors’ contribution to English language learning, grammar acquisition, classroom environment and language games. A hundred and twenty pupils from three schools; two from Ripoll and one from Campdevànol were enrolled in a specific grammar games intervention. This was imparted in three different phases: first of all, I interviewed the three teachers from the three schools, then I put into practice my competitive and cooperative games which I designed especially for this study (all the sessions were carried, assessed and registered by myself); finally, all pupils answered a questionnaire related to their experiences in my grammar games intervention. Analysis of teaching interventions showed that, in terms of English language acquisition, pupils used different strategies to show up understanding and achieve the objective of the game such as: recalling their background knowledge, expressing sentences influenced by their internal language and their mother tongue. Data collected revealed that most difficulties were founded in team work, even more in competitive games. The results also showed that team work is something which has to be developed step by step in order to achieve language learning and all pupils’ active participation successfully.
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Aquesta recerca està basada en l’observació de les cançons per aprendre i ensenyar la llengua anglesa en l’etapa d’Educació Primària. S’analitza la cançó com un recurs eficaç per aprendre aquesta llengua, així com també s’observen els avantatges i desavantatges que es poden trobar en l’ús de les cançons a les aules de Primària. A partir d’una aplicació pràctica també s’estudia la validesa d’aquest recurs en el primer i darrer curs de la Primària. A més a més, es mesura la motivació que mostren els alumnes davant d’aquesta eina d’aprenentatge. Finalment, es presenten els resultats obtinguts en l’aplicació pràctica que s’ha portat a terme en una escola i les conclusions que s’extreuen a partir de la justificació teòrica i els resultats obtinguts a partir de les sessions pràctiques.
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Avui en dia les Tecnologies de la Informació i la Comunicació (TIC) s’han convertit en eines d’ús quotidià i alhora invisibles en diversos àmbits de la societat i les escoles no n’estan al marge. No cal ensenyar a fer servir eines tecnològiques, sinó que cal entendre-les com un suport. Recerques recents han demostrat que un bon ús d’aquestes potencien un bon ensenyament i aprenentatge. Al mateix temps, es potencien mètodes globalitzats a les aules que permeten construir coneixements significatius a partir de situacions i problemes. Per això, l’objectiu principal d’aquest estudi consisteix en investigar quins canvis s’observen en la motivació de l’alumnat i quins canvis succeeixen a l’aula en general quan s’usen les TIC com a suport en un mètode globalitzat anomenat la recerca del medi. Per tal de resoldre aquest problema d’investigació es recullen diverses dades d’una intervenció didàctica basada en aquest mètode que es porta a terme en dos cursos de cinquè de Primària. Tal com s’observarà, l’ús de les noves tecnologies en un mètode que permet apropar els infants a la realitat n’augmenta la motivació i promou canvis a l’aula que ajuden i faciliten la tasca del docent i alhora afavoreix un aprenentatge significatiu.
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Hi ha molts tipus d’escoles diferents, i fins i tot, podem constatar que cada escola és diferent de les altres. Per aquesta raó, quan parlem sobre l’aprenentatge de l’anglès, no podem generalitzar una manera de fer-ho, perquè cada una d’elles tracta aquesta llengua de manera diferent. A més, pel que fa a l’aprenentatge d’una llengua, hi ha diferents habilitats involucrades, i entre totes aquestes, he centrat aquest projecte en l’habilitat oral. Aquesta recerca esta basada en l’observació de tres exemples de tipus d’escoles, i per ser més precisos, té l’objectiu d’aprofundir com tracten l’Anglès. D’aquesta manera, el principal objectiu d’aquest projecte és comparar l’habilitat oral dels alumnes d’aquestes escoles, tot considerant les seves diferències. Així doncs, amb el desenvolupament d’aquesta recerca, vaig voler descobrir si hi havien alguns alumnes amb millors habilitats orals que d’altres, i trobar-ne la possible raó.
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This paper presents a customizable system used to develop a collaborative multi-user problem solving game. It addresses the increasing demand for appealing informal learning experiences in museum-like settings. The system facilitates remote collaboration by allowing groups of learners tocommunicate through a videoconferencing system and by allowing them to simultaneously interact through a shared multi-touch interactive surface. A user study with 20 user groups indicates that the game facilitates collaboration between local and remote groups of learners. The videoconference and multitouch surface acted as communication channels, attracted students’ interest, facilitated engagement, and promoted inter- and intra-group collaboration—favoring intra-group collaboration. Our findings suggest that augmentingvideoconferencing systems with a shared multitouch space offers newpossibilities and scenarios for remote collaborative environments and collaborative learning.
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Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process
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Two spatial tasks were designed to test specific properties of spatial representation in rats. In the first task, rats were trained to locate an escape hole at a fixed position in a visually homogeneous arena. This arena was connected with a periphery where a full view of the room environment existed. Therefore, rats were dependent on their memory trace of the previous position in the periphery to discriminate a position within the central region. Under these experimental conditions, the test animals showed a significant discrimination of the training position without a specific local view. In the second task, rats were trained in a radial maze consisting of tunnels that were transparent at their distal ends only. Because the central part of the maze was non-transparent, rats had to plan and execute appropriate trajectories without specific visual feedback from the environment. This situation was intended to encourage the reliance on prospective memory of the non-visited arms in selecting the following move. Our results show that acquisition performance was only slightly decreased compared to that shown in a completely transparent maze and considerably higher than in a translucent maze or in darkness. These two series of experiments indicate (1) that rats can learn about the relative position of different places with no common visual panorama, and (2) that they are able to plan and execute a sequence of visits to several places without direct visual feed-back about their relative position.
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This research project focuses on the role of English and Spanish as linguae francae. More specifically, the research attempts to answer the following questions: (i) What is the place of English and Spanish as linguae francae in the world, in general, and in China, in particular? (ii) What kinds of foreign language teaching/learning attitudes and practices are characteristic of the Chinese educational system? (iii) What are the motivations, expectations and experience of Chinese students in study abroad programmes, in general, and in the programme of the University of Lleida, in particular? The study constitutes an attempt to answer each of these questions in two ways: a review of the literature and a pilot study with 26 Chinese students at UdL. The research reveals that even though English is a very dominant foreign language in China, Spanish is a language on the rise and mainly for economic reasons. The results of the study also point at the impact of the dominance of the grammar-translation method in the perspective of Chinese students about language learning. Finally, the study shows the relevance of taking part in a SA programme for Chinese students as well as their experience of them.
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L'objecte d'estudi d'aquest article és la relació entre l'educació física i l'aprenentatge de la llengua anglesa, per mitjà de l'enfocament educatiu AICLE (CLIL, en anglès), concretat en el programa Mou-te i aprèn. Pel que fa a l'educació física es fonamenta en la metodologia d'instrucció directa: global pura, anàlisi progressiu i anàlisi seqüencial, complementada amb estratègies d'aprenentatge cooperatiu. L'educació física és una forma diferent i excel-lent d'aprendre la llengua. La combinació de les diferents metodologies i tècniques són molt efectives per millorar alhora el llenguatge, la motricitat i la salut.
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The purpose of this article is to treat a currently much debated issue, the effects of age on second language learning. To do so, we contrast data collected by our research team from over one thousand seven hundred young and adult learners with four popular beliefs or generalizations, which, while deeply rooted in this society, are not always corroborated by our data.Two of these generalizations about Second Language Acquisition (languages spoken in the social context) seem to be widely accepted: a) older children, adolescents and adults are quicker and more efficient at the first stages of learning than are younger learners; b) in a natural context children with an early start are more liable to attain higher levels of proficiency. However, in the context of Foreign Language Acquisition, the context in which we collect the data, this second generalization is difficult to verify due to the low number of instructional hours (a maximum of some 800 hours) and the lower levels of language exposure time provided. The design of our research project has allowed us to study differences observed with respect to the age of onset (ranging from 2 to 18+), but in this article we focus on students who began English instruction at the age of 8 (LOGSE Educational System) and those who began at the age of 11 (EGB). We have collected data from both groups after a period of 200 (Time 1) and 416 instructional hours (Time 2), and we are currently collecting data after a period of 726 instructional hours (Time 3). We have designed and administered a variety of tests: tests on English production and reception, both oral and written, and within both academic and communicative oriented approaches, on the learners' L1 (Spanish and Catalan), as well as a questionnaire eliciting personal and sociolinguistic information. The questions we address and the relevant empirical evidence are as follows: 1. "For young children, learning languages is a game. They enjoy it more than adults."Our data demonstrate that the situation is not quite so. Firstly, both at the levels of Primary and Secondary education (ranging from 70.5% in 11-year-olds to 89% in 14-year-olds) students have a positive attitude towards learning English. Secondly, there is a difference between the two groups with respect to the factors they cite as responsible for their motivation to learn English: the younger students cite intrinsic factors, such as the games they play, the methodology used and the teacher, whereas the older students cite extrinsic factors, such as the role of their knowledge of English in the achievement of their future professional goals. 2 ."Young children have more resources to learn languages." Here our data suggest just the opposite. The ability to employ learning strategies (actions or steps used) increases with age. Older learners' strategies are more varied and cognitively more complex. In contrast, younger learners depend more on their interlocutor and external resources and therefore have a lower level of autonomy in their learning. 3. "Young children don't talk much but understand a lot"This third generalization does seem to be confirmed, at least to a certain extent, by our data in relation to the analysis of differences due to the age factor and productive use of the target language. As seen above, the comparably slower progress of the younger learners is confirmed. Our analysis of interpersonal receptive abilities demonstrates as well the advantage of the older learners. Nevertheless, with respect to passive receptive activities (for example, simple recognition of words or sentences) no great differences are observed. Statistical analyses suggest that in this test, in contrast to the others analyzed, the dominance of the subjects' L1s (reflecting a cognitive capacity that grows with age) has no significant influence on the learning process. 4. "The sooner they begin, the better their results will be in written language"This is not either completely confirmed in our research. First of all, we perceive that certain compensatory strategies disappear only with age, but not with the number of instructional hours. Secondly, given an identical number of instructional hours, the older subjects obtain better results. With respect to our analysis of data from subjects of the same age (12 years old) but with a different number of instructional hours (200 and 416 respectively, as they began at the ages of 11 and 8), we observe that those who began earlier excel only in the area of lexical fluency. In conclusion, the superior rate of older learners appears to be due to their higher level of cognitive development, a factor which allows them to benefit more from formal or explicit instruction in the school context. Younger learners, however, do not benefit from the quantity and quality of linguistic exposure typical of a natural acquisition context in which they would be allowed to make use of implicit learning abilities. It seems clear, then, that the initiative in this country to begin foreign language instruction earlier will have positive effects only if it occurs in combination with either higher levels of exposure time to the foreign language, or, alternatively, with its use as the language of instruction in other areas of the curriculum.
Resumo:
The purpose of this article is to treat a currently much debated issue, the effects of age on second language learning. To do so, we contrast data collected by our research team from over one thousand seven hundred young and adult learners with four popular beliefs or generalizations, which, while deeply rooted in this society, are not always corroborated by our data.Two of these generalizations about Second Language Acquisition (languages spoken in the social context) seem to be widely accepted: a) older children, adolescents and adults are quicker and more efficient at the first stages of learning than are younger learners; b) in a natural context children with an early start are more liable to attain higher levels of proficiency. However, in the context of Foreign Language Acquisition, the context in which we collect the data, this second generalization is difficult to verify due to the low number of instructional hours (a maximum of some 800 hours) and the lower levels of language exposure time provided. The design of our research project has allowed us to study differences observed with respect to the age of onset (ranging from 2 to 18+), but in this article we focus on students who began English instruction at the age of 8 (LOGSE Educational System) and those who began at the age of 11 (EGB). We have collected data from both groups after a period of 200 (Time 1) and 416 instructional hours (Time 2), and we are currently collecting data after a period of 726 instructional hours (Time 3). We have designed and administered a variety of tests: tests on English production and reception, both oral and written, and within both academic and communicative oriented approaches, on the learners' L1 (Spanish and Catalan), as well as a questionnaire eliciting personal and sociolinguistic information. The questions we address and the relevant empirical evidence are as follows: 1. "For young children, learning languages is a game. They enjoy it more than adults."Our data demonstrate that the situation is not quite so. Firstly, both at the levels of Primary and Secondary education (ranging from 70.5% in 11-year-olds to 89% in 14-year-olds) students have a positive attitude towards learning English. Secondly, there is a difference between the two groups with respect to the factors they cite as responsible for their motivation to learn English: the younger students cite intrinsic factors, such as the games they play, the methodology used and the teacher, whereas the older students cite extrinsic factors, such as the role of their knowledge of English in the achievement of their future professional goals. 2 ."Young children have more resources to learn languages." Here our data suggest just the opposite. The ability to employ learning strategies (actions or steps used) increases with age. Older learners' strategies are more varied and cognitively more complex. In contrast, younger learners depend more on their interlocutor and external resources and therefore have a lower level of autonomy in their learning. 3. "Young children don't talk much but understand a lot"This third generalization does seem to be confirmed, at least to a certain extent, by our data in relation to the analysis of differences due to the age factor and productive use of the target language. As seen above, the comparably slower progress of the younger learners is confirmed. Our analysis of interpersonal receptive abilities demonstrates as well the advantage of the older learners. Nevertheless, with respect to passive receptive activities (for example, simple recognition of words or sentences) no great differences are observed. Statistical analyses suggest that in this test, in contrast to the others analyzed, the dominance of the subjects' L1s (reflecting a cognitive capacity that grows with age) has no significant influence on the learning process. 4. "The sooner they begin, the better their results will be in written language"This is not either completely confirmed in our research. First of all, we perceive that certain compensatory strategies disappear only with age, but not with the number of instructional hours. Secondly, given an identical number of instructional hours, the older subjects obtain better results. With respect to our analysis of data from subjects of the same age (12 years old) but with a different number of instructional hours (200 and 416 respectively, as they began at the ages of 11 and 8), we observe that those who began earlier excel only in the area of lexical fluency. In conclusion, the superior rate of older learners appears to be due to their higher level of cognitive development, a factor which allows them to benefit more from formal or explicit instruction in the school context. Younger learners, however, do not benefit from the quantity and quality of linguistic exposure typical of a natural acquisition context in which they would be allowed to make use of implicit learning abilities. It seems clear, then, that the initiative in this country to begin foreign language instruction earlier will have positive effects only if it occurs in combination with either higher levels of exposure time to the foreign language, or, alternatively, with its use as the language of instruction in other areas of the curriculum.
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These guidelines were created by a Task Force appointed by the State Library of Iowa and the Iowa Department of Education to provide assistance to local school districts in developing school library programs. These include a summary of the data collected annually by the State Library of Iowa in its Survey of School Libraries. This data will allow local schools to compare themselves in terms of collections, budgets and staffing to schools of similar size throughout the state.
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Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.