Cette recherche aborde la problématique de la relation à la formation dans un processus d’autoformation en ligne. Elle pose la question du rapport au pouvoir dans ce type de situation d’apprentissage. La médiation pédagogique humaine et la médiatisation technologique y sont au centre des préoccupations. Il s’agit d’aborder, au travers de la conception même des instruments d’investigation, les concepts: de contrôle, d’autodirection, d’autonomie, d’efficacité, de compétence, d’autodétermination en relation avec la notion de motif d’engagement. Les dispositions et les prédispositions liées à l'autoformation sont également observées. On se propose de comprendre les orientations motivationnelles et les motifs qui éclairent l’engagement au regard de la perception de soi dans un contexte d’autoformation. Nos réflexions portent également sur le concept d'alterdidaxie par opposition aux démarches autodidactes dans un contexte d'autoformation./<p><p>This research approaches the problems in relation to training in the process of e-learning. It raises the question of the self-directed learning’s power in this type of training situation. The human teaching mediation and the technological mediatization are both in the center of the concerns. This research is an approach, through the design even of instruments of investigation, to the concepts :control, autodirection, autonomy, effectiveness, competence, self-determination in relation with the engagement. Competences and readiness scales related to the adults’ self-training are also observed. One proposes to observe motivational directions and the engagement’s reasons in relation with the perception of oneself as self-directed learners in a context of self-training. Our reflections also relate to the concept of Alterdidacticism in opposition to the self-educated steps, to the Autodidacticism in a context of adults’ self-training.<p><p> / Doctorat en Sciences Psychologiques et de l'éducation / info:eu-repo/semantics/nonPublished

This thesis describes the approach and results of the research to create a TRIZ based computer aided innovation tools (AEGIS and Design for Wow). This research has mainly been based around two tools created under this research: called AEGIS (Accelerated Evolutionary Graphics Interface System), and Design for Wow. Both of these tools are discussed in this thesis in detail, along with the test data, design methodology, test cases, and research. Design for Wow (http://www.designforwow.com) is an attempt to summarize the successful inventions/ designs from all over the world on a web portal which has multiple capabilities. These designs/innovations are then linked to the TRIZ Principles in order to determine whether innovative aspects of these successful innovations are fully covered by the forty TRIZ principles. In Design for Wow, a framework is created which is implemented through a review tool. The Design for Wow website includes this tool which has been used by researcher and the users of the site and reviewers to analyse the uploaded data in terms of strength of TRIZ Principles linked to them. AEGIS (Accelerated Evolutionary Graphics Interface System) is a software tool developed under this research aimed to help the graphic designers to make innovative graphic designs. Again it uses the forty TRIZ Principles as a set of guiding rules in the software. AEGIS creates graphic design prototypes according to the user input and uses TRIZ Principles framework as a guide to generate innovative graphic design samples. The AEGIS tool created is based on TRIZ Principles discussed in Chapter 3 (a subset of them). In AEGIS, the TRIZ Principles are used to create innovative graphic design effects. The literature review on innovative graphic design (in chapter 3) has been analysed for links with TRIZ Principles and then the DNA of AEGIS has been built on the basis of this study. Results from various surveys/ questionnaires indicated were used to collect the innovative graphic design samples and then TRIZ was mapped to it (see section 3.2). The TRIZ effects were mapped to the basic graphic design elements and the anatomy of the graphic design letters was studied to analyse the TRIZ effects in the collected samples. This study was used to build the TRIZ based AEGIS tool. Hence, AEGIS tool applies the innovative effects using TRIZ to basic graphic design elements (as described in section 3.3). the working of AEGIS is designed based on Genetic Algorithms coded specifically to implement TRIZ Principles specialized for Graphic Design, chapter 4 discusses the process followed to apply TRIZ Principles to graphic design and coding them using Genetic Algorithms, hence resulting in AEGIS tool. Similarly, in Design for Wow, the content uploaded has been analysed for its link with TRIZ Principles (see section 3.1 for TRIZ Principles). The tool created in Design for Wow is based on the framework of analysing the TRIZ links in the uploaded content. The ‘Wow’ concept discussed in the section 5.1 and 5.2 is the basis of the concept of Design for Wow website, whereby the users upload the content they classify as ‘Wow’. This content then is further analysed for the ‘Wow factor’ and then mapped to TRIZ Principles as TRIZ tagging methodology is framed (section 5.5). From the results of the research, it appears that the TRIZ Principles are a comprehensive set of innovation basic building blocks. Some surveys suggest that amongst other tools, TRIZ Principles were the first choice and used most .They have thus the potential of being used in other innovation domains, to help in their analysis, understanding and potential development.

The present study examined the self-learning experiences of 12 university students nearing graduation in order to understand the role of curriculum in the development of identity. This inquiry was conducted as a narrative study within a systems theory framework to examine the factors influencing higher education. The study used two rounds of open-ended interviews, separated by a researcher-created interpretation of participants‘ stories so that students could confirm their experiences and contextual influences. These included familial, cultural, and social factors. Phenomenological analysis revealed a process of repeating cycles of Disorientation and Reorientation in participants‘ self-learning experiences. Sites of learning included predominantly Expectations/Experiences and Learning to Manage Relationships. A directional theme of Seeking/Finding Fit appeared in areas such as Discipline, Program Fit, and Career. This trajectory showed distinct patterns of engagement, both in learning and social and community settings. Findings suggest that experiences outside the classroom contributed most powerfully to self-learning. Results indicate a lack of awareness of personal values or their role in finding disciplinary or career preference, and a lack of understanding of the ways students could apply their academic and self-learning to the world beyond post-secondary education. Opportunities for critical self-reflection appeared to contribute to the development of insight and self-awareness, but few opportunities occurred in classroom learning experiences. While all participants could be described as academically successful, a strong relationship between academic performance and self-knowledge was not apparent. The findings suggest that certain curriculum strategies encourage identity development in undergraduate students. These strategies use integrated, experiential learning with opportunities for self-reflection, and include interdisciplinary approaches to teaching and learning.

This work deals with intercultural management in Europian Union, that brings many pro-blems in company's management. Based on self-learning organization concept, this work aims to explain, that an organization can not even succesfully overcome these problems but can even make a comparative advantage from them. Supporting with results from analysis of middle-europian unit of company KONE.

Esta investigación se enfocará en el aprendizaje de la fotografía que se da en las juntas fotográficas de Lima en base a la procedencia ocupacional de los asistentes. Podemos identificar el aprendizaje informal y el autoaprendizaje como principales procesos. Se analizará también a las cuentas de fotógrafos en redes sociales y el proceso de convocatoria de las juntas fotográficas, así como el proceso de aprendizaje que se da dentro de ella. / This research will focus on the learning of photography that occurs in the photographic meetings of Lima based on the occupational origin of the attendees. We can identify informal learning and self-learning as main processes. It will also analyze the accounts of photographers in social networks and the process of convening the photographic boards, as well as the learning process that takes place within it. / Trabajo de investigación

Technische Entwicklungen sowie Elemente der Automatisierung führen im Maschinen- und Anlagenbau zu einer steigenden Komplexität, welche mit einem gesteigerten Gesamtwirkungsgrad (nach (DIN 8743:2014-01) der Endprodukte einhergeht. In der Bedienung kann jedoch, bspw. in der Lebensmittelverarbeitungs- und -verpackungsindustrie, eine Diskrepanz des technisch möglichen und real erzielten Wirkungsgrades im zweistelligen Prozentbereich festgestellt werden (Schult, Oehm, Klaeger & Carsch 2018). Mit den Ironies of automation wurde bereits in den 1980er Jahren eine Ursache dafür identifiziert. Die fehlende Erfahrung sowie fehlendes Prozessverständnis im Umgang mit komplexen Systemen auf Bedienenden-Seite führen zu Problemen im Umgang mit ebenjenen (Bainbridge 1983). Insbesondere bei biogenen Rohstoffen mit volatilen Eigenschaften können weit verzweigte Ursache-Wirkungs-Kausalitäten im Störungsfall weder verstanden noch nachhaltig behoben werden. Diese theoretische Annahme wird auch durch Analysen am Fraunhofer Institut für Verfahrenstechnik und Verpackung (IVV) in Dresden bestätigt. Seit 1995 konnte in über 6.000 Stunden Maschineneffizienzanalysen in der Lebensmittelverarbeitung und -verpackung festgestellt werden, dass die Prozesse von so genannten Mikrostörungen, also Unterbrechungen kürzer als 2 Minuten, geprägt sind (Schult, Beck & Majschak 2015). Ein für die nachhaltige Problemlösung notwendiger Erfahrungsaustausch und -aufbau unter den Mitarbeitenden wird dabei häufig durch Personalfluktuation, Fachkräftemangel und Kommunikationsbarrieren behindert. [...aus der Einleitung]

L'Internet des objets (IoT) devrait interconnecter plus de 50 milliards d’objet d'ici à 2020. Avec l'IoT, une variété d’objets de différentes industries seront interconnectés à travers Internet. Avec un accent sur la gestion et le stockage des ressources énergétique et l'eau. L'IoT permet d’enrichir les services fournis par les distributeurs d’énergie à travers les smart-grid au-delà de la distribution, de l'automatisation et du contrôle. Les systèmes de gestion pour la domotique et les bâtiments intelligents aideront les consommateurs à surveiller et à ajuster leur consommation. Les compteurs intelligents fournissent ainsi un ensemble d’information permettant aux fournisseurs d’énergie de mettre en place des services plus intelligents pour l'ensemble de la chaîne de production d'énergie. L'objectif principal de ce projet de recherche doctorale est de développer des modules de communication très basse consommation. La consommation énergétique étant la plus grande contrainte pour les applications de compteurs intelligents. Les objets connectés alimentés par batterie tels que les capteurs et compteurs de gaz et d'eau sont concernés directement par la consommation en énergie de leur module de communication. Aujourd'hui, la plupart des solutions sans fil embarquées conçues pour capteurs alimentés ne sont pas compatible avec la pile protocolaire IPv6 afin d’économiser la consommation énergétique. Élaborer des technologies sans fil de l'IoT pour atteindre les objectifs de consommation d'énergie va démocratiser l’utilisation de ces technologies et aider les solutions de l’IoT à trouver leur place sur le marché. Ce doctorat débutera par: 1) Un état de l'art permettant d'examiner les solutions actuelles développées pour les réseaux de capteurs et des protocoles conçus pour les appareils alimentés par batterie. 2) Dans un deuxième temps en examinant les solutions Itron pour IPv6 réseau maillé. 3) La troisième phase sera la proposition et la conception d'une solution à faible consommation pour les modules sans fil et l'internet des objets. 4) Et enfin l’expérimentation et la validation des solutions proposées sur des plateformes d’expérimentations / The Internet of Things (IoT) is expected to grow to 50 billion connected devices by 2020. Within the IoT, devices across a variety of industries will be interconnected through the Internet and peer-to-peer connections as well as closed networks like those used in the smart grid infrastructure. With the global focus on energy and water management and conservation, the IoT will extend the connected benefits of the smart grid beyond the distribution, automation and monitoring being done by utility providers. Management systems for in-home and in-building use will help consumers monitor their own usage and adjust behaviors. These systems will eventually regulate automatically by operating during off-peak energy hours and connect to sensors to monitor occupancy, lighting conditions, and more. But it all starts with a smarter and more connected grid. Smart metering provides a base around which utilities can build up smarter advanced services for the whole chain of energy generation, transmission and distribution. The main objective of this doctoral research project is to come up with the IoT communication modules with very low consumption characteristics. The energy consumption is the most challenging issue for smart home and smart metering applications. The battery powered devices such as sensors and gas and water meters are concerned directly with the consumption of their communication module. Today most of the embedded wireless solutions designed for sensors and battery powered devices do not embed IPv6 stack in the communication module to have a basic hardware with low consumption. Elaborating IoT wireless technologies to achieve the tough energy consumption objectives imposed to them will boost up the spread of these technologies and help IoT to find its place in the market fast. This PhD program will start with: First) a state of the art and reviewing the current solutions developed for sensor networks and protocols designed for battery powered devices. Second) it continues by reviewing Itron solutions for IPv6 meshed network. Third) Design of a low consumption solution for IoT wireless modules and) finally test and experimentation on platform

Machine learning systems have been demonstrated to be highly effective in various fields, such as in vision tasks for autonomous driving. However, the deployment of these systems poses a significant challenge in terms of ensuring their reliability and safety in diverse and dynamic environments. Online Unsupervised Domain Adaptation (UDA) aims to address the issue of continuous domain changes that may occur during deployment, such as sudden weather changes. Although these methods possess a remarkable ability to adapt to unseen domains, they are hindered by the high computational cost associated with constant adaptation, making them unsuitable for real-world applications that demand real-time performance. In this work, we focus on the challenging task of semantic segmentation. We present a framework for real-time domain adaptation that utilizes novel strategies to enable online adaptation at a rate of over 29 FPS on a single GPU. We propose a clever partial backpropagation in conjunction with a lightweight domain-shift detector that identifies the need for adaptation, adapting appropriately domain-specific hyperparameters to enhance performance. To validate our proposed framework, we conduct experiments in various storm scenarios using different rain intensities and evaluate our results in different domain shifts, such as fog visibility, and using the SHIFT dataset. Our results demonstrate that our framework achieves an optimal trade-off between accuracy and speed, surpassing state-of-the-art results, while the introduced strategies enable it to run more than six times faster at a minimal performance loss. / Maskininlärningssystem har visat sig vara mycket effektiva inom olika områden, till exempel i datorseende uppgifter för autonom körning. Spridning av dessa system utgör dock en betydande utmaning när det gäller att säkerställa deras tillförlitlighet och säkerhet i olika och dynamiska miljöer. Online Unsupervised Domain Adaptation (UDA) syftar till att behandla problemet med kontinuerliga domänändringar som kan inträffas under systemets användning, till exempel plötsliga väderförändringar. Även om dessa metoder har en anmärkningsvärd förmåga att anpassa sig till okända domäner, hindras de av den höga beräkningskostnaden som är förknippad med ständig nöndvändighet för anpassning, vilket gör dem olämpliga för verkliga tillämpningar som kräver realtidsprestanda. I detta avhandling fokuserar vi på utmanande uppgiften semantisk segmentering. Vi presenterar ett system för domänanpassning i realtid som använder nya strategier för att möjliggöra onlineanpassning med en hastighet av över 29 FPS på en enda GPU. Vi föreslår en smart partiell backpropagation i kombination med en lätt domänförskjutningsdetektor som identifierar nãr anpassning egentligen behövs, vilket kan konfigureras av domänspecifika hyperparametrar på lämpligt sätt för att förbättra prestandan. För att validera vårt föreslagna system genomför vi experiment i olika stormscenarier med olika regnintensiteter och utvärderar våra resultat i olika domänförskjutningar, såsom dimmasynlighet, och med hjälp av SHIFT-datauppsättningen. Våra resultat visar att vårt system uppnår en optimal avvägning mellan noggrannhet och hastighet, och överträffar toppmoderna resultat, medan de introducerade strategierna gör det möjligt att köra mer än sex gånger snabbare med minimal prestandaförlust.

Automatiskt rättning av korta texter är ett område som spänner allt från naturlig språkbehandling till maskininlärning. Projektet behandlar maskininlärning för att förutsäga korrektheten av svar i fritext. Naturlig språkbehandling används för att analysera text och utvinna viktiga underliggande relationer i texten. Det finns idag flera approximativa lösningar för automatiskt rättning av korta svar i fritext. Två framstående metoder är maskininlärning och regelbaserad metod. Vi kommer att framföra en alternativ metod som kombinerar maskininlärning med en regelbaserad metod för att approximativt lösa förenämnda problemet. Studien handlar om att implementera en regelbaserad metod, maskininlärning metod och en slutgiltig kombination av båda dessa metoder. Utvärderingen av den kombinerade metoden utförs genom att titta på de relativa ändringarna i prestanda då vi jämför med den regelbaserade och maskininlärning metoden. De erhållna resultaten har visat att det inte finns någon ökning av noggrannheten hos den kombinerade metoden jämfört med endast maskininlärning metoden. Den kombinerade metoden använder emellertid en liten mängd märkta data med en noggrannhet som är nästan lika metoden med maskininlärning, vilket är positivt. Ytterligare undersökning inom detta område behövs, denna uppsats är bara ett litet bidrag till nya metoder i automatisk rättning. / Automatic correction of short text answers is an area that involves everything from natural language processing to machine learning. Our project deals with machine learning for predicting the correctness of candidate answers and natural language processing to analyse text and extract important underlying relationships in the text. Given that today there are several approximative solutions for automatically correcting short answers, ranging from rule-based methods to machine learning methods. We intend to look at how automatic answer scoring can be solved through a clever combination of both machine learning methods and rule-based method for a given dataset. The study is about implementing a rule-based method, a machine learning method and a final combination of both these methods. The evaluation of the combined method is done by measuring its relative performance compared to the rule-based method and machine learning method. The results obtained have shown that there is no increase in the accuracy of the combined method compared to the machine learning method alone. However, the combined method uses a small amount of labeled data with an accuracy almost equal to the machine learning, which is positive. Further investigation in this area is needed, this thesis is only a small contribution, with a new approaches and methods in automatic short answer scoring.

L’éducation musicale académique n’est officialisée au Sénégal qu’à partir de 1976, dans l’intention de démocratiser l’accès à la culture à l’école. Le but est de former un citoyen sénégalais enraciné dans sa propre culture et ouvert vers le reste du monde. Mais la concrétisation de cette noble ambition a presque échoué en raison d’une « ouverture » qui a pris le pas sur « l’enracinement ». Car la formation des professeurs d’éducation musicale est calquée sur les contenus de cours légués par les français et basés essentiellement sur la musique classique européenne inconnue des sénégalais. Ce qui crée une tension par rapport à la culture musicale populaire des élèves. Dans les écoles, rien n’est prévu pour l’enseignement de cette discipline, au niveau des moyens et matériels didactiques. Les professeurs d’éducation musicale sont confrontés aussi à un problème de rapport au savoir académique dans une société de tradition orale très islamisée avec un système de castes, d’où des préjugés culturels et religieux à propos de la musique. Dans ce travail, nous étudions l’éducation musicale sénégalaise sous ses aspects socioculturels, politiques, politiques, scolaires et économiques. / Academic music education is formalized in Senegal until 1976, with the intention of democratizing access to culture in the school. The goal is to train a Senegal citizen rooted in their own culture and open to the rest of the world. But the realization of this noble ambition almost failed due to an ‘’openness’’ that has overtaken the ‘’rooting’’. Because the pattern of musical education training for teachers is imitating the courses contents left by the French and based mainly on European classical music unknown by the Senegalese. What creates a voltage compared to the popular musical culture of students. In schools, nothing is provided for teaching this subject as for as the resources and educational tools are concerned. Music education teachers are also facing a problem report to the academic knowledge in a society of highly Islamized oral tradition with a caste system, where cultural and religious prejudices about the music. In this work, we study the Senegalese musical education in its socio-cultural, political, academic and economic aspects.