Dissertations / Theses: 'Activist learnings'

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Makris, Dimitrios. "Learning an activity-based semantic scene model." Thesis, City University London, 2004. http://eprints.kingston.ac.uk/7781/.

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Kim, Juho Ph D. Massachusetts Institute of Technology. "Learnersourcing : improving learning with collective learner activity." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101464.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages [199]-213). Millions of learners today are watching videos on online platforms, such as Khan Academy, YouTube, Coursera, and edX, to take courses and master new skills. But existing video interfaces are not designed to support learning, with limited interactivity and lack of information about learners' engagement and content. Making these improvements requires deep semantic information about video that even state-of-the-art AI techniques cannot fully extract. I take a data-driven approach to address this challenge, using large-scale learning interaction data to dynamically improve video content and interfaces. Specifically, this thesis introduces learnersourcing, a form of crowdsourcing in which learners collectively contribute novel content for future learners while engaging in a meaningful learning experience themselves. I present learnersourcing applications designed for massive open online course videos and how-to tutorial videos, where learners' collective activities 1) highlight points of confusion or importance in a video, 2) extract a solution structure from a tutorial, and 3) improve the navigation experience for future learners. This thesis demonstrates how learnersourcing can enable more interactive, collaborative, and data-driven learning. by Juho Kim. Ph. D.

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Albert, Florea George, and Filip Weilid. "Deep Learning Models for Human Activity Recognition." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20201.

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AMI Meeting Corpus (AMI) -databasen används för att undersöka igenkännande av gruppaktivitet. AMI Meeting Corpus (AMI) -databasen ger forskare fjärrstyrda möten och naturliga möten i en kontorsmiljö; mötescenario i ett fyra personers stort kontorsrum. För attuppnågruppaktivitetsigenkänninganvändesbildsekvenserfrånvideosoch2-dimensionella audiospektrogram från AMI-databasen. Bildsekvenserna är RGB-färgade bilder och ljudspektrogram har en färgkanal. Bildsekvenserna producerades i batcher så att temporala funktioner kunde utvärderas tillsammans med ljudspektrogrammen. Det har visats att inkludering av temporala funktioner både under modellträning och sedan förutsäga beteende hos en aktivitet ökar valideringsnoggrannheten jämfört med modeller som endast använder rumsfunktioner[1]. Deep learning arkitekturer har implementerats för att känna igen olika mänskliga aktiviteter i AMI-kontorsmiljön med hjälp av extraherade data från the AMI-databas.Neurala nätverks modellerna byggdes med hjälp av KerasAPI tillsammans med TensorFlow biblioteket. Det ﬁnns olika typer av neurala nätverksarkitekturer. Arkitekturerna som undersöktes i detta projektet var Residual Neural Network, Visual GeometryGroup 16, Inception V3 och RCNN (LSTM). ImageNet-vikter har använts för att initialisera vikterna för Neurala nätverk basmodeller. ImageNet-vikterna tillhandahålls av Keras API och är optimerade för varje basmodell [2]. Basmodellerna använder ImageNet-vikter när de extraherar funktioner från inmatningsdata. Funktionsextraktionen med hjälp av ImageNet-vikter eller slumpmässiga vikter tillsammans med basmodellerna visade lovande resultat. Både Deep Learning användningen av täta skikt och LSTM spatio-temporala sekvens predikering implementerades framgångsrikt. The Augmented Multi-party Interaction(AMI) Meeting Corpus database is used to investigate group activity recognition in an oﬃce environment. The AMI Meeting Corpus database provides researchers with remote controlled meetings and natural meetings in an oﬃce environment; meeting scenario in a four person sized oﬃce room. To achieve the group activity recognition video frames and 2-dimensional audio spectrograms were extracted from the AMI database. The video frames were RGB colored images and audio spectrograms had one color channel. The video frames were produced in batches so that temporal features could be evaluated together with the audio spectrogrames. It has been shown that including temporal features both during model training and then predicting the behavior of an activity increases the validation accuracy compared to models that only use spatial features [1]. Deep learning architectures have been implemented to recognize diﬀerent human activities in the AMI oﬃce environment using the extracted data from the AMI database.The Neural Network models were built using the Keras API together with TensorFlow library. There are diﬀerent types of Neural Network architectures. The architecture types that were investigated in this project were Residual Neural Network, Visual Geometry Group 16, Inception V3 and RCNN(Recurrent Neural Network). ImageNet weights have been used to initialize the weights for the Neural Network base models. ImageNet weights were provided by Keras API and was optimized for each base model[2]. The base models uses ImageNet weights when extracting features from the input data.The feature extraction using ImageNet weights or random weights together with the base models showed promising results. Both the Deep Learning using dense layers and the LSTM spatio-temporal sequence prediction were implemented successfully.

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Olnén, Johanna, and Julia Sommarlund. "Activity Recognition Using IoT and Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-295603.

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Internet of Things devices, such as smartphonesand smartwatches, are currently becoming widely accessible andprogressively advanced. As the use of these devices steadilyincreases, so does the access to large amounts of sensory data.In this project, we developed a system that recognizes certainactivities by applying a linear classifier machine learning modelto a data set consisting of examples extracted from accelerometersensor data. We obtained the data set by collecting data from amobile device while performing commonplace everyday activities.These activities include walking, standing, driving, and ridingthe subway. The raw accelerometer data was then aggregatedinto data points, consisting of several informative features. Thecomplete data set was subsequently split into 80% training dataand 20% test data. A machine learning algorithm, in this case,a support vector machine, was presented with the training dataset and finally classified all test data with a precision higher than90%. Hence, meeting our set objective to build a service with acorrect classification score of over 90%.Human activity recognition has a large area of application,including improved health-related recommendations and a moreefficiently engineered system for public transportation. Internet of Things-enheter, så som smarta telefoner och klockor, blir numera allt mer tillgängliga och tekniskt avancerade. Eftersom användningen av dessa smarta enheter stadigt ökar, ökar också tillgången till stora mängder data från sensorer i dessa enheter. I detta projekt utvecklade vi ett system som känner igen vissa aktiviteter genom att tillämpa en linjär klassificerande maskininlärningsmodell på en uppsättning data som extraherats från en accelerometer, en sensor i en smart telefon. Datauppsättningen skapades genom att samla in data från en smart telefon medan vi utförde vardagliga aktiviteter, så som promenader, stå stilla, köra bil och åka tunnelbana. Rå accelerometerdata samlades in och gjordes om till datavektorer innehållandes statistiska mått. Den totala datauppsättningen delades sedan upp i 80% träningsdata och 20% testdata. En maskininlärningsalgoritm, i detta fall en supportvektormaskin, introducerades med träningsdatan och klassificerade slutligen testdatan med en precision på över 90%. Därmed uppfylldes vårt uppsatta mål med att bygga en tjänst med en korrekt klassificering på över 90%. Igenkänning av mänsklig aktivitet har ett stort användningsområde, och kan bidra till förbättrade hälsorekommendationer och en mer effektiv kollektivtrafik. Kandidatexjobb i elektroteknik 2020, KTH, Stockholm

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Pang, Jinyong. "Human Activity Recognition Based on Transfer Learning." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7558.

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Human activity recognition (HAR) based on time series data is the problem of classifying various patterns. Its widely applications in health care owns huge commercial benefit. With the increasing spread of smart devices, people have strong desires of customizing services or product adaptive to their features. Deep learning models could handle HAR tasks with a satisfied result. However, training a deep learning model has to consume lots of time and computation resource. Consequently, developing a HAR system effectively becomes a challenging task. In this study, we develop a solid HAR system using Convolutional Neural Network based on transfer learning, which can eliminate those barriers.

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Axelsson, Henrik, and Daniel Wass. "Machine Learning for Activity Recognition of Dumpers." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260256.

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The construction industry has lagged behind other industries in productivity growth rate. Earth-moving sites, and other practices where dumpers are used, are no exceptions. Such projects lack convenient and accurate solutions for utilization mapping and tracking of mass flows, which both currently and mainly rely on manual activity tracking. This study intends to provide insights of how autonomous systems for activity tracking of dumpers can contribute to the productivity at earthmoving sites. Autonomous systems available on the market are not implementable to dumper fleets of various manufacturers and model year, whereas this study examines the possibilities of using activity recognition by machine learning for a system based on smartphones mounted in the driver’s cabin. Three machine learning algorithms (naive Bayes, random forest and feed-forward backpropagation neural network) are trained and tested on data collected by smartphone sensors. Conclusions are that machine learning models, and particularly the neural network and random forest algorithms, trained on data from a standard smartphone, are able to estimate a dumper’s activities at a high degree of certainty. Finally, a market analysis is presented, identifying the innovation opportunity for a potential end-product as high. Byggnadsbranschen har halkat efter andra branscher i produktivitetsökning. Markarbetesprojekt och andra arbeten där dumprar används är inga undantag. Sådana projekt saknar användarvänliga system för att kartlägga maskinutnyttjande och massaflöde. Nuvarande lösningar bygger framförallt på manuellt arbete. Denna studie syftar skapa kännedom kring hur autonoma system för aktivitetsspårning av dumprar kan öka produktiviteten på markarbetesprojekt. Befintliga autonoma lösningar är inte implementerbara på maskinparker med olika fabrikat eller äldre årsmodeller. Denna studie undersöker möjligheten att applicera aktivitetsigenkänning genom maskininlärning baserad på smartphones placerade i förarhytten för en sådan autonom lösning. Tre maskininlärningsalgoritmer (naive Bayes, random forest och backpropagation neuralt nätverk) tränas och testas på data från sensorer tillgängliga i vanliga smartphones. Studiens slutsatser är att maskininlärningsmodeller, i synnerhet neuralt nätverk och random forest-algoritmerna, tränade på data från vanliga smartphones, till hög grad kan känna igen en dumpers aktiviteter. Avslutningsvis presenteras en marknadsanalys som bedömer innovationsmöjligheten för en eventuell slutprodukt som hög.

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Marty, Laurence. "Apprendre et lutter au bord du monde : récits de mouvements pour la justice climatique en France et en Europe (2014-2017)." Electronic Thesis or Diss., Paris, EHESS, 2021. http://www.theses.fr/2021EHES0143.

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Cette thèse porte sur les mouvements français et européens contre le dérèglement climatique et sur les tensions qui les caractérisent : qu’est-ce que lutter quand l’envergure de la catastrophe, l’urgence, et le sentiment d’impuissance prévalent ? Comment continue-t-on à lutter dans un monde en ruines qu’on ne croit plus pouvoir sauver ? Et comment le fait-on lorsqu’on se sait appartenir aux pays responsables (historiquement et encore aujourd’hui) des bouleversements environnementaux sans précédent qui nous arrivent ? L’ethnographie au cœur de cette thèse suit des activistes et collectifs dans la préparation des mobilisations qui ont eu lieu autour de la COP21 (Paris, décembre 2015) ainsi que dans la décomposition-recomposition des luttes climatiques qui l’ont suivie. Ces activistes et collectifs ont pour spécificité d’appartenir à l’espace du mouvement écologiste le moins institutionnalisé : leurs engagements dessinent un continuum d’agirs allant de l’agriculture vivrière à l’action directe. Ils relèvent par ailleurs de la partie du mouvement qui a participé à importer et nourrir un certain cadrage de l’enjeu climatique en France à compter de 2015 : celui de la justice climatique. A partir d’une ethnographie qui s’est aussi vécue comme une expérience à la première personne et un partage de vie aux côtés de ces activistes et collectifs, j’ai cherché à rendre sensibles les cheminements et apprentissages qui se déploient au sein des mouvements climat, comme les essoufflements, les doutes, les joies et les puissances qui s’y éprouvent. Le manuscrit est organisé en deux « volumes » qui correspondent chacun à une grande question adressée aux mouvements contre le dérèglement climatique qui relaie celles que se posent les militant.e.s elleux-mêmes : « quel est le "bon moyen" pour lutter contre le dérèglement du climat ? », et « quel est le "bon sujet politique" du mouvement pour la justice climatique ? ». A rebours de réponses univoques et absolues, je propose de penser ces questions comme des pharmaka au sens d’Isabelle Stengers : en fonction de leur dosage, elles peuvent rendre puissant.e.s comme elles peuvent affaiblir, empoisonner. Chacun des deux volumes est lui-même composé de plusieurs « récits » qui font le travail de décaler ces questions et de montrer leurs effets en situation. Enfin, entre ces « récits » sont intercalés des « ateliers » qui sont la reprise de notes de formations auxquelles j’ai participé dans les mouvements climat depuis 2015 This dissertation focuses on the French and European movements against climate change and on the tensions that characterize them: what does it mean to fight when the scale of the disaster, the sense of urgency and the feeling of powerlessness prevail? How does one keep fighting in a world in rubble, which we do not believe we can save anymore? And how do we do so when we know that we belong to the countries responsible (historically and still today) for the unprecedented environmental disruptions that are happening to us? This ethnography explores the actions of activists and collective groups in the preparation of the mobilizations that took place around the COP21 (Paris, December 2015). It examines the decomposition and re-composition of the struggles against climate change that ensued. The specificity of these activists and collectives is that they belong to the least institutionalized space of the environmental movement: their commitments rested on a continuum of collective actions ranging from food farming to direct action. Moreover, they belong to the part of the movement that has participated in importing and developing the climate justice framing in France since 2015. From this ethnography, which was also lived as a personal experience, whereby I shared moments of life with these activists and collectives, I sought to make tangible the pathways and learnings that unfolded within the climate movements, as well as the breathlessness, doubts, joys and empowerment, which have been experienced in these movements.The manuscript is organized in two "volumes", each of which corresponds to a major question addressed to the movements against climate disruption and which relays those asked by the activists themselves: “What is the ‘right way’ to fight against climate disruption?” and “What is the ‘right political subject’ of the movement for climate justice?” In contrast to univocal and absolute answers, I propose to think about these questions as pharmaka in the sense of Isabelle Stengers: depending on their dosage, they can empower or weaken, poison. Each of the two volumes is itself composed of several “stories”, which are used to shift these questions and showing their effects in situation. Finally, between these stories I have interspersed “workshops”, which are the summary of notes I took during trainings, in which I participated in the climate movements since 2015

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Gouin, Rachel. "Gendering resistance : young women's learning in social action." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102242.

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Learning happens informally and incidentally in social struggle, yet it has not been the focus of many studies. When critical adult education scholars research the role of learning and education in transforming society, their analysis is centred on the role of capitalism, or the role of civil society. Critical adult education theory is caught in a debate between radical pluralist and socialist traditions---traditions that guide the role of education and educators in transforming society. Addressing this polemic, I draw on antiracist feminist scholarship to propose an analytical framework that takes into consideration the interdependence of systems of domination; namely, white supremacy, patriarchy and capitalism. In this study, I focus on young female activists' experiences and learning in social struggle. I rely on interviews and a participatory research project conducted with a group of young facilitators working with girls in an elementary school. The role of oppression and domination in social movements and in emancipatory projects is explored. Learning is found to be situated in particular historical contexts and to be influenced by underlying social dynamics inherent to social struggle. It is also found to be contradictory---it both inhibits and fosters change. This study is my praxis. It is a back and forth between grassroots practice and research. It engages activists in thinking critically about their actions and uses various written texts to reflect their stories back to them, and to broader audiences. In the tradition of feminist and participatory research, I use this study as a catalyst for learning and for transforming practice.

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Coley, David. "Learning for solidarity : transformative journeys into global trade union activism." Thesis, London Metropolitan University, 2014. http://repository.londonmet.ac.uk/897/.

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This thesis explores the intersection at which UK trade union learning meets global worker solidarity, primarily through the use of in-depth interviews with learners and learning providers. It examines the extent to which trade union learning influences and activates members to respond through solidarity to address key challenges posed by neo-liberal globalisation. Mobilisation theory is drawn upon to assist in identifying the foundational elements for global active-solidarity formation whilst transformative learning theory assists in examining any possible complementarity with trade union learning methods and approaches. Research into formal learning through trade union courses and informal learning opportunities, including overseas study visits, indicates that awareness of global labour issues is growing, as is active-solidarity, supported in large part by contemporary trade union learning provision. Nonetheless, dominant global ideologies, limited member mobilisation and continuing trade union political disunities present a challenge for transformative learning and global trade union solidarities.

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Hamid, Muhammad Raffay. "Unsupervised Activity Discovery and Characterization for Sensor-Rich Environments." Thesis, Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/14131.

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This thesis presents an unsupervised method for discovering and analyzing the different kinds of activities in an active environment. Drawing from natural language processing, a novel representation of activities as bags of event n-grams is introduced, where the global structural information of activities using their local event statistics is analyzed. It is demonstrated how maximal cliques in an undirected edge-weighted graph of activities, can be used in an unsupervised manner, to discover the different activity-classes. Taking on some work done in computer networks and bio-informatics, it is shown how to characterize these discovered activity-classes from a wholestic as well as a by-parts view-point. A definition of anomalous activities is formulated along with a way to detect them based on the difference of an activity instance from each of the discovered activity-classes. Finally, an information theoretic method to explain the detected anomalies in a human-interpretable form is presented. Results over extensive data-sets, collected from multiple active environments are presented, to show the competence and generalizability of the proposed framework.

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Linsell, Chris, and n/a. "Learning algebra in an activity-based mathematics programme." University of Otago. Department of Mathematics & Statistics, 2005. http://adt.otago.ac.nz./public/adt-NZDU20061016.161725.

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This thesis presents the findings of a research project which explored students� learning during an activity-based mathematics programme. The research investigated what students learnt about solving linear equations and examined the role of activities in this learning. The investigation of learning in the classroom was guided by the principles of naturalistic enquiry. A longitudinal study was used to investigate students� learning during a unit of work that that made extensive use of activities and contexts. The longitudinal design of the study allowed the development of algebraic thinking to be investigated. The ideas of both Piaget and Vygotsky suggest that it is necessary to study the process of change in order to understand the thinking of students. A group of four students, two girls and two boys, were studied for twenty-seven lessons with each student interviewed individually within six days of each lesson, using the technique of stimulated recall. All lessons and interviews were recorded for subsequent transcription and analysis. Learning to solve equations formally, using inverse operations, proved to be difficult for all the students. For two of them, their poor understandings of arithmetic structure and inverse operations were impediments that prevented them from doing more than attempt to follow procedures. Two of the students did succeed in using inverse operations to solve equations, but were still reasoning arithmetically. There was little evidence in the data that any of the students got to the point of regarding equations as objects to act on. They consistently focussed on the arithmetic procedures required for inverse operations. Even by the end of the topic the most able student, like the others, was still struggling to write algebraic statements. One of the most striking features of the results was the slow progress of the students. For at least two of the students, lack of prerequisite numeracy skills provided a good explanation of why this was so. However for the other two, poor numeracy did not appear to be a reason. The findings are, however, perhaps not too surprising. For children learning about arithmetic, the change from a process to an object view, from counting strategies to part/whole strategies, seems a particularly difficult transition to make. To move from a process to an object view of equations appears to be a similarly difficult transition. The way in which the students made use of the contexts showed that the activities did not directly facilitate the students to develop an understanding of formal solution processes. The students did not usually make use of the contexts when solving equations, working at the abstract symbolic level instead. Although it was hoped that, by engaging students in meaningful activities, the students would construct understandings of formal solution processes, this did not occur. None of the activities used in the study provided a metaphor for the formal method of solving equations. It is suggested that, for a context to be of great value for teaching a mathematical concept, the physical activity should act as a metaphor for the intended mathematical activity.

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Sabzpoushan, Maryam. "Play to learn : children learning and activity space." Thesis, KTH, Arkitektur, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-96485.

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Play To Learn is an architectural project that aims to create an interwoven series of formal and informal, experimental learning and activity spaces for children between the ages of 3-12 years. Play To Learn creates a new place in an inner city and seaside location where children can come to play, experience, experiment and learn.

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Pijeira, Díaz H. J. (Héctor Javier). "Electrodermal activity and sympathetic arousal during collaborative learning." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526222196.

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Abstract This dissertation investigates high school students’ individual and interpersonal physiology of electrodermal activity (EDA) during collaborative learning in naturalistic settings. EDA is an index of sympathetic arousal, which is concomitant with cognitive and affective processes. Two data collections were organized with students working collaboratively in triads. The first one took place during the performance of a science task, and the second during two runs of a six-week advanced physics course. The data collected included EDA (measured unobtrusively using Empatica® E3 and E4 wristbands), performance measures (pre- and post-tests, task solutions, and course exam), and questionnaires on cognitive, affective, and collaborative aspects of learning. The work was reported in three articles. The results indicate that, on average, students spent more than half (60%) of the class at a low arousal level, possibly signaling relaxation, disengagement, or boredom. Most of the time (≈60–95% of the lesson), triad members were at a different arousal level, which might indicate that students took turns (alternating task-doers) in executing the task or applied some division of labor rather than truly collaborating. In terms of achievement, sympathetic arousal during the exam was a predictor of the exam grades, and pairwise directional agreement of EDA was positively and highly correlated to the dual learning gain. Arousal contagion could have occurred in up to 41% of the high arousal intervals found. The possible arousal contagion cases took place mostly on a 1:1 basis (71.3%), indicating that interactions in a collaborative learning triad seem to occur mainly between two members rather than among the three. The findings provide an ecologically-valid picture of the students’ EDA responses in the classroom, both individually and collaboratively, benefiting from the connection of arousal to cognitive and affective processes to increase the saliency of otherwise elusive phenomena. Methodologically, the study contributes to the exploration and exploitation of psychophysiological approaches for collaborative learning research. On a practical level, it provides physiological indices that could be incorporated into learning analytics dashboards to support students’ awareness and reflection, and teachers’ pedagogical practices Tiivistelmä Tässä väitöstutkimuksessa tarkastellaan elektrodermaalista aktiivisuutta (EDA) ja tästä johdettua sympaattista vireystilaa ja fysiologisia indeksejä, samanaikaisesti yksilöiden ja yksilöiden välisten kognitiivisten ja affektiivisten prosessien kanssa. Tutkimusaineisto kerättiin yhteisöllisen oppimisen tilanteista, joissa oppilaat työskentelivät kolmen hengen ryhmissä. Ensimmäinen osa aineistosta kerättiin oppilaiden suorittaessa luonnontieteiden alan tehtävää ja toinen kahden fysiikan syventävän kurssin aikana. Aineistoon sisältyi EDA (Empatica® E3- ja E4-rannekkeista), oppimisen mittaukset (alku- ja lopputestit, tehtävien ratkaisut ja kurssikokeet) sekä kyselylomakkeet oppimisen kognitiivisista, affektiivisista ja yhteisöllisen työskentelyn näkökulmista. Tutkimus on raportoitu kolmessa artikkelissa. Tulokset osoittavat, että opiskelijoiden sympaattisen hermoston vireystila oli keskimäärin yli puolet (60 %) luokkatyöskentelystä alhainen, mikä viittaa mahdolliseen rentoutumiseen, osallistumisen puutteeseen tai tylsistymiseen. Ryhmänjäsenet olivat suurimman osan ajasta (≈60-95 %) eri vireystilan tasoilla, mikä voi tarkoittaa, että he suorittivat tehtävää vuorotellen (tehtävän suorittajaa vaihdellen) tai jonkinlaista työnjakoa käyttäen, yhteisöllisen työskentelyn sijaan. Sympaattinen vireystila kurssikokeessa ennusti kokeen arvosanoja. Lisäksi oppilasparien EDA:n samansuuntaisuus korreloi vahvasti oppimistulosten kanssa. Yksilöiden välillä tapahtuvaa sympaattisen vireystilan ”tarttumista” on voinut esiintyä jopa 41 prosentissa todetuista korkean vireystilan intervalleista. Mahdolliset ”tarttumiset” ilmenivät enimmäkseen (71,3%) 1:1 suhteessa, mikä viittaa siihen, että vuorovaikutus yhteisöllisessä oppimisessa näyttäisi tapahtuvan pääasiassa kahden yksilön välillä kaikkien kolmen sijaan. Tulokset tarjoavat ekologisesti validin kuvan opiskelijoiden EDA-reaktioista luokkahuoneessa sekä yksilöllisesti että yhteisöllisesti tarkasteltuna, selventäen samalla kuvaa sympaattisen vireystilan yhteydestä kognitiivisiin ja affektiivisiin prosesseihin. Menetelmällisesti tutkimus kartoittaa psykofysiologisen lähestymistavan mahdollisuuksia yhteisöllisen oppimisen tutkimuksessa. Se esittelee fysiologisia indeksejä, jotka voitaisiin visualisoida oppimisen analytiikan sovelluksissa opiskelijoiden tietoisuuden ja reflektion sekä opettajien pedagogisten käytäntöjen tukemiseksi

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Dong, Shuonan. "Unsupervised learning and recognition of physical activity plans." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42195.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007. Includes bibliographical references (p. 125-129). This thesis desires to enable a new kind of interaction between humans and computational agents, such as robots or computers, by allowing the agent to anticipate and adapt to human intent. In the future, more robots may be deployed in situations that require collaboration with humans, such as scientific exploration, search and rescue, hospital assistance, and even domestic care. These situations require robots to work together with humans, as part of a team, rather than as a stand-alone tool. The intent recognition capability is necessary for computational agents to play a more collaborative role in human-robot interactions, moving beyond the standard master-slave relationship of humans and computers today. We provide an innovative capability for recognizing human intent, through statistical plan learning and online recognition. We approach the plan learning problem by employing unsupervised learning to automatically determine the activities in a plan based on training data. The plan activities are described by a mixture of multivariate probability densities. The number of distributions in the mixture used to describe the data is assumed to be given. The training data trajectories are fed again through the activities' density distributions to determine each possible sequence of activities that make up a plan. These activity sequences are then summarized with temporal information in a temporal plan network, which consists of a network of all possible plans. Our approach to plan recognition begins with formulating the temporal plan network as a hidden Markov model. Next, we determine the most likely path using the Viterbi algorithm. Finally, we refer back to the temporal plan network to obtain predicted future activities. Our research presents several innovations: (cont.) First, we introduce a modified representation of temporal plan networks that incorporates probabilistic information into the state space and temporal representations. Second, we learn plans from actual data, such that the notion of an activity is not arbitrarily or manually defined, but is determined by the characteristics of the data. Third, we develop a recognition algorithm that can perform recognition continuously by making probabilistic updates. Finally, our recognizer not only identifies previously executed activities, but also pre-dicts future activities based on the plan network. We demonstrate the capabilities of our algorithms on motion capture data. Our results show that the plan learning algorithm is able to generate reasonable temporal plan networks, depending on the dimensions of the training data and the recognition resolution used. The plan recognition algorithm is also successful in recognizing the correct activity sequences in the temporal plan network corresponding to the observed test data. by Shuonan Dong. S.M.

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Gordon, Susan Eve. "Understanding Students Learning Statistics: An Activity Theory Approach." Thesis, The University of Sydney, 1998. http://hdl.handle.net/2123/353.

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In this project I investigate university students orientations to learning statistics. The students who participated in my research were studying statistics as a compulsory component of their psychology course. My central thesis is that learning develops in the relationship between the thinking, feeling and acting person and the social, institutional and cultural contexts surrounding him or her. How students orient themselves or position themselves to learn statistics is reflected in their engagement with the learning task and their activities. These activities determine the quality of their learning and emerging knowledge. To understand student learning I draw on the powerful theories of Vygotsky (1962, 1978) and Leontev (1978, 1981). In particular, I extend and apply Leontev's construct of activity (Leontev, 1981). This suggests that individuals act in accordance with their purposes and needs which are shaped by and reflect histories and resources, both personal and cultural. My investigation consists of two studies. Study One is a qualitative exploration of the orientations to learning statistics of five older students. These students sought help with statistics at the Mathematics Learning Centre where I work. My case studies of these students are inseparable from my efforts to help them learn statistics. Study Two is grounded in Study One. The main source of data for this broader study is a survey which was completed by 279 psychology students studying statistics. In keeping with the theoretical framework, my methodology involves a holistic analysis of students and the milieu in which they act. My findings suggest relationships among students affective appraisals; their conceptions of statistics; their approaches to learning it; their evaluations and the outcomes of their actions. In Study One the relationships emerged from the students' descriptions. In Study Two I quantified the ways in which variables related to each other. Structure for the data was provided by means of correlations, factor analysis and cluster analysis. For this study I also interviewed students and teachers of statistics. My data support the systemic view of teaching and learning in context afforded by my theoretical perspective. Learning statistics involves the whole person (Semenov, 1978) and is inseparable from the arena of his or her actions. The goal of statistics education is surely to enable students to develop useful, meaningful knowledge. My findings suggest that for many of the participants in my project this goal was not being met. Most of these students reported their reluctance to learn statistics and described adopting primarily surface approaches to learning it. A range of conceptions of the subject was expressed, but for many of the students statistical meaning was evidently reduced to performance on assessment tasks. Such orientations to learning statistics may lead to it becoming irrelevant and inert information. For a few students, however, the experience of learning statistics led to self development and enhanced perspectives on the world in which we live. My project indicates the diversity of students' experiences. It raises issues as to why we teach statistics today and how the teaching and learning of statistics is being supported at university. //REFERENCES Leontev, A. N. (1978). Activity, Consciousness, and Personality. (M. J. Hall, Trans.). Englewood Cliffs, New Jersey: Prentice-Hall. Leontev, A. N. (1981). The problem of activity in psychology. In J. V. Wertsch (Ed.), The Concept of Activity in Soviet Psychology, (pp. 37-71). New York: M. E. Sharpe. Semenov, N. (1978). An empirical psychological study of thought processes in creative problem-solving from the perspective of the theory of activity. Soviet Psychology, 16(1), 3-46. Vygotsky, L. S. (1962). Thought and Language. Cambridge, Massachusetts: The M.I.T. Press. Vygotsky, L. S. (1978). Mind in Society. Cambridge, MA: Harvard University Press.

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Gordon, Susan Eve. "Understanding Students Learning Statistics: An Activity Theory Approach." University of Sydney. School of Development and Learning, 1998. http://hdl.handle.net/2123/353.

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In this project I investigate university students orientations to learning statistics. The students who participated in my research were studying statistics as a compulsory component of their psychology course. My central thesis is that learning develops in the relationship between the thinking, feeling and acting person and the social, institutional and cultural contexts surrounding him or her. How students orient themselves or position themselves to learn statistics is reflected in their engagement with the learning task and their activities. These activities determine the quality of their learning and emerging knowledge. To understand student learning I draw on the powerful theories of Vygotsky (1962, 1978) and Leontev (1978, 1981). In particular, I extend and apply Leontev's construct of activity (Leontev, 1981). This suggests that individuals act in accordance with their purposes and needs which are shaped by and reflect histories and resources, both personal and cultural. My investigation consists of two studies. Study One is a qualitative exploration of the orientations to learning statistics of five older students. These students sought help with statistics at the Mathematics Learning Centre where I work. My case studies of these students are inseparable from my efforts to help them learn statistics. Study Two is grounded in Study One. The main source of data for this broader study is a survey which was completed by 279 psychology students studying statistics. In keeping with the theoretical framework, my methodology involves a holistic analysis of students and the milieu in which they act. My findings suggest relationships among students affective appraisals; their conceptions of statistics; their approaches to learning it; their evaluations and the outcomes of their actions. In Study One the relationships emerged from the students' descriptions. In Study Two I quantified the ways in which variables related to each other. Structure for the data was provided by means of correlations, factor analysis and cluster analysis. For this study I also interviewed students and teachers of statistics. My data support the systemic view of teaching and learning in context afforded by my theoretical perspective. Learning statistics involves the whole person (Semenov, 1978) and is inseparable from the arena of his or her actions. The goal of statistics education is surely to enable students to develop useful, meaningful knowledge. My findings suggest that for many of the participants in my project this goal was not being met. Most of these students reported their reluctance to learn statistics and described adopting primarily surface approaches to learning it. A range of conceptions of the subject was expressed, but for many of the students statistical meaning was evidently reduced to performance on assessment tasks. Such orientations to learning statistics may lead to it becoming irrelevant and inert information. For a few students, however, the experience of learning statistics led to self development and enhanced perspectives on the world in which we live. My project indicates the diversity of students' experiences. It raises issues as to why we teach statistics today and how the teaching and learning of statistics is being supported at university. //REFERENCES Leontev, A. N. (1978). Activity, Consciousness, and Personality. (M. J. Hall, Trans.). Englewood Cliffs, New Jersey: Prentice-Hall. Leontev, A. N. (1981). The problem of activity in psychology. In J. V. Wertsch (Ed.), The Concept of Activity in Soviet Psychology, (pp. 37-71). New York: M. E. Sharpe. Semenov, N. (1978). An empirical psychological study of thought processes in creative problem-solving from the perspective of the theory of activity. Soviet Psychology, 16(1), 3-46. Vygotsky, L. S. (1962). Thought and Language. Cambridge, Massachusetts: The M.I.T. Press. Vygotsky, L. S. (1978). Mind in Society. Cambridge, MA: Harvard University Press.

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Kling, Mattias. "Developing a Source Criticism Learning Activity for a Digital Learning Environment in History." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-118311.

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Source criticism is an important part of the national curriculum in the history subject in middle grade schools. This master thesis presents the development of a digital learning activity for teaching students about source criticism concepts. The learning activity was developed by first researching the history curriculum and how source criticism is taught within the subject. A conceptual design was drafted based on these findings and the design of an existing framework for teaching students within the history subject. The existing framework, and the developed learning activity, is based on learning-by-teaching implemented in the form of a teachable agent. The teachable agent act as a tutee that students have to teach themselves, increasing students' motivation and learning. By teaching the agent, students improve their own learning. The final implementation of the activity is integrated into both the technical framework and the narrative of the existing environment.

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Coupland, Mary. "Learning with new tools." Access electronically, 2004. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20041221.111821/index.html.

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Rambusch, Jana. "Embodiment and situated learning." Thesis, University of Skövde, School of Humanities and Informatics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-904.

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Cognition has for a long time been viewed as a process that can be described in terms of computational symbol manipulation, i.e. a process that takes place inside people’s heads and is largely unaffected by contextual aspects. In recent years, however, there has been a considerable change in the way researchers look at and study human cognition. These changes also have far-reaching implications for education and educational research. Situated learning is a theoretical framework in which sociocultural aspects of cognition and learning are strongly emphasised, that is, the context in which learning takes place is an important part of learning activity. The concept of activity is central to situated learning theories, but activity has been considered an exclusively sociocultural process in which the body only plays a minor role. In embodied cognition research, on the other hand, there is an increasing awareness that mind and body are inextricably intertwined and cannot be viewed in isolation. Findings in cognitive neuroscience provide additional evidence that cognition is tightly linked to perception and action. The aim of this thesis has been to investigate the role of the body in situated learning activity by integrating these different perspectives on cognition and learning. The analysis suggests that, like individual human conceptualization and thought, situated learning is in fact deeply rooted in bodily activity. In social interactions the body provides individuals with a similar perspective on the world, it functions as a means of signalling to others what cannot (yet) be expressed verbally, and it serves as a resonance mechanism in the understanding of others.

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Goessling, Kristen Parker. "Re/narrating youth : a critical qualitative study of learning in an activist organization." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/53974.

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This critical qualitative research investigated the meaning making practices of a group of 10 youth activists in a youth-driven social justice organization, called Think Again, located in Vancouver, BC. An overarching goal of this study was to contribute to scholarship concerned with how young people, as cultural producers, re/narrate what it means to be a young person in a neoliberal society. To this end, I explored the ways in which contemporary youth narratives, such as the “millennial youth” narrative, afford and constrain learning opportunities for specific groups of young people. My research questions were as follows: (1) In what ways can Think Again be described as a community of practice?; (2) What forms of participation are encouraged at Think Again?; (3) How does youths’ participation at Think Again support and/or challenge the broader social narratives of youth? and; (4) How do participants narrate their lived experiences and participation at Think Again? These questions allowed me to explore the potential disconnect between contemporary youth narratives and youths’ activist narratives to better understand how youths perceive of themselves and their lives within an evolving community of practice (Lave & Wenger, 1991). Analysis of the qualitative data was conducted at three levels in order to identify and examine: (1) narratives across the data, (2) traces of participation across youths’ constructions of knowing, being, and valuing, and (3) participation as future-making. This study resulted in four key findings. The first is a set of more nuanced counternarratives of what it means to be a “youth” today. The second attends to how thinking about learning as participation, a holistic endeavor, also entails changes in knowing, being, and valuing. The third outlines local opportunities for youth participation that generate the conditions for a “politics of possibility” (Holland & Gómez, 2013) as essential to personal and social transformation. The fourth addresses the changing face of youth activism in the contemporary neoliberal context. This study advances the fields of youth engagement, learning as participation, and qualitative methodologies by deploying narrative accounts of young people’s lived experiences. Education, Faculty of Educational and Counselling Psychology, and Special Education (ECPS), Department of Graduate

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Pietsch, James Roderick. "Collaborative learning in mathematics." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/1088.

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This study looked at the implementation of a collaborative learning model at two schools in Sydney designed to realise the principles recommended by reform documents such as the Principles and Standards for School Mathematics (NCTM, 2000) and policy documents including Numeracy, A Priority for All (DETYA, 2000). A total of 158 year seven and year eight students ranging in age from 12 to 15 years old from two schools participated in the study. In all, seven classroom teachers participated in the study each completing two topics using the collaborative learning model. Four research questions were the focus of the current study. Three research questions were drawn from eight principles identified in the literature regarding what constitutes effective mathematics learning. These questions related to the nature of collaboration evident in each classroom, the level of motivation and self-regulation displayed by students in the different types of classrooms and the relationship between learning mathematics within the collaborative learning model and real-world mathematics. A final research question examined the degree to which the concerns of teachers relating to preparing students for examinations are met within the collaborative learning model. Several different data collection strategies were adopted to develop a picture of the different forms of activity evident in each classroom and the changes that took place in each classroom during and after the implementation of the collaborative learning model. These included classroom observations, interviews with student and teacher participants, questionnaires and obtaining test results. Both exploratory and confirmatory factor analysis were used to reduce the data collected. Factor scores and test results were compared using t-tests, ANOVAs and Mann Whitney nonparametric tests. Data collected from interviews and classroom observations were analysed using a grounded approach beginning with the open coding of phenomena. Leont’ev’s theoretical approach to activity systems (1972; 1978) was then used to describe the changing nature of classroom activity with the introduction of the collaborative learning model. Within the collaborative classrooms there were a greater number of mathematical voices participating in classroom discussions, a breaking down of traditional roles held by teachers and students, and dominant patterns of collaboration evident in each classroom reflecting pre-existing cultural ways of doing. Furthermore, there was some quantitative evidence suggesting that student levels of critical thinking, self-regulation and help seeking increased and students were also observed regulating their own learning as well as the learning of others. Classroom practice was also embedded in the cultural practice of preparing topic tests, enabling students to use mathematics within the context of a work group producing a shared outcome. Finally, there was quantitative evidence that students in some of the collaborative classes did not perform as well as students in traditional classrooms on topic tests. Comments from students and teachers, however, suggested that for some students the collaborative learning model enabled them to learn more effectively, although other students were frustrated by the greater freedom and lack of direction. Future research could investigate the effectiveness of strategies to overcome this frustration and the relationship between different types of collaboration and developing mathematical understanding.

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Pietsch, James Roderick. "Collaborative learning in mathematics." University of Sydney, 2005. http://hdl.handle.net/2123/1088.

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Doctor of Philosophy (PhD) This study looked at the implementation of a collaborative learning model at two schools in Sydney designed to realise the principles recommended by reform documents such as the Principles and Standards for School Mathematics (NCTM, 2000) and policy documents including Numeracy, A Priority for All (DETYA, 2000). A total of 158 year seven and year eight students ranging in age from 12 to 15 years old from two schools participated in the study. In all, seven classroom teachers participated in the study each completing two topics using the collaborative learning model. Four research questions were the focus of the current study. Three research questions were drawn from eight principles identified in the literature regarding what constitutes effective mathematics learning. These questions related to the nature of collaboration evident in each classroom, the level of motivation and self-regulation displayed by students in the different types of classrooms and the relationship between learning mathematics within the collaborative learning model and real-world mathematics. A final research question examined the degree to which the concerns of teachers relating to preparing students for examinations are met within the collaborative learning model. Several different data collection strategies were adopted to develop a picture of the different forms of activity evident in each classroom and the changes that took place in each classroom during and after the implementation of the collaborative learning model. These included classroom observations, interviews with student and teacher participants, questionnaires and obtaining test results. Both exploratory and confirmatory factor analysis were used to reduce the data collected. Factor scores and test results were compared using t-tests, ANOVAs and Mann Whitney nonparametric tests. Data collected from interviews and classroom observations were analysed using a grounded approach beginning with the open coding of phenomena. Leont’ev’s theoretical approach to activity systems (1972; 1978) was then used to describe the changing nature of classroom activity with the introduction of the collaborative learning model. Within the collaborative classrooms there were a greater number of mathematical voices participating in classroom discussions, a breaking down of traditional roles held by teachers and students, and dominant patterns of collaboration evident in each classroom reflecting pre-existing cultural ways of doing. Furthermore, there was some quantitative evidence suggesting that student levels of critical thinking, self-regulation and help seeking increased and students were also observed regulating their own learning as well as the learning of others. Classroom practice was also embedded in the cultural practice of preparing topic tests, enabling students to use mathematics within the context of a work group producing a shared outcome. Finally, there was quantitative evidence that students in some of the collaborative classes did not perform as well as students in traditional classrooms on topic tests. Comments from students and teachers, however, suggested that for some students the collaborative learning model enabled them to learn more effectively, although other students were frustrated by the greater freedom and lack of direction. Future research could investigate the effectiveness of strategies to overcome this frustration and the relationship between different types of collaboration and developing mathematical understanding.

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Okaty, Jessica. "The Effectiveness of Outdoor Education on Environmental Learning, Appreciation, and Activism." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/791.

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The main objective of this research was to determine the effectiveness of outdoor education on student knowledge retention, appreciation for nature, and environmental activism in a college level course on south Florida ecology. Six class sections were given quizzes on four course topics either post-lecture or post-field trip. Students were also given pre-course and post-course opinion surveys. Although mean quiz scores for the post-field trip were higher than for the post-lecture, statistical analysis determined that there was no significant difference in quiz scores for location taken (post-lecture or post-field trip). Survey results show a correlation between knowledge of environmental issues and environmental activism. Even though student survey responses point to outdoor education and field trips being the most effective method of learning and influential on appreciation for nature, the quiz scores do not reflect such.

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Solis, John D. "The relationship between preservice teachers' social learning style preferences and learning activity role choices." Laramie, Wyo. : University of Wyoming, 2006. http://proquest.umi.com/pqdweb?did=1225152311&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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Khasanzyanova, Albina. "Les apprentissages des bénévoles dans l’activité associative. Quelles compétences acquièrent-ils, pour quels usages ?" Thesis, Reims, 2015. http://www.theses.fr/2015REIML010.

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Cette recherche doctorale a pour objectif d'étudier les types d'apprentissages que les bénévoles développent durant leur activité au sein d'associations et concerne essentiellement les apprentissages informels, c'est-à-dire dans l'action et par la pratique. Elle s'appuie sur deux enquêtes (par questionnaires et par entretiens semi-directifs) et mobilise un cadre de références composite qui intègre les concepts d'expérience, d'apprentissage par l'expérience, d'activité, de compétences et de développement. Les résultats de ce travail montrent que les bénévoles acquièrent ou renforcent des compétences « professionnelles », mais aussi des soft skills (compétences douces) de nature relationnelle, sociale et humaine. Parmi les processus qui concourent au développement des apprentissages, la reconfiguration dans l'activité des ressources cognitives à partir des expériences ou des acquis antérieurs (professionnels, académiques ou familiaux) semble essentielle.Les résultats mettent également en évidence que les bénévoles transfèrent couramment leurs acquis hors du milieu associatif et que les compétences acquises sont différentes selon les milieux socio professionnels d'appartenance (étudiants, salariés, personnes à la recherche d'un emploi). Enfin il apparait que les usages sociaux des apprentissages réalisés dans le milieu associatif sont diversifiés This research aims to study the types of learning that volunteers develop during their activities in associations and it mainly concerns informal learning, that is to say, in action and in practice. It is based on two surveys (questionnaires and semi-structured interviews) and mobilizes a composite frame of reference which incorporates the concepts of experience, experiential learning, activity, competencies and development.The results of this study show that volunteers acquire or strengthen « professional » competencies but also soft skills; relational, social and human skills. Among the processes that contribute to the development of learning, reconfiguration of cognitive resources from prior experiences or learning (professional, academic or family) seems essential.The results also show that volunteers usually transfer their knowledge outside associations and the competencies acquired are different depending on socio professional backgrounds (students, employees, persons looking for work). Finally it appears that the social uses of the learning developed in associations are diverse

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Parker, Abigail B. "Teaching Envisionment: Activity Settings for Learning to Teach Literature." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1218493014.

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Nguyen, Dieu My Thanh. "OLFACTORY LEARNING AND BRAIN ACTIVITY IN NOVOMESSOR COCKERELLI ANTS." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613353.

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In this study, an olfactory associative conditioning paradigm was developed to study the learning and memory capabilities of Novomessor cockerelli ants. When the antennae of the ant come into contact with sucrose solution, the ant extends its tongue to consume the sucrose. The tongue reflex was conditioned by pairing an odor (conditioned stimulus) with sucrose (unconditioned stimulus) over ten trials. The ant’s tongue reflex in response to odor indicates that an association between the odor and the sucrose has been made in the ant’s brain. The second part of the study includes analyzing the regional brain variations of cytochrome oxidase (COX) staining after olfactory conditioning. The antennal lobe and mushroom body are major brain regions in the insect olfactory pathway, and are regions of interest in this analysis. Results show that there are significant differences in metabolic activity across brain regions (antennal lobe, glomeruli, central boxy complex, mushroom body, and lateral protocerebrum), but the differences do not correlate with the learning status of the ants (learned vs non-learned).

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Zhang, Chenyang. "Human Activity Analysis using Multi-modalities and Deep Learning." Thesis, The City College of New York, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10159927.

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With the successful development of video recording devices and sharing platforms, visual media has become a significant component of everyone's life in the world. To better organize and understand the tremendous amount of visual data, computer vision and machine learning have become the key technologies to resolve such a huge problem. Among the topics in computer vision research, human activity analysis is one of the most challenging and promising areas. Human activity analysis is dedicated to detecting, recognizing, and understanding the context and meaning of human activities in visual media. This dissertation focuses on two aspects in human activity analysis: 1) how to utilize multi-modality approach, including depth sensors and traditional RGB cameras, for human action modeling. 2) How to utilize more advanced machine learning technologies, such as deep learning and sparse coding, to address more sophisticated problems such as attribute learning and automatic video captioning. To explore the utilization of the depth cameras, we first present a depth camera-based image descriptor called histogram of 3D facets (H3DF) and its utilization in human action and hand gesture recognition and a holistic depth video representation for human actions. To unify both the inputs from depth cameras and RGB cameras, this dissertation first discusses a joint framework to model human affections from both facial expressions and body gestures with a multi-modality fusion framework. Then we present deep learning-based frameworks for human attribute learning and automatic video captioning tasks. Compared to human action detection recognition, automatic video captioning is more challenging because it includes complex language models and visual context. Extensive experiments have also been conducted on several public datasets to demonstrate that our proposed frameworks in this dissertation outperform the state-of-the-art approaches in this research area.

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Goutham, Mithun. "Machine learning based user activity prediction for smart homes." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595493258565743.

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Bhavaraju, Srilaya. "Using machine learning for analysis of neuronal network activity." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129131.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020 Cataloged from student-submitted PDF of thesis. Includes bibliographical references (pages 75-77). Analyzing neuronal activity in developing neuronal networks can improve our understanding of neuronal dysfunctions underlying conditions such as Rett syndrome. Two-photon calcium imaging is used to capture neuronal network activity over time. This method produces large sets of images that are typically manually analyzed by skilled neuroscientists. Because this process is both time-consuming and subject to error, discovery of therapies that ameliorate network dysfunction may be slowed. We improve an existing, semi-autonomous machine learning pipeline for two-photon calcium imaging sequence analysis. We introduce to the pipeline neuron detection methods using supervised learning models, heuristic filtering of pixels for signal extraction, and event detection using deconvolution. With these methods, we improve neuron detection performance, alter signal-to-noise ratio of extracted calcium signals, and allow for integration of methods that infer action potential firing underlying these signals. by Srilaya Bhavaraju. M. Eng. M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

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Gentek, Anna. "Activity Recognition Using Supervised Machine Learning and GPS Sensors." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-295600.

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Human Activity Recognition has become a popular research topic among data scientists. Over the years, multiple studies regarding humans and their daily motion habits have been investigated for many different purposes. This fact is not surprising when we look at all the opportunities and applications that can be applied and utilized thanks to the results of these algorithms. In this project we implement a system that can effectively collect sensor data from mobile devices, process it and by using supervised machine learning successfully predict the class of a performed activity. The project was executed based on datasets and features extracted from GPS sensors. The system was trained using various machine learning algorithms and Python SciKit to guarantee optimal solutions with accurate predictions. Finally, we applied a majority vote rule to secure the best possible accuracy of the activity classification process. As a result we were able to identify various activities including walking, cycling, driving and public transportation methods bus and metro with 90+% accuracy. Att utföra aktivitetsigenkänning på människor har blivit ett populärt forskningsämne bland datavetare, där flertalet studier rörande människor och deras dagliga rörelsevanor undersökts för många olika syften. Detta är inte förvånande när man ser till de möjligheter och användningsområden som kan tillämpas och utnyttjas tack vare resultaten från dessa system. Detta projekt går ut på att implementera ett system som mha samlad sensordata från mobila enheter, kan bearbeta den och genom s.k övervakad maskininlärning med goda resultat bestämma den aktivitet som utförts. Projektet genomfördes baserat på dataset och egenskaper extraherade från GPS-data. Systemet tränades med olika maskininlärningsalgoritmer genom Python SciKit för att välja den bäst lämpade metoden för detta projekt. Slutligen tillämpade vi majority votemetoden för att säkerställa bästa möjliga noggrannhet i aktivitetsklassificeringsprocessen. Resultatet blev ett system som framgångsrikt kan identifiera aktiviteterna gå, cykla, köra bil samt med ett ytterligare fokus på kollektivtrafikmetoderna buss och tunnelbana, med en noggrannhet på över 90%. Kandidatexjobb i elektroteknik 2020, KTH, Stockholm

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Greenall, John Patrick. "High-level activity learning and recognition in structured environments." Thesis, University of Leeds, 2012. http://etheses.whiterose.ac.uk/3231/.

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Automatic recognition of events in video is an immensly challenging problem. If solved, the number of potential domains in which such a system could be deployed is vast and growing; including traffic monitoring, surveillance, security, elderly care and semantic video search to name but a few. Much prior research in the area has focused on producing a solution that is tailored towards one of these applications, applying methods which are most appropriate given the constraints of the target domain. For the moment, this remains to some extent the only practical way to approach the problem. The aim in this thesis is to build a high-level framework for event recognition which is in the main generic and widely transferrable, yet allows domain-appropriate elements to be incorporated. A detector is constructed for low-level events which is based on dense extraction of Histograms of Optical Flow. This descriptor has only recently been adopted by the event detection community, and as such there are aspects of the features which have not been optimized. This thesis performs extensive experimentation on normalization scheme and finds that the strategy most widely in use is suboptimal compared to one of the alternatives proposed. The detector is then trained on a challenging real world domain to run in a sliding window fashion on continuous video input. A high level model which exploits temporal relations between different event types is constructed. The model is designed with transferrability and computational tractability in mind. Several methods are benchmarked for learning the distributions over time differences between pairs of events. Three different connection strategies are proposed and evaluated for creating a tree structured prior that permits fast, exact inference. An efficient iterative optimization scheme is presented for handling scenarios which contain unknown numbers of event instances. Finally, the model is extended in a Conditional Random Field framework that allows weights to be learned to balance the response from independent detectors with the pairwise temporal relationships.

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Brown, Jamie Branam, Mary R. Langenbrunner, and Teresa Brooks-Taylor. "Oppression Activity Using the Mechanism of Social Service Learning." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etsu-works/5867.

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Li, Huiyong. "Enhancing Students' Self-Direction Skill with Learning and Physical Activity Data." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263776.

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Mahdaviani, Maryam. "Semi-supervised and active training of conditional random fields for activity recognition." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/346.

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Automated human activity recognition has attracted increasing attention in the past decade. However, the application of machine learning and probabilistic methods for activity recognition problems has been studied only in the past couple of years. For the first time, this thesis explores the application of semi-supervised and active learning in activity recognition. We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs),a probabilistic graphical model. In real-world applications such as activity recognition, unlabeled sensor traces are relatively easy to obtain whereas labeled examples are expensive and tedious to collect. Furthermore, the ability to automatically select a small subset of discriminatory features from a large pool can be advantageous in terms of computational speed as well as accuracy. We introduce the semi-supervised virtual evidence boosting (sVEB)algorithm for training CRFs — a semi-supervised extension to the recently developed virtual evidence boosting (VEB) method for feature selection and parameter learning. sVEB takes advantage of the unlabeled data via mini-mum entropy regularization. The objective function combines the unlabeled conditional entropy with labeled conditional pseudo-likelihood. The sVEB algorithm reduces the overall system cost as well as the human labeling cost required during training, which are both important considerations in building real world inference systems. Moreover, we propose an active learning algorithm for training CRFs is based on virtual evidence boosting and uses entropy measures. Active virtual evidence boosting (aVEB) queries the user for most informative examples, efficiently builds up labeled training examples and incorporates unlabeled data as in sVEB. aVEB not only reduces computational complexity of training CRFs as in sVEB, but also outputs more accurate classification results for the same fraction of labeled data. Ina set of experiments we illustrate that our algorithms, sVEB and aVEB, benefit from both the use of unlabeled data and automatic feature selection, and outperform other semi-supervised and active training approaches. The proposed methods could also be extended and employed for other classification problems in relational data.

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Malmberg, J. (Jonna). "Tracing the process of self-regulated learning – students’ strategic activity in g/nStudy learning environment." Doctoral thesis, Oulun yliopisto, 2014. http://urn.fi/urn:isbn:9789526204703.

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Abstract This study focuses on the process of self-regulated learning by investigating in detail how learners engage in self-regulated and strategic learning when studying in g/nStudy learning environments. The study uses trace methods to enable recognition of temporal patterns in learners’ activity that can signal strategic and self-regulated learning. The study comprises three data sets. In each data set, g/nStudy technology was used to support and trace self-regulated learning. In the analysis, micro-analytical protocols along with qualitative approach were favoured to better understand the process of self-regulated and strategic learning in authentic classroom settings. The results suggested that the specific technological tools used to support strategic and self-regulated learning can also be used methodologically to investigate patterns emerging from students’ cognitive regulation activity. The advantage of designing specific tools to trace and support self-regulated learning also helps to interpret the way in which the learning patterns actually inform SRL theoretically and empirically. Depending on how the tools are used, they can signal the typical patterns existing in the learning processes of students or student groups. The learning patterns found in the students’ cognitive regulation activity varied in terms of how often the patterns emerged in their learning, how the patterns were composed and when the patterns were used. Moreover, there were intra-individual differences – firstly, in how students with different learning outcomes allocated their study tactic use, and secondly, how self-regulated learning was used in challenging learning situations perceived by students. These findings indicate log file traces can reveal differences in self-regulated learning between individuals and between groups of learners with similar characteristics based on the learning patterns they used. However, learning patterns obtained from log file traces can sometimes be complex rather than simple. Therefore, log file traces need to be combined with other situation-specific measurements to better understand how they might elucidate self-regulated learning in the learning context Tiivistelmä Tässä väitöskirjassa tutkitaan oppilaiden itsesäätöisen ja strategisen oppimisen ilmenemistä oppimisprosessin aikana. Tutkimuksessa hyödynnetään g/nStudy- oppimisympäristöä, jonka avulla on mahdollista tukea ja jäljittää oppimisen strategista toimintaa. g/nStudy-oppimisympäristö tallentaa lokidataa, joka on tarkkaa ajallista informaatiota siitä toiminnasta, jota oppilas tekee työskentelynsä aikana. Toisin sanoen, lokidatasta on mahdollista jäljittää ne tiedot, jotka reflektoivat strategista – ja itsesäätöistä oppimista. Erityisenä mielenkiinnon kohteena oli selvittää miten lokidatasta voi löytää strategisia oppimisen toimintamalleja, ja miten nämä strategiset oppimisen toimintamallit vaihtelevat oppilaiden, oppilasryhmien ja erilaisten oppimisen tilanteiden aikana. Väitöstutkimus muodostuu kolmesta erillisestä tutkimusaineistosta. Jokaisessa kolmessa aineistossa on hyödynnetty g/nStudy-teknologian mahdollisuuksia tukea ja jäljittää itsesäätöistä oppimista. Tutkimusaineiston analyysissä hyödynnetään mikroanalyyttista lähestymistapaa sekä laadullista tutkimusotetta. Tutkimuksen analyyttinen lähestymistapa antaa mahdollisuuden ymmärtää itsesäätöisen- ja strategisen oppimisen ilmenemistä aidossa oppimistilanteessa. Tutkimustulokset osoittavat, että oppimisympäristöön sisällytettyjä teknologisia työkaluja voidaan käyttää tukemaan itsesäätöistä ja strategista toimintaa. Sen lisäksi samoja työkaluja voidaan käyttää myös menetelmällisenä välineenä tutkittaessa itsesäätöistä – ja strategista toimintaa erilaisissa oppimistilanteissa. Tutkimus -tulokset osoittavat, että oppimisen strategiset toimintamallit vaihtelivat oppilaiden – ja oppimistilanteiden välillä. Oppimisen strategisissa toimintamalleissa oli myös laadullisia eroja sen suhteen, miten usein ne ilmenivät oppimisprosessin aikana ja mistä strategisista toiminnoista ne koostuivat. Johtopäätöksenä voi todeta, että lokidatan käyttäminen tutkimusmenetelmänä edesauttaa paljastamaan opiskelun strategisia toimintamalleja oppilaiden – ja oppilasryhmien välillä. Tutkimuksen perusteella voidaan todeta, että strategiset toimintamallit voivat olla hyvinkin monimuotoisia. On tärkeää tunnistaa, missä tilanteissa ja milloin näitä toimintamalleja käytetään ja erityisesti mikä on niiden vaikutus oppimisen laatuun

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Bygrave, Patricia, and n/a. "Music as a cognitive developing activity : implications for learning and for the learning disabled child." University of Canberra. Education, 1985. http://erl.canberra.edu.au./public/adt-AUC20060622.143654.

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Various cognitive learning theories have been examined for the purpose of considering music as an activity developing cognitive processes. It was felt that an exploration of these theories could offer insights into how music can be used to demonstrate cognitive development in learning and in children with learning disabilities. In an attempt to illustrate the relationship between music and cognition, concepts in the theories of Piaget, the Neo-Piagetians (Case, Pascaul-Leone, Biggs and Collis), Bruner, Ausubel, Vygotsky, Luria and Leont'ev have been discussed in association with music activities. It is argued that music can be identified as a cognitive activity and applied to learning and to learning disabilities through recognised special education approaches; these include perceptual-motor, multi-sensory, languagedevelopment related, developmental and behavioural. The theories of Vygotsky, Luria and Leont'ev - the 'troika' - are considered in greater detail. Their theories, although focussing on concepts of language in cognitive development, appear to offer a means for the wider application of music to cognitive development. Vygotsky's developmental hierarchy, Luria's brain functional system, and Leont'ev's theory of activity have been amalgamated into a theoretical framework demonstrating the processing of information through music activity leading to cognitive development. This framework provides for an investigation into learning capacities and learning potential, relevant to cognitive development in learning and in the learning disabled child.

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Langdon, Jonathan. "Democracy and social movement learning in Ghana: reflections on 15 years of learning in the democratic terrain by Ghanaian activist-educators." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86816.

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Ghana's democracy is a widely-known African good news story. What is not known about this story is how this democracy's dynamism is fundamentally grounded on ongoing social movement activism that is constantly pressurizing the largely elite democratic institutions to better respond to the everyday needs of average Ghanaians. Critical to this pressurization is not only activism around domestic policies, but also a wide-spread ongoing questioning of the forces of transnational neoliberal governmentality that discipline, contain, and subvert the potential of African states to place the needs of their populace in-front of the needs of transnational capital. This is the alternative story of Ghana's democracy told by this study, where Ghanaian activist-educators embedded in the country's various contemporary social movements have come together in a participatory research endeavour to critically analyze Ghana's current democratic terrain. Key to this analysis is the connection between Ghana's social movement activism, and learning within these movements, to this reconstituted story of Ghana's democracy. According to our participatory research group, it is the intersection of the ways movements learn and communicate with the ways these movements stay rooted in the needs of their wider membership that concomitantly determines their impact on the range of democratic possibility. Instrumental to this intersection, according to this study, are the informal processes through which movement members learn in, through, and to struggle. It is from our mutually-constituted understanding of these processes that our participatory research is now leading to action. La démocratie du Ghana constitue une bonne nouvelle africaine. Ce qu'on ne sait pas au sujet de cette nouvelle, c'est la façon dont le dynamisme de la démocratie est fondamentalement basé sur l'activisme continu des mouvements sociaux qui exercent une pression constante sur les grandes institutions démocratiques d'élite afin qu'elles répondent mieux aux besoins quotidiens des Ghanéens. En plus de l'activisme relatif aux politiques intérieures, le questionnement constant et répandu des forces de la gouvernementalité néolibérale transnationale qui contrôlent, limitent et minent le potentiel des États africains à placer les besoins de leur population avant les besoins de la capitale transnationale, s'avère essentiel à cette pression. Voici l'autre version de la démocratie du Ghana racontée par la présente étude, au cours de laquelle des éducateurs activistes ghanéens participant à divers mouvements sociaux contemporains du pays se sont réunis dans le cadre d'une initiative de recherche participative visant à faire une analyse critique du terrain démocratique actuel du Ghana. Le lien entre l'activisme des mouvements sociaux du Ghana, l'apprentissage au sein de ces mouvements, et cette histoire reconstituée de la démocratie du Ghana s'avèrent essentiel à l'analyse. Selon notre groupe de recherche participative, le croisement des façons dont les mouvements apprennent et communiquent et des façons dont ces mouvements restent ancrés dans les besoins de leurs membres, détermine en même temps leur incidence sur l'éventail de possibilités au plan démocratique. Selon la présente étude, les processus informels par l'entremise desquels les membres des mouvements apprennent et luttent sont essentiels à ce croisement. Grâce à notre compréhension mutuelle de ces processus, notre recherche participative nous permet maintenant d'agir.

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Chung, Chak. "The implementation of the activity approach in Hong Kong." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18540296.

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Cool, Kathleen Leni. "Informal Learning as Performance: Toward a Hermeneutic Phenomenology of Museum Learning in Second Life." NSUWorks, 2013. http://nsuworks.nova.edu/gscis_etd/124.

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This study explored how avid users of Second Life (SL) experience and make meaning of informal learning activities in virtual art museums and similar cultural spaces through their avatars. While recent literature has laid the groundwork for studying student engagement and formal learning, the lacuna of research bound by the historical traditions of qualitative research design has done little to ease the skepticism surrounding the value of virtual worlds for learning. Within the context of museological discourse, virtual museum learning experiences have the potential to shift viewing practices as well as how meaning is generated, interpreted, and disseminated. Technical, conceptual, and methodological barriers to studying virtual worlds remain. Another goal of this study was to demonstrate the potential of hermeneutic phenomenology, particularly my conceptualization of virtual hermeneutics, to study virtual worlds. Hermeneutic phenomenology has the potential to make practical understanding of the informal learning process in SL explicit by providing an interpretation of this process. The challenge lies in applying the philosophy behind the methodology to the changing reality of virtual worlds. It is only by studying these experiences in context and situated within virtual spaces that we can expand our understanding of the avatar-mediated informal learning process. Findings from this study show that in-world informal learning experiences can, in fact, be studied on their own terms. Furthermore, rich textural data can not only be extracted from exclusively in-world interaction, but collaborative relationships can also develop with no actual world contact. These experiences and interactions can lead to experiential learning, but also transformational learning where the avatar-identity can affect users' actual world viewing practices and meaning making. It is not so much the technology per se that can affect change, but rather identity exploration, diegesis, and relationship building afforded by the technology. Albeit some learning outcomes were observed, affective outcomes and cognitive strategies, including metacognitive skills, were more frequently described by participants. Due to the complexity of assessing such outcomes and the present obsession with quantitatively measurable outcomes in formal education, it is unlikely that SL can or will be used outside the scope of informal learning in the near future unless formal education undergoes social reform.

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Blandon, Alondra Marcela. "Incorporating multicultural education criteria into Project Learning Tree curricula." CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3285.

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Many environmental educators have realized that in order to effectively teach environmental sensitivity and literacy, they must approach their audience through a cultural context. Thus, environmental education lessons need to incorporate strategies used in multicultural education in order to be more culturally inclusive. This project includes the identification of multicultural education criteria and the application of these to three lessons from Project Learning Tree: PreK-8 Environmental Education Activity Guide.

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Thievenaz, Joris. "Construction de l’expérience et transformation silencieuse des habitudes d’orientation de l’action : Le cas de l’activité dialogale du médecin du travail." Thesis, Paris, CNAM, 2012. http://www.theses.fr/2012CNAM0831/document.

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À travers une entrée par l’activité, cette recherche se donne pour objet la compréhension des processus selon lesquels le sujet construit son expérience en réélaborant ses « habitudes d’activités ». L’analyse de l’activité de plusieurs médecins du travail lors de consultations avec les salariés des entreprises dont ils assurent le suivi, nous permet de réaliser l’hypothèse selon laquelle le dialogue qui s’y déroule constitue pour ces acteurs un moyen privilégié de conduire leur action de prévention, mais également d’apprendre au contact d’autrui. En mobilisant la théorie de « l’enquête » de J. Dewey, nous montrons comment ces médecins sont susceptibles de transformer les habitudes qui orientent leur action, lorsqu’ils sont confrontés à une situation insuffisamment déterminée. Nous pensons que ces transformations qui se réalisent dans et par l’action, constituent au fil du temps, une des voies privilégiées du « travail de l’expérience » du sujet en situation professionnelle By focusing on the activity, this research aims to understand the process through which the subject constructs his experience by re-developing his “activity habits”. By analyzing the activities of a number of occupational health physicians during their consultations with patients (who are business employees), we may hypothesize that the dialogue which unfolds between the physicians and the patients is a means for physicians to take preventative action and to connect with others. By mobilising J. Dewey’s theory of the “inquiry”, we show how these physicians may transform the habits that orient their action when they are confronted with a situation that is insufficiently determined. We think that these transformations take place in and through actions, constituting

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Opushnyev, Serhiy. "Neuronal growth patterns in states of learning and activity blockade." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/61075.

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The role of activity on the formation of neural networks during development is known to be critical. In the research conducted for this dissertation the effect of experience was probed at the single neuron level. First, a method for selecting neurons based on their responses to a visual stimulus and electroporating the selected neurons in a somata dense region was developed. This method was then used to select neurons responsive to a predetermined visual stimulus and the growth behavior of the neuronal arbor was observed in the presence of visual stimuli. When neurons were trained to better discern the visual stimulus the plasticity of the neuron was correlated with the dendritic growth behavior. In general, responsive neurons tended to prune their dendritic arbors while non-responsive neurons tended to grow. Interestingly, neurons that acquired a response with training tended to grow before acquiring a response and prune after. Blockade of NMDA receptors abolished these effects. In a separate set of experiments dendritic growth patterns were observed while all excitatory activity was blocked pharmacologically. These experiments showed that short-term (1.5 hours) excitatory activity blockade does not alter dendritic growth patterns. However, 30 minutes after the start of the activity blockade, the density of filopodia increased, suggesting that the neuron was compensating for the lack of activity. Medicine, Faculty of Graduate

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Xie, Xiaohui 1972. "Spike-based learning rules and stabilization of persistent neural activity." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86625.

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Dissertations / Theses on the topic 'Activist learnings'

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