Дисертації з теми "Learning tracks"
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1
Tang, Fung Michael, and 鄧峰. "Sequence classification and melody tracks selection." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B29742973.
2
Tang, Fung Michael. "Sequence classification and melody tracks selection /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25017470.
3
Unger, Mary Ann. "Traversing the tracks : students with learning disabilities speak up /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/7788.
4
Krigström, Rasmus. "Learning Tracks : En studie om auditiva hjälpmedel vid instudering av körmusik." Thesis, Kungl. Musikhögskolan, Institutionen för musik, pedagogik och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kmh:diva-4231.
Анотація:
Denna studie är gjord på ämnet learning tracks, dvs auditiva instuderingsfiler för vokalmusik. Det finns ingen historisk forskning eller annan tidigare forskning på ämnet men man vet att det har förekommit som fenomen inom genren barbershop lika länge som den portabla kassettbandspelaren, och på senare år utvecklats mycket i och med internet samt möjligheten att spela in och editera musik på en hemdator. Angränsande forskning om spegelneuroner, inlärning på gehör och körmetodik har studerats som forskningsgrund och det sociokulturella perspektivet samt variationsteori är studiens teoretiska perspektiv. Syftet med studien är att undersöka vilka variationer i musikaliskt resultat samt i elevernas upplevelse av instudering som kan urskiljas kopplat till notbaserad instudering av körmusik, respektive instudering med hjälp av instuderingsfiler som komplement. Två testgrupper, en som fick jobba med instuderingsfiler som komplement till noter och en som bara fick instudera med noter, jobbademed ett stycke musik under fyra lektionspass som observerades och ljud spelades in för att kunna följa progressionen i instuderingen. En enkät till samtliga elever som deltog som frågade om deras upplevelse av instuderingen fylldes i direkt efter studiens avslut. Resultatet var tydligt, både utifrån testgruppernas musikaliska prestation och ifrån deras egen upplevelse av instuderingen, instuderingsfiler var för dem bättre än enbart noter. Resultatet går även att tydligt knyta an till den angränsande tidigare forskningen på ämnet. Även om studien är tydlig behövs det mer forskning inom detta område.This study is on the subject of music learning tracks for learning a capella music. While there is no specific research on the subject yet it has been known as a phenomenon in the genre of barbershop harmony for as long as the tape recorder has been around, and has grown into a well-established business because of the internet and the possibilities of editing music on home computers. Earlier research in surrounding areas such as choir methodology, ear training and mirror neurons have laid the research ground for the study, and the theoretical perspectives which the data was analyzed through are the sociocultural perspective and variation theory. The purpose of this study is to explore variations in musical results and the pupils experience of learning that can be detected between a group that studies with learning tracks and a group that studies without learning tracks. The two groups were followed learning the same piece of music during four classes through observation and recording of sound. Directly following the last class, the students answered a survey about their experience of the learning process. The results were clear, both from the difference in musical results and from the answers in the survey, learning tracks are better for learning new music than just using sheet music. The results also connect to earlier research in surrounding areas, but even though the results of this study are clear more research is needed in this specific area.
5
Brodin, Johan. "Working with emotions : Recommending subjective labels to music tracks using machine learning." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199278.
Анотація:
Curated music collection is a growing field as a result of the freedom and supply that streaming music services like Spotify provide us with. To be able to categorize music tracks based on subjective core values in a scalable manner, this thesis has explored if recommending such labels are possible through machine learning. When analysing 2464 tracks with one or more of the 22 different core values a profile was built up for each track by features from three different categories: editorial, cultural and acoustic. When classifying the tracks into core values different methods of multi-label classification were explored. By combining five different transformation approaches with three base classifiers and using two algorithm adaptations a total of 17 different configurations were constructed. The different configu- rations were evaluated with multiple measurements including (but not limited to) Hamming Loss, Ranking Loss, One error, F1 score, exact match and both training and testing time. The results showed that the problem transformation algorithm Label Powerset together with Sequential minimal optimization outper- formed the other configurations. We also found promising results for neural networks, something that should be investigated further in the future.Kurerade musiksamlingar är ett växande område som en direkt följd av den frihet som strömmande musiktjänster som Spotify ger oss. För att kunna kategorisera låtar baserade på subjektiva värderingar på ett skalbart sätt har denna avhandling undersökt om rekommendationer av sådana etiketter är möjliga genom maskininlärning. När 2464 spår med ett eller flera av 22 olika kärnvärden analyserades byggdes en profil för varje spår upp av attribut från tre olika kategorier: redaktionella, kulturella och akustiska. Vid klassificering av spåren undersöktes flera olika metoder för fleretikettsklassificering. Genom att kombinera fem olika transformationsmetoder med tre bas-klassificerare och använda två algoritm-anpassningar konstruerades totalt 17 olika konfigurationer. De olika konfigurationerna utvärderades med flera olika mätvärden, inkluderat (men inte begränsat till) Hamming Loss, Ranking Loss, One error, F1 score, exakt matchning och både träningstid och testningstid. Resultaten visade att transformationsalgoritmen ”Label Powerset” tillsammans med Sekventiell Minimal Optimering utklassade de andra konfigurationerna. Vi fann också lovande resultat för artificiella neuronnät, något som bör undersökas ytterligare i framtiden.
6
Howell, Jamie Robert. "Learning through stories : An investigation into how Tracks Rites of Passage Programme impacts on the development of young men and their family systems." Thesis, University of Canterbury. Educational Studies and Leadership, 2012. http://hdl.handle.net/10092/7611.
Анотація:
The Tracks rites of passage are processes that mark the adolescent transition, for the participant, the family and the community, between the two life stages of childhood and adulthood. Adolescent initiation rites offer a community led journey of separation, transition and integration as a way to work meaningfully with adolescents as they move between the life stages of childhood into adulthood. In Aotearoa/New Zealand the Tracks programme provides a five day contemporary rite of passage for adolescents and, where possible, their fathers. The rite of passage is based on the assumption that adolescents need opportunities to find their voices and make meaning if they are to become more aware of who they are and where they belong.
The methodology recognises that I, as researcher and insider in the Tracks organisation, needed to develop a holistic approach to insider research so that I could call on my understandings of the organisation and also guard against bias. The holistic approach involves the four interpenetrating strategies of appreciative inquiry, narrative inquiry, a blend of approaches to self-study that include meditation and critical reflection, and most importantly organic inquiry. The four strategies are based on coherence theories that describe learning as being organic, interconnected and emergent. Data were gathered from interviews and cycles of critical self-reflection in the form of a learning journal.
Data comes from interviews with the mother or fathers and young men of six families who have participated in the Tracks rite of passage programme. I have also discussed this work with a number of professionals in the field of youth work. The project found that Tracks had created conditions that empowered these young men with an increased capacity to make sense of their lives. Fathers expressed how challenging and rewarding they had found it to speak in honest terms with their sons, and that they were supported to do the inner work necessary to be able to speak in such ways. All of the family members expressed a need to have more support after the event.
The findings suggest a need to explore further the nature of the work happening at Tracks. It validates Lashlie’s (2005) theory that adolescents need their fathers and other men to be involved in their lives at the time of transition. Tracks also helps fathers to get to grips with the inner work of developing emotional maturity. The work happening at Tracks invites further research into and debate on the value of emotional intelligence. The Tracks rite of passage offers an alternative perspective to understand the unacceptably high rates of adolescent morbidity and mortality happening in New Zealand.
7
Li, Jingxian. "Reinforcement learning using sensorimotor traces." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45590.
Анотація:
The skilled motions of humans and animals are the result of learning good solutions
to difficult sensorimotor control problems. This thesis explores new models
for using reinforcement learning to acquire motion skills, with potential applications
to computer animation and robotics. Reinforcement learning offers a principled
methodology for tackling control problems. However, it is difficult to apply
in high-dimensional settings, such as the ones that we wish to explore, where the
body can have many degrees of freedom, the environment can have significant
complexity, and there can be further redundancies that exist in the sensory representations
that are available to perceive the state of the body and the environment.
In this context, challenges to overcome include: a state space that cannot be fully
explored; the need to model how the state of the body and the perceived state of
the environment evolve together over time; and solutions that can work with only
a small number of sensorimotor experiences.
Our contribution is a reinforcement learning method that implicitly represents
the current state of the body and the environment using sensorimotor traces. A
distance metric is defined between the ongoing sensorimotor trace and previously
experienced sensorimotor traces and this is used to model the current state as a
weighted mixture of past experiences. Sensorimotor traces play multiple roles in
our method: they provide an embodied representation of the state (and therefore
also the value function and the optimal actions), and they provide an embodied
model of the system dynamics.
In our implementation, we focus specifically on learning steering behaviors for
a vehicle driving along straight roads, winding roads, and through intersections.
The vehicle is equipped with a set of distance sensors. We apply value-iteration using off-policy experiences in order to produce control policies capable of steering
the vehicle in a wide range of circumstances. An experimental analysis is provided
of the effect of various design choices.
In the future we expect that similar ideas can be applied to other high-dimensional
systems, such as bipedal systems that are capable of walking over variable terrain,
also driven by control policies based on sensorimotor traces.
8
Taylor, Teresa Brooks. "Service-Learning/Civic Engagement Track." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/3632.
9
Riviere, Jean-Philippe. "Capturing traces of the dance learning process." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG054.
Анотація:
Cette thèse porte sur la conception d’outils interactifs pour comprendre et faciliter l’apprentissage de la danse à partir de vidéos. Les processus d’apprentissage des danseurs représentent une source d’informations riches pour les chercheurs qui s’intéressent à la conception de systèmes soutenant l’apprentissage moteur. En effet, les danseurs experts réutilisent un large éventail de compétences qu’ils ont appris. Cependant, ces compétences sont en partie le résultat de connaissances implicites et incarnées,qui sont difficilement exprimables et verbalisables par un individu.Dans cette thèse, je soutiens que nous pouvons capturer et sauvegarder une trace des connaissances implicites des danseurs et les utiliser pour concevoir des outils interactifs qui soutiennent l’apprentissage de la danse. Mon approche consiste à étudier différentes sessions d’apprentissage de danse dans des contextes réels, aussi bien individuels que collaboratifs.Sur la base des résultats apportés par ces études, je contribue à une meilleure compréhension des processus implicites qui sous-tendent l’apprentissage de la danse dans des contextes individuels et collectifs. Je présente plusieurs stratégies d’apprentissage utilisées par des danseurs et j’affirme que l’on peut documenter ces stratégies en sauvegardant une trace de l’apprentissage. Je discute de l’opportunité que représente la capture de ces connaissances incarnées et j’apporte de nouvelles perspectives pour la conception d’outils d’aide à l’apprentissage du mouvement par la vidéoThis thesis focuses on designing interactive tools to understand and support dance learning from videos. Dancers' learning practice represents a rich source of information for researchers interested in designing systems that support motor learning. Indeed, dancers embody a wide range of skills that they reuse during new dance sequences learning. However, these skills are in part the result of embodied implicit knowledge. In this thesis, I argue that we can capture and save traces of dancers' embodied knowledge and use them to design interactive tools that support dance learning. My approach is to study real-life dance learning tasks in individual and collaborative settings. Based on the findings from all the studies, I discuss the challenge of capturing embodied knowledge to support dancers’ learning practice. My thesis highlights that although dancers’ learning processes are diverse, similar strategies emerge to structure their learning process. Finally, I bring and discuss new perspectives to the design of movement-based learning tools
10
Meza, Fernandez Sandra. "Enseigner et apprendre en ligne : vers un modèle de la navigation sur des sites Web de formation universitaire." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-00974481.
Анотація:
Cette thèse propose de cartographier le parcours de navigation des usagers des EIAH pour le visualiser, visualiser pour interpréter et interpréter pour anticiper. Les profils d'apprentissage ont une influence sur les modes de navigation dans un environnement d'apprentissage en ligne. S'appuyant sur une méthodologie capable de modéliser le parcours de navigation d'un usager et d'anticiper son prochain clic sur une plateforme, notre étude cherche à élargir le champ des connaissances de l'efficacité/performance des styles d'apprentissage. La méthodologie utilisée repose sur l'analyse des traces d'utilisation élaborée à partir de 63 archives logs Web, incluant 4637 lignes de registre et 13 206 possibilités de choix de module. Le travail de recherche s'inscrit dans le cadre d'approches associant sémiologie, des sciences de l'information, psychologie cognitive et sciences de l'éducation. Trois observations ont été menées, générant des informations sur le profil de l'usager, la représentation des parcours et l'impact du style d'apprentissage dans le choix des fonctionnalités de travail offertes disponibles sur la plateforme. Les principaux résultats sont de deux types : d'une part, l'élaboration d'un outil convertissant les traces des fichiers log en parcours de navigation, et d'autre part, la confirmation d'un lien entre style d'apprentissage et mode de navigation. Ce deuxième résultat permet d'élaborer une méthode d'anticipation du nouveau choix de module sur une plateforme numérique de travail. Les applications pratiques visant à rendre exploitables ces traces dans les formations universitaires sont l'élaboration de bilans de qualité (ressources préférées, fonctionnalités moins utilisées) et l'identification des besoins de médiation pédagogique pour la compréhension de la tâche ou du processus (identifié par exemple dans l'insistance sur le module de consignes, le temps investi par un groupe ou par des trajets répétés). Cette thèse s'adresse principalement aux responsables pédagogiques universitaires décideurs de l'intégration des TIC, et par extension, aux étudiants universitaires et aux concepteurs d'outils d'apprentissage.
11
Palmieri, Elena. "Learning declarative process models from positive and negative traces." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22501/.
Анотація:
In the recent years, the growing number of recorded events made the interest in process mining techniques expand. These techniques make it possible to learn the model of a process, to compare a recent event log with an existing model or to enhance the process model using the information extracted from the log. Most of the existing process mining algorithms only make use of positive examples of a business process in order to extract its model, however, negative ones can bring major benefits. In this work, a discovery algorithm, inspired by the one presented by Mooney in 1995, that takes advantage of both positive and negative sequences of actions is presented in two different versions that return a declarative model connected respectively in disjunctive and conjunctive logic formulas.
12
Lu, Wei-Lwun. "Learning to track and identify players from broadcast sports videos." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/39956.
Анотація:
Tracking and identifying players in sports videos filmed with a single pan-tilt-zoom camera has many applications, but it is also a challenging problem. This thesis introduces the first intelligent system that tackles this difficult task. The system possesses the ability to detect and track multiple players, estimates the homography between video frames and the court, and identifies the players. The tracking system is based on the tracking-by-detection philosophy. We first localize players using a player detector, categorize detections based on team colors, and then group them into tracks of specific players. Instead of using visual cues to distinguish between players, we instead rely on their short-term motion patterns. The homography estimation is solved by using a variant of the Iterated Closest Points (ICP). Unlike most existing algorithms that rely on matching robust feature points, we propose to match edge points in two images. In addition, we also introduce a technique to update the model online to accommodate logos and patterns in different stadiums. The identification system utilizes both visual and spatial cues, and exploits both temporal and mutual exclusion constraints in a Conditional Random Field. In addition, we propose a novel Linear Programming Relaxation algorithm for predicting the best player identification in a video clip. In order to reduce the number of labeled training data required to learn the identification system, we pioneer the use of weakly supervised learning with the assistance of play-by-play texts. Experiments show promising results in tracking, homography estimation, and identification. Moreover, weakly supervised learning with play-by-play texts greatly reduces the number of labeled training data required. Experiments show that we can use weakly supervised learning with merely 200 labels to achieve similar accuracies to a strongly supervised approach, which requires at least 20000 labels.
13
Kaland, Cecilia. "Organizational learning : A qualitative analysis of conditions and predecessors for organizational learning in Fast Track." Thesis, Norges teknisk-naturvitenskapelige universitet, Psykologisk institutt, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-21720.
Анотація:
This study has explored the process of knowledge sharing within an organizational context. Furthermore, it has explored the occurrence of organizational learning and explored the PRIMA method in light of organizational learning. The origin of the study is based on cooperation with a division X within Statoil ASA. In order to illuminate the research question we chose to utilize a qualitative approach. All informants were connected to Fast Track and a total of 8 in depth semi-structured interviews were carried out. Furthermore, grounded theory was utilized as our method and tool for analysis. The results found indicate that knowledge is mostly shared within informal forums. Nevertheless, both formal and informal structures are utilized as knowledge sharing channels. However, the results also indicate that certain facets are important predecessors for knowledge sharing to take place, such as good relations, trust and motivation. Furthermore, it appears that a positive flow of communication depends upon common understanding and shared mental maps. The results also illuminate a challenge in regards to sustaining knowledge learnt in Fast Track within formal channels. Lastly, results indicate that the PRIMA holds potential for organizational learning, but mostly so when employees are invited to participate. However, in regards to raising awareness it appears to be insufficient beyond the management level. The results also contribute to illuminate future implications for organizational learning and the PRIMA method. Based on the results it is suggested that the organization arrange for the development of new networks across subcultures like professions and that they arrange for dialogue to create common understandings and shared mental maps to guide their employees’ actions. In addition, it is suggested that PRIMA utilize the potential of its workshops to create arenas for dialogue. Most of all the results illuminate the necessity of inviting the organizations employees to participate in the utilization of the PRIMA method.
14
Jilani, Rabia. "Learning static knowledge for AI planning domain models via plan traces." Thesis, University of Huddersfield, 2017. http://eprints.hud.ac.uk/id/eprint/34414/.
Анотація:
Learning is fundamental to autonomous behaviour and from the point of view of Machine Learning, it is the ability of computers to learn without being programmed explicitly. Attaining such capability for learning domain models for Automated Planning (AP) engines is what triggered research into developing automated domain-learning systems. These systems can learn from training data. Until recent research it was believed that working in dynamically changing and unpredictable environments, it was not possible to construct action models a priori. After the research in the last decade, many systems have proved effective in engineering domain models by learning from plan traces. However, these systems require additional planner oriented information such as a partial domain model, initial, goal and/or intermediate states. Hence, a question arises - whether or not we can learn a dynamic domain model, which covers all domain behaviours from real-time action sequence traces only. The research in this thesis extends an area of the most promising line of work that is connected to work presented in an REF Journal paper. This research aims to enhance the LOCM system and to extend the method of Learning Domain Models for AI Planning Engines via Plan Traces. This method was first published in ICAPS 2009 by Cresswell, McCluskey, and West (Cresswell, 2009). LOCM is unique in that it requires no prior knowledge of the target domain; however, it can produce a dynamic part of a domain model from training. Its main drawback is that it does not produce static knowledge of the domain, and its model lacks certain expressive features. A key aspect of research presented in this thesis is to enhance the technique with the capacity to generate static knowledge. A test and focus for this PhD is to make LOCM able to learn static relationships in a fully automatic way in addition to the dynamic relationships, which LOCM can already learn, using plan traces as input. We present a novel system - The ASCoL (Automatic Static Constraints Learner) which provides a graphical interface for visual representation and exploits directed graph discovery and analysis technique. It has been designed to discover domain-specific static relations/constraints automatically in order to enhance planning domain models. The ASCoL method has wider applications. Combined with LOCM, ASCoL can be a useful tool to produce benchmark domains for automated planning engines. It is also useful as a debugging tool for improving existing domain models. We have evaluated ASCoL on fifteen different IPC domains and on different types of goal-oriented and random-walk plans as input training data and it has been shown to be effective.
15
Lindqvist, Björn. "Music generation using tracker music and machine learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302573.
Анотація:
We investigate the modelling of polyphonic “tracker music” using deep neural networks. Tracker music is a music storage format invented in the late 1980s for use on that time’s home computers and is often used for storing synthesized electronic music. Tracker music differs significantly from other music formats and has properties that makes it both harder and easier to use for training neural networks than other formats. This makes it interesting to explore what methods are most suitable for extracting musical information from the format. As far as we know, we are the first to explore how to use tracker music for music generation. We design a method for turning tracker music into sequential data usable for training neural networks. The sequential nature of the data means that musically unaware sequence models can be used for training. The method is general and can be applied to other kinds of symbolic music. We then compile a dataset of about 20 000 freely available instrumental songs in the tracker format MOD, downloaded from the website The Mod Archive. We use the dataset to train several different sequence models, including a Long Short-Term Memory (LSTM) network and a Transformer model. We evaluate the models using a sequence completion task and we investigate the statistical properties of the output. We also conduct a listener study involving some 100 participants to determine how often music generated by the models is preferred over human-composed music. The listener study’s result indicates that music generated by the models trained on the dataset is sometimes competitive with music composed by humans. We conclude that neural networks for music generation can be trained using tracker music using our proposed conversion method, but that it is cumbersone. Due to how the tracker music format is constructed it is significantly more difficult to get musical information out of it than we initially thought.Vi undersöker hur man bäst använder sig av trackermusik för att träna neurala nätverk till att generera polyfonisk musik. Trackermusik kan sägas både vara en speciell instrumental musikgenre och ett speciellt musikformat. Formatet som skiljer sig markant från exempelvis MIDI och MP3 har en del egenskaper som gör det svårare och andra som gör det lättare att träna neurala nätverk med det än med jämförbara musikformat. Därför är det intressant att utforska vilka metoder som är bäst att använda för att utvinna musikinformation ur formatet. Så vitt vi vet har ämnet inte utforskats tidigare och vårt utforskande av det är vår uppsats centrala bidrag till forskningen kring musikgenerering med neurala nätverk. I uppsatsen föreslår vi en metod som konverterar trackermusik till ett sekventiellt format som är lämpligt att använda för att träna neurala nätverk. Vi demonstrerar också att metoden fungerar i praktiken genom att träna ett antal neurala nätverk med en samling på cirka 20 000 instrumentala sånger i trackermusiklagringsformatet MOD som vi sedan utvärderar. Utvärderingen består bland annat i en lyssnarstudie. Resultatet av den visar att den musik som genereras av tre neurala nätverk som vi tränar med trackermusiksamlingen ibland föredras av lyssnare över musik skapad av människor. Vi drar slutsatsen att musikgenererande neurala nätverk kan tränas med hjälp av trackermusik med vår föreslagna konverteringsmetod, men att det är bökigt. På grund av hur trackermusik är uppbyggt och organiserat är det betydligt svårare än vad vi inledningsvis trodde att utvinna musikinformation ur det.
16
Anastasia, Marion. "Assessment for Learning:." ScholarWorks @ UVM, 2011. http://scholarworks.uvm.edu/graddis/8.
Анотація:
Although formative assessment is fundamental to educational theory and practices, it is a widely misunderstood term for most educators. This qualitative study defines formative assessment as short-cycle assessments in which teachers adapt their instruction to meet the learners‟ immediate needs. This study focused on the transformation of teachers‟ practices and their perspectives of the critical pedagogical principles necessary to enact The Keeping Learning on Track Program® (KLT™) in their classrooms and in teacher learning communities. The participants in this study included 21 formally trained KLT teachers at the St. Johnsbury School. Over a one year period, I observed in classrooms, attended all KLT teacher learning community (TLC) sessions, collected field notes, attended KLT trainings and presentations, and conducted individual and focus group interviews. The primary area of transformation included: the regulation of learning, beliefs and attitudes, accountability, shared leadership, systemic supports, motivation, classroom culture, and teacher practices.
17
Blot, Guillaume. "Élaboration, parcours et automatisation de traces et savoirs numériques." Thesis, Paris 4, 2017. http://www.theses.fr/2017PA040089.
Анотація:
Comment l'accès au savoir peut-il être impacté par la technologie ? Il suffit d'observer le virage intenté par les outils de communication au début des années 2000 pour se rendre compte : convergence des médias, pratiques participatives et numérisation massive des données. Dans ce contexte, on imagine que l'accès au savoir tend à se démocratiser. En effet, les individus semblent se réapproprier les espaces de vie, en inversant le modèle de transmission top-down, qui va du producteur vers le consommateur, au profit de processus de transfert basés sur l'intelligence collective. Pourtant, on aurait tort de réduire cette réorganisation à un simple renversement du modèle. Car l'intelligence collective est encline à divers biais cognitifs et socio-cognitifs, amenant parfois vers des situations irrationnelles. Autrefois, on s’accommodait de ces mécaniques sociales aux conséquences limitées, aujourd'hui les savoirs numérisés constituent des ensembles massivement communiquant, donnant naissance à de nouvelles voies d'accès et à de nouveaux clivages. Pourquoi ce savoir qui n'a jamais été aussi massif et ouvert, se révèle-t-il si sélectif ? Je propose d'explorer ce paradoxe. L'enregistrement massif et constant de nos traces numériques et l'hyper-connexion des individus, participent à la construction de structures organisationnelles, où se retrouvent numérisées de manière complexe, une partie des dynamiques sociales. En formalisant de la sorte les voies navigables, ces structures organisationnelles façonnent nos trajectoires. Sur cette base, les informaticiens ont mis au point des algorithmes de parcours individualisés, ayant pour objectifs de prédire et de recommander. Ainsi, on propose d'automatiser l'accès au savoir. Se pose alors la question de la gouvernance des individus, dans un contexte où l'intelligence collective est soumise à l'infrastructure : enregistrement des traces, composition des structures organisationnelles et algorithmes de parcoursHow access to knowledge can be impacted by Information Technology? In the earlier 2000s, communication tools caused a significant turn : media convergence, participative practices and massive data. In this way, free access to knowledge might tend to be democratized. People seem to regain spaces, reversing traditional top-down model, going from producer to consumer, for the benefit of an horizontal model based on collective intelligence. However, it should not automatically be assumed that this leads to a simple model reversing. Collective intelligence is subject to cognitive biases, leading to potential irrational situations. Formerly, those social mechanisms had limited consequences. Nowadays, digital knowledge are massive communicating spaces, giving birth to new access paths and new cleavages. Why this massive and open knowledge, is actually so selective? I propose to explore this paradox. Massive and constant tracking of traces and individuals hyper-connection, these two facts help organizational structures design, where social dynamics are digitalized in a complex way. These structures formalize human trajectories. On this basis, computer scientists set up prediction algorithms and recommender engines. This way, knowledge access is automatized. It can then be asked about people governance, in this context of infrastructure submission: recording traces, designing knowledge structure and automating algorithms
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Chachoua, Soraya. "Contribution à l'évaluation de l'apprenant et l'adaptation pédagogique dans les plateformes d'apprentissage : une approche fondée sur les traces." Thesis, La Rochelle, 2019. http://www.theses.fr/2019LAROS003/document.
Анотація:
L’adoption des Nouvelles Technologies de l’Information et de la Communication (NTIC) a permis la modernisation des méthodes d’enseignement dans les systèmes d’apprentissage en ligne comme l’e-Learning, les systèmes tutoriels intelligents, etc. Ces derniers assurent une formation à distance qui répond aux besoins des apprenants. Un aspect très important à prendre en considération dans ces systèmes est l’évaluation précoce de l’apprenant en termes d’acquisition des connaissances. En général, trois types d’évaluation et leurs relations sont nécessaires durant le processus d’apprentissage, à savoir : (i) diagnostic qui est exécuté avant l’apprentissage pour estimer le niveau des élèves, (ii) évaluation formative qui est appliquée lors de l’apprentissage pour tester l’évolution des connaissances et (iii) évaluation sommative qui est considérée après l’apprentissage pour évaluer l’acquisition des connaissances. Ces méthodes peuvent être intégrées d’une manière semi-automatique, automatique ou adaptée aux différents contextes de formation, par exemple dans le domaine d’apprentissage des langues (français, anglais, etc.), des sciences fondamentales (mathématiques, physique, chimie, etc.) et langages de programmation (java, python, sql, etc.) Cependant, les méthodes d’évaluation usuelles sont statiques et se basent sur des fonctions linéaires qui ne prennent en considération que la réponse de l’apprenant. Elles ignorent, en effet, d’autres paramètres de son modèle de connaissances qui peuvent divulguer d’autres indicateurs de performance. Par exemple, le temps de résolution d’un problème, le nombre de tentatives, la qualité de la réponse, etc. Ces éléments servent à détecter les traits du profil, le comportement ainsi que les troubles d’apprentissage de l’apprenant. Ces paramètres additionnels sont vus dans nos travaux de recherche comme des traces d’apprentissage produites par l’apprenant durant une situation ou un contexte pédagogique donné. Dans ce cadre, nous proposons dans cette thèse une approche d’évaluation de l’apprenant à base des traces d’apprentissage qui peut être exploitée dans un système d’adaptation de la ressource et/ou de la situation pédagogique. Pour l’évaluation de l’apprenant, nous avons proposé trois modèles génériques d’évaluation qui prennent en considération la trace temporelle, le nombre de tentatives et leurs combinaisons. Ces modèles ont servi, par la suite, comme métrique de base à notre modèle d’adaptation de la ressource et/ou de la situation d’apprentissage. Le modèle d’adaptation est également fondé sur les trois traces susmentionnées et sur nos modèles d’évaluation. Notre modèle d’adaptation génère automatiquement des trajectoires d’apprentissage adaptées en utilisant un modèle d’état-transition. Les états présentent des situations d’apprentissage qui consomment des ressources et les transitions entre situations expriment les conditions nécessaires à remplir pour passer d’une situation à une autre. Ces concepts sont aussi implémentés dans une ontologie du domaine et un algorithme d’adaptation a été également proposé. L’algorithme assure deux types d’adaptation : (i) Adaptation de la situation et (ii) Adaptation des ressources dans une situation. Afin de collecter les traces d’apprentissage pour la mise en œuvre de notre approche d’évaluation de l’apprenant et d’adaptation de ressources et de situations d’apprentissage, nous avons effectué des expérimentations sur deux groupes d’étudiants en Licence Informatique (L2). Un groupe en apprentissage classique et un groupe en apprentissage adapté. Sur la base des traces obtenues des sessions de travail des étudiants, nous avons utilisé nos modèles d’évaluation dont les résultats ont été utilisés pour mettre en œuvre l’adaptation. Après comparaison des résultats de l’apprentissage adapté à ceux obtenus de l’apprentissage classique, nous avons constaté une amélioration des résultats en termes de moyenne générale et d’écart-type des moyennes des apprenantsThe adoption of new Information and Communication Technologies (ICT) has enabled the modernization of teaching methods in online learning systems such as e-Learning, intelligent tutorial systems (ITS), etc. These systems provide a remote training that which meets the learner needs. A very important aspect to consider in these systems is the early assessment of the learner in terms of knowledge acquisition. In general, three types of assessment and their relationships are needed during the learning process, namely : (i) diagnostic which is performed before learning to estimate the level of students, (ii) formative evaluation which is applied during learning to test the knowledge evolution and (iii) summative evaluation which is considered after learning to evaluate learner’s knowledge acquisition. These methods can be integrated into a semi-automatic, automatic or adapted way in different contexts of formation, for example in the field of languages literary learning such as French, English, etc., hard sciences (mathematics, physics, chemistry, etc.) and programming languages (java, python, sql, etc.). However, the usual evaluation methods are static and are based on linear functions that only take into account the learner’s response. They ignore other parameters of their knowledge model that may disclose other performance indicators. For example, the time to solve a problem, the number of attempts, the quality of the response, etc. These elements are used to detect the profile characteristics, behavior and learning disabilitiesof the learner. These additional parameters are seen in our research as learning traces produced by the learner during a given situation or pedagogical context. In this context, we propose in this thesis a learner evaluation approach based on learning traces that can be exploited in an adaptation system of the resource and/or the pedagogic situation. For the learner assessment, we have proposed three generic evaluation models that take into consideration the temporal trace, number of attempts and their combinations. These models are later used as a base metric for our resource adaptation model and/or learning situation. The adaptation model is also based on the three traces mentioned above and on our evaluation models. Our adaptation model automatically generates adapted paths using a state-transition model. The states represent learning situations that consume resources and the transitions between situations express the necessary conditions to pass from one situation to another. These concepts are implemented in a domain ontology and an algorithm that we have developed. The algorithm ensures two types of adaptation : (i) Adaptation of the situation and (ii) Adaptation of resources within a situation. In order to collect traces of training for the implementation of our approaches of learner evaluation and adaptation of resources and learning situations, we conducted experiments on two groups of students in Computer Science (L2). One group in classical training and the other group in adapted training. Based on the obtained traces from the students’ training sessions, we assessed merners based on our evaluation models. The results are then used to implement the adaptation in a domain ontology. The latter is implemented within oracle 11g which allows a rule-based semantic reasoning. After comparing the results of the adapted training with those obtained from the classical one, we found an improvement in the results in terms of general average and standard deviation of the learner averages
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Asber, Johnny. "A Machine Learning-Based Approach for Fault Detection of Railway Track and its Components." Thesis, Luleå tekniska universitet, Drift, underhåll och akustik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-81275.
Анотація:
The hard equation of railway safety versus the high commercial profits can only be achieved through the use of new inspection methods supported by modern technologies. The track and its components can have different types of troubles, such as rail surface defects, broken sleepers, missing fasteners, and irregular ballast levels. Each component of the track infrastructure plays a significant role, where the failure or the absence of any of them can pave the way to undesired situations. The rail is designed to carry and direct the train, the sleepers are meant to maintain the level of the rail, and the ballast mission is to keep all components floating on the surface of the ground. The fasteners are used to fasten the rail to the sleepers, and therefore too many missing fasteners can lead to sever unsteady tracks, which can, in turn, result in derailment. Therefore, there is a high demand for advanced inspection methods to monitor the railway track and its components continuously. The presence of such advanced inspection models would help the railway industry avoid obstacles such as high operation and maintenance costs, dangerous accidents, and uncomfortable passenger's experience. This master thesis aims to present an efficient method to classify the track and its components by combining image processing techniques and deep learning algorithms. This method was able to detect the missing fasteners in the set of images captured by a line camera, continuously monitoring the rail and its associated fasteners. The experimental results obtained in this thesis showed that the proposed method is efficient and robust for detecting the track and its components in complex environments. The thesis also discusses the idea of building one complete model that can process and classify all track components at once. The image processing technique was employed to extract different components of the track, individually: fasteners, rail, ballast, and sleepers. The model was trained and used to classify the state of the fasteners. Classification of other components of the track will be a part of the future work.
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Brimson, Philip. "The use of a metacognitive tool to track learning in science by adults." Thesis, University of Surrey, 2009. http://epubs.surrey.ac.uk/844620/.
Анотація:
The territory covered by this work includes the response to new information in science by adults. A central aim is to shed some light on the problem of how new and more complex knowledge (specifically conceptual knowledge) develops or arises from old and less complex knowledge. This problem has challenged both philosophers and educators for over twenty centuries. The study draws on perspectives from several academic disciplines, in particular from philosophy, science, and sociology, and to a lesser extent from psychology. These disciplines are used in the first part of the thesis to set the context, both for the problem and for the qualitative research approach which tackles it, as well as to review literature that pertains to the field. Among hindrances to learning that are considered, particular attention is given to difficulties encountered with science texts; trials of some experimental approaches to the problems are included. The central research question concerns how adults learning science respond to new information, especially information that conflicts with their existing knowledge. The problem is approached within a constructivist framework using the metacognitive tool of the concept map as a means of tracking the type of learning (deep or surface) that is taking place. Data relating to the type of learning are also produced through questionnaires and interviews from volunteer participants who are pursuing further and higher education courses that include mandatory science components. The results of the study indicate considerable reluctance to abandon what has been learned previously, in favour of new information. Contrary to expectation was the discovery that adults respond to new information with surface learning strategies, placing extensive reliance (initially at least) on memory, whether or not they declare a preference for meaningful learning. There are implications of this discovery for those who plan and deliver short 'refresher' training courses.
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Ji, Min. "Exploiting activity traces and learners’ reports to support self-regulation in project-based learning." Thesis, Lyon, INSA, 2015. http://www.theses.fr/2015ISAL0032/document.
Анотація:
L'Apprentissage Par Projet (APP) est une méthode d'enseignement orientée apprenant, qui leur permet de réaliser des projets sous forme d'enquêtes approfondies. L'APP offre aux apprenants la possibilité de planifier leur projet, de collaborer avec leurs pairs et de rechercher les ressources pour atteindre les objectifs du projet. Cependant, l'APP est difficile à mettre en œuvre avec succès du fait que les apprenants manquent souvent des compétences d'autorégulation pour suivre, réfléchir, gérer et évaluer les activités durant le projet. L'apprentissage autorégulé peut aider les apprenants à acquérir ces compétences. Cependant, la plupart des environnements d'apprentissage utilisés en APP proposent surtout des matériaux d'apprentissage riches aux apprenants, et rarement les moyens de suivre et analyser leurs processus de gestion de projet et d'apprentissage. L'objectif principal de cette thèse est de soutenir l'apprentissage autorégulé en apprentisage par projet. Nous proposons une architecture générale de système de gestion des apprentissage par projet (PBLMS) qui aide les apprenants à comprendre comment réguler leurs activités d'apprentissage au cours d'un projet. Cette architecture générale intègre un système existant de gestion des apprentissages (LMS) et deux outils que nous proposons: un outil de reporting et un tableau de bord dynamique. L'outil de reporting supporte les processus de réflexion des apprenants en les amenant à décrire leurs activités non instrumentées, leurs réflexions et leurs évaluations sur les activités menées durant le projet à l'aide de phrases semi-structurées. Le système enregistre automatiquement les traces des interactions des utilisateurs avec le LMS, l'outil de reporting et le tableau de bord. Ces traces d'activité sont fusionnées avec les données autodéclarées afin que les indicateurs puissent être calculés sur la base de ces deux types d'informations. Le tableau de bord dynamique permet aux apprenants de créer des indicateurs personnalisables. Les apprenants peuvent spécifier les données à prendre en compte, le calcul et les modes de visualisation. Nous avons implémenté cette proposition théorique avec le développement de la plate-forme DDART (tableau de bord dynamique basé sur les traces d'activité et déclarées) qui intègre l'outil de reporting et le tableau de bord dynamique. Pour évaluer notre proposition, nous avons tout d'abord testé la capacité de DDART à créer un large échantillon d'indicateurs qui sont proposés dans les recherches existantes sur l'analyse des activités, la cognition, les émotions et les réseaux sociaux. De plus, une expérience a été menée afin d'évaluer l'utilisabilité et l'utilité perçue de DDART. Selon les résultats de cette expérience, nous avons constaté que DDART supporte les réflexions des apprenants sur la façon dont ils mènent leur projet et leur fournit les moyens de suivre leurs activités et apprentissages, même si la création d'indicateurs apparait difficile pour les novicesProject-based Learning (PBL) is a learner-oriented instructional method, which enables learners to carry out challenging and authentic projects by thorough investigations. PBL affords learners the opportunities to organize and plan the project, to collaborate with peers and to look for the resources and guidance to achieve the project goals. However, PBL is difficult to implement successfully because learners often lack of the self-regulation skills required to monitor, reflect, manage and assess their project activities and learning. Self-Regulated Learning (SRL) can train learners to gain these skills. However, most learning systems used in PBL focus on providing rich learning materials to the learners but rarely offer possibilities to monitor and analyze their project and learning processes. The main goal of this thesis is to support SRL during PBL situations. We propose a general architecture of Project-based Learning Management System (PBLMS), which help learners to understand how to regulate their learning activities during the projects. This general architecture integrates an existing Learning Management System (LMS) and two tools we propose: a reporting tool and a dynamic dashboard. The reporting tool enhances learners' reflective processes by leading them to describe their non-instrumented activities, their reflections and assessments on the project activities based on semi-structured sentences. The system can record automatically the activity traces of the users' interactions with the LMS, the reporting tool and the dashboard. These activity traces are merged with the self-reporting data so that indicators can be calculated basing on this entire information. The dynamic dashboard supports learners in creating customizable indicators. Learners can specify the data to take into account, the calculation and the visualization modes. We implemented this theoretical proposition with the development of the DDART (Dynamic Dashboard based on Activity and self-Reporting Traces) platform that integrates the reporting tool and the dynamic dashboard. To evaluate the proposition, we firstly test the ability of DDART to recreate a large sample of indicators that are proposed in existing researches about the analysis of activities, cognition, emotion and social network. Furthermore, an experiment was conducted to evaluate the usability and perceived utility of DDART. According to the results of this experiment, we found that DDART supports learners' reflections on the way they carry out the project and provides them with the opportunities to monitor their activities and learning, even if the indicator creation could be difficult for the novices
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Maia, Helena de Almeida. "A mediator for multiple trackers in long-term scenario." Universidade Federal de Juiz de Fora (UFJF), 2016. https://repositorio.ufjf.br/jspui/handle/ufjf/4841.
Анотація:
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Nos últimos anos, o rastreador TLD (Tracking-Learning-Detection) se destacou por combinar um método de rastreamento através do movimento aparente e um método de detecção para o problema de rastreamento de objetos em vídeos. O detector identifica o objeto pelas aparências supostamente confirmadas. O rastreador insere novas aparências no modelo do detector estimando o movimento aparente. A integração das duas respostas é realizada através da mesma métrica de similaridade utilizada pelo detector que pode levar a uma decisão enviesada. Neste trabalho, é proposto um framework para métodos baseados em múltiplos rastreadores onde o componente responsável pela integração das respostas é independente dos rastreadores. Este componente é denominado mediador. Seguindo este framework, um novo método é proposto para integrar o rastreador por movimento e o detector do rastreador TLD pela combinação das suas estimativas. Os resultados mostram que, quando a integração é independente das métricas de ambos os rastreadores, a performance é melhorada para objetos com significativas variações de aparência durante o vídeo.
On the problem of tracking objects in videos, a recent and distinguished approach combining tracking and detection methods is the TLD (Tracking-Learning-Detection) framework. The detector identifies the object by its supposedly confirmed appearances. The tracker inserts new appearances into the model using apparent motion. Their outcomes are integrated by using the same similarity metric of the detector which, in our point of view, leads to biased results. In our work, we propose a framework for generic multitracker methods where the component responsible for the integration is independent from the trackers. We call this component as mediator. Using this framework, we propose a new method for integrating the motion tracker and detector from TLD by combining their estimations. Our results show that when the integration is independent of both tracker/detector metrics, the overall tracking is improved for objects with high appearance variations throughout the video.
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Dalton-Brits, E., and M. Viljoen. "Personality traits and learning approaches : are they influencing the learning process?" Journal for New Generation Sciences, Vol 8, Issue 3: Central University of Technology, Free State, Bloemfontein, 2010. http://hdl.handle.net/11462/565.
Анотація:
Published ArticleThe relationship between the big five personality traits, Extraversion, Agreeableness Neuroticism, Conscientiousness and Openness to Experience and deep and surface approaches to learning forms the basis of this article. The findings of a research study in this milieu will be presented to prove that earlier studies in this field have been upheld, but that an important deviation has occurred on certain levels of personality. A students way of learning implies the type of learning that is taking place. Ultimately we as lecturers want to encourage deep learning as this stimulates retention of information, important in production of students that are ready for employment.
24
Settouti, Lotfi. "Systèmes à base de traces modélisées : modèles et langages pour l'exploitation des traces d'interactions." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10019.
Анотація:
Ce travail de thèse s'inscrit dans le cadre du projet < personnalisation des environnements informatiques pour l'apprentissage humain (EIAH) > financé par la Région Rhône-Alpes. La personnalisation des EIAH est essentiellement dépendante de la capacité à produire des traces pertinentes et exploitables des activités des apprenants interagissant avec un EIAH. Dans ce domaine, l'exploitation des traces relève explicitement plusieurs problématiques allant de sa représentation de manière normalisée et intelligible à son traitement et interprétation en temps différé ou en temps réel au moment même de l'apprentissage. La multiplication des pratiques et des usages des traces requiert des outils génériques pour soutenir leurs exploitations. L'objectif de cette thèse est de définir les fondements théoriques de tels outils génériques permettant l'exploitation des traces d'interaction. Ceci nous a amené à définir la notion de Systèmes à Base de Trace modélisées : une classe de systèmes à base de connaissances facilitant le raisonnement et l'exploitation des traces modélisées. L'approche théorique proposée pour construire de tels systèmes s'articule autour de deux contributions : (1) La définition d'un cadre conceptuel définissant les concepts, l'architecture et les services mobilisés par les SBT. (2) La définition d'un cadre formel pour les systèmes à base de traces modélisées. Plus précisément, la proposition d'un langage pour l'interrogation et la transformation de trace modélisées à base de règles permettant des évaluations ponctuelles et continues. La sémantique formelle de ce langage est définie sous forme d'une théorie des modèles et d'une théorie de point fixe, deux formalismes habituellement utilisés pour décrire la sémantique formelle des langages de représentation de connaissancesThis thesis is funded by the Rhône-Alpes Region as a part of the project < Personalisation of Technology-Enhanced Learning (TEL) Systems >. Personalising TEL Systems is, above all, dependent on the capacity to produce relevant and exploitable traces of individual or collaborative learning activities. In this field, exploiting interaction traces addresses several problems ranging from its representation in a normalised and intelligible manner to its processing and interpretation in continuous way during the ongoing TEL activities. The proliferation of trace-based exploitations raises the need of generic tools to support their representation and exploitation. The main objective of this thesis is to define the theoretical foundations of such generic tools. To do that, we define the notion of Trace-Based System (TBS) as a kind of Knowledge-based system whose main source of knowledge is a set of trace of user-system interactions. This thesis investigates practical and theoretical issues related to TBS, covering the spectrum from concepts, services and architecture involved by such TBS (conceptual framework) to language design over declarative semantics (formal framework). The central topic of our framework is the development of a high-level trace transformation language supporting deductive rules as an abstraction and reasoning mechanism for traces. The declarative semantics for such language is defined by a (Tarski-style) model theory with accompanying fixpoint theory
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Abgrall, Corentin. "Deep learning models as advisors to execute trades on financial markets." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235782.
Анотація:
Recent work has shown that convolutional networks can successfully handle time series as input in various different problems. This thesis embraces this observation and introduces a new method combining machine learning techniques in order to create profitable trading strategies. The method addresses a binary classification problem: given a specific time, access to prices before this moment and an exit policy, the goal is to forecast the next price movement. The classification method is based on convolutional networks combining two major improvements: a special form of bagging and a weight propagation, to enhance the accuracy and reduce the overall variance of the model. The rolling learning and the convolutional layers are able to exploit the time dependency to strongly improve the trading strategy. The presented architecture is able to surpass the expert traders.Nyligen utförda arbeten har visat att faltningsnätverk framgångsrikt kan hantera tidsserier som indata i olika problem. Observationen utnyttjas i detta examensarbete som introducerar en ny metod som kombinerar tekniker för maskininlärning för att skapa lönsamma handelsstrategier. Metoden löser ett binärt klassificeringsproblem: beroende på en viss tidpunkt, tillgång till priser före denna tidpunkt och ett säljkriterium så är målet att förutsäga nästa prisvariation. Klassificeringsmetoden baseras på faltningsnätverk som kombinerar två stora förbättringar: en speciell form av bagging och en viktpropagering för att förbättra noggrannheten och reducera modellens varians. Det rullande lärandet och faltningsnätverken kan utnyttja tidsberoendet för att förbättra handelsstrategin. Den presenterade arkitekturen klarar av att prestera bättre än experthandlare.
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Bard-Schwarz, Anna Ewa. "A Philosophy and an Approach to Teaching Non-professional-track Violin Students." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc500007/.
Анотація:
The aim of this dissertation is to lay the groundwork for an integrated approach to violin instruction for children who are not being groomed explicitly for professional careers as instrumentalists. The study presents a particular focus on the age of middle school children, in order to showcase a more specialized and definitive result of research without, however, distinguishing between advantages and limitations of different age groups of children who study music and learn to play the violin. My first goal is to craft a sample method of teaching with a premise that not all students studying music must or need to become professional musicians in their future. I promote an approach based on the premise that music has universal value available to all and that any kind of music education encourages the growth, personality development, and imagination of children. My second goal is to explore how music education functions in 21st century western culture. Research is based on teachings and methods established by Suzuki, Kodaly, Jaques-Dalcroze, and Orff, among others.
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Carrillo, Rozo Rubiela. "Suivi de l’engagement des apprenants lors de la construction de cartes mentales à partir de traces d’interaction." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1030/document.
Анотація:
A la différence de l'apprentissage par mémorisation (rote learning), l'apprentissage significatif (meaningful learning) vise à associer de nouvelles connaissances à des connaissances déjà acquises. La construction de cartes mentales exige et supporte la mise en place de stratégies d'apprentissage significatif, et permet de rendre visible la structure de connaissances de l'apprenant. Cependant, les enseignants qui intègrent la construction de cartes mentales dans leurs activités pédagogiques doivent se contenter du rendu final des cartes mentales, et risquent de faire de mauvaises interprétations et évaluations de celles-ci par manque d'information sur leur processus de construction. Dans cette thèse, nous nous intéressons à l'observation a posteriori de l'engagement de l'apprenant dans ses dimensions comportementale et cognitive, afin de proposer des indicateurs orientés processus qui permettent de comprendre ses actions et ses choix de construction de carte mentale. Nous avons suivi la méthodologie de recherche orientée par la conception (Design Based Research), qui nous a permis de proposer 3 niveaux de contributions : 1) un modèle théorique d'engagement (comportemental et cognitive) pour les activités de construction de cartes mentales, 2) un ensemble d'indicateurs d'engagement de l'apprenant à partir de traces capturées automatiquement lors de la construction de cartes mentales, et 3) un tableau de bord appelé MindMap Monitor présentant différents indicateurs à l'enseignant pour le suivi de la classe et des apprenants. Le modèle a été obtenu à partir d'une étude de littérature sur les théories de l'engagement de l'apprenant issues notamment de la recherche en psychologie de l'éducation. Les indicateurs ont été définis en croisant le modèle avec les résultats de plusieurs études de terrain avec les enseignants. Le tableau de bord implémentant les indicateurs a été construit en trois itérations. Son interface présente des vues synthétiques permettant de comparer les élèves de la classe et d'identifier ceux en difficulté lors de la construction de leur carte, et des vues détaillées décrivant l'activité de construction d'une carte pour chaque élève. Notre tableau de bord a été évalué au cours d'une expérimentation avec 12 enseignants en comparant son utilisation avec celle des cartes mentales finales associées aux vidéos de leur processus de construction. Les résultats montrent que nos indicateurs sur MindMap Monitor permettent de mieux identifier les élèves en difficulté, les difficultés partagées, ainsi que les difficultés pour un élève. Les résultats concernant la compréhension du processus de construction de la carte mentale sont plus nuancés. Nous avons également pu identifier plusieurs pistes d'amélioration sur le contenu du tableau de bord et sa présentation. Les perspectives de notre travail concernent principalement le suivi de l'engagement des apprenants en temps réel pour l'intervention et l'adaptation de la stratégie pédagogiqueIn contrast to rote learning, meaningful learning aims to associate new knowledge with knowledge already acquired. Mind mapping activities require and support the implementation of meaningful learning strategies and enlighten the knowledge structure of the learner. However, teachers who integrate mind mapping into their educational activities have to deal with the final rendering of maps, and risk to misinterpret and wrongly evaluate them due to the lack of information about their construction process. In this thesis, we are interested in a posteriori observation of the engagement of learners along its behavioral and cognitive dimensions, in order to propose processoriented indicators that help to understand actions and construction choices of mind maps. We followed the Design Based Research methodology, that allowed us to propose three levels of contributions : 1) a theoretical model of engagement (behavioral and cognitive) for mind mapping activities, 2) a set of indicators of learner engagement constructed from automatically captured map building traces, and 3) a dashboard called MindMap Monitor presenting various indicators to teachers for class and learners monitoring. The model was obtained from a literature review on theories of engagement, including research in educational psychology. The indicators have been defined by comparing the model with the results of several field studies with teachers. The dashboard implementing the indicators was developed following three iterations. Its interface presents synthetic views allowing the comparison of students in the class, the identification of those in difficulty, and detailed views describing the mind mapping activity for each student. Our dashboard was evaluated with an experiment involving 12 teachers. We compared its use with that of final mind maps associated with videos of their construction process. Results show that our indicators on MindMap Monitor are useful to better identify students in difficulty, shared difficulties, as well as difficulties for individual students. Results concerning the understanding of the mind maps construction process are more balanced. We were also able to identify several ways to improve both the content and the visualizations of the dashboard. The perspectives of our work are mainly related to monitoring learners’ engagement in real time for the intervention and adaptation of the teachers’ educational strategies
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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.
Анотація:
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 contextTiivistelmä 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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LaCroix, Lionel N. "Learning mathematics for the workplace : an activity theory study of pipe trades training." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27022.
Анотація:
This study examines a single pipe trades pre-apprentice within a one-on-one impromptu tutoring session making sense of fractions-of-an-inch on a measuring tape within the context of a pre-apprenticeship program for the pipe trades. The multi-semiotic analysis of this event is framed using cultural-historical activity theory and Radford’s theory of knowledge objectification. From these complementary perspectives, mathematics is considered a culturally situated purposeful activity. Specifically, mathematics learning involves a cultural-historical, socially, and semiotically mediated process of objectification, (i.e., a process in which one becomes progressively aware and conversant, through one’s actions and interpretations, of a cultural logic of mathematical objects).
The analysis focuses on the pre-apprentice’s and tutor’s joint activity during this encounter, drawing on video data and various artifacts used. This entailed slow-motion and frame-by-frame analysis of the video to assess the role and coordination of various semiotic systems, actions, and artifacts. Particular attention is paid to: the semiotic system of cultural signification, norms of practice, contradictions or conflicts that serve to motivate this activity, specific objectives of or sub-goals in the learning process for this student, semiotic processes used both by the student and tutor in the objectification process, as well as changes to the subjectification of both the pre-apprentice and researcher-as-tutor in this process.
This analysis informs Radford’s theory of knowledge objectification by showing, through fine-grained analysis, relevant aspects of its dynamics and by calling attention to a new form of iconicity and a process of semiotic extraction, both original contributions to research. It also shows various ways in which a learner’s subjectification is evident in the process of learning mathematics. The results have a number of practical implications for the teaching of mathematics generally, and mathematics for the workplace in particular, by drawing attention to the social, cultural, historical, and mediated dimensions and dynamics of mathematics learning activity. The findings also illustrate the complexity of learning to measure by identifying a number of processes and conflicts involved and practical ways these are negotiated or resolved.
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Lebis, Alexis. "Capitaliser les processus d'analyse de traces d'apprentissage : modélisation ontologique & assistance à la réutilisation." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS523.
Анотація:
Cette thèse en informatique porte sur la problématique de la capitalisation des processus d’analyse de traces d’apprentissage au sein de la communauté des Learning Analytics (LA). Il s’agit de permettre de partager, adapter et réutiliser ces processus d’analyse de traces. Actuellement, cette capitalisation est limitée par deux facteurs importants : les processus d’analyse sont dépendants des outils d’analyse qui les mettent en œuvre - leur contexte technique - et du contexte pédagogique pour lequel ils sont menés. Cela empêche de les partager, mais aussi de les ré-exploiter simplement en dehors de leurs contextes initiaux, quand bien même les nouveaux contextes seraient similaires. L’objectif de cette thèse est de fournir des modélisations et des méthodes permettant la capitalisation des processus d’analyse de traces d’apprentissage, ainsi que d’assister les différents acteurs de l’analyse, notamment durant la phase de réutilisation. Pour cela, nous répondons aux trois verrous scientifiques suivant : comment partager et combiner des processus d’analyse mis en œuvre dans différents outils d’analyse ? ; comment permettre de ré-exploiter un processus d’analyse existant pour répondre à un autre besoin d’analyse ? ; comment assister les différents acteurs lors de l’élaboration et de l’exploitation de processus d’analyse ? Notre première contribution, issue d’une synthèse de l’état de l’art, est la formalisation d’un cycle d'élaboration et d'exploitation des processus d'analyse, afin d'en définir les différentes étapes, les différents acteurs et leurs différents rôles. Cette formalisation est accompagnée d’une définition de la capitalisation et de ses propriétés. Notre deuxième contribution répond au premier verrou lié à la dépendance technique des processus d’analyse actuels, et à leur partage. Nous proposons un méta-modèle qui permet de décrire les processus d’analyse indépendamment des outils d’analyse. Ce méta-modèle formalise la description des opérations utilisées dans les processus d'analyse, des processus eux-mêmes et des traces utilisées, afin de s’affranchir des contraintes techniques occasionnées par ces outils. Ce formalisme commun aux processus d’analyse permet aussi d’envisager leur partage. Il a été mis en œuvre et évalué dans un de nos prototypes. Notre troisième contribution traite le deuxième verrou sur la ré-exploitation des processus d’analyse. Nous proposons un framework ontologique pour les processus d'analyse, qui permet d'introduire de manière structurée des éléments sémantiques dans la description des processus d'analyse. Cette approche narrative enrichit ainsi le formalisme précédent et permet de satisfaire les propriétés de compréhension, d’adaptation et de réutilisation nécessaires à la capitalisation. Cette approche ontologique a été mise en œuvre et évaluée dans un autre de nos prototypes. Enfin, notre dernière contribution répond au dernier verrou identifié et concerne de nouvelles pistes d’assistances aux acteurs, notamment une nouvelle méthode de recherche des processus d’analyse, s’appuyant sur nos propositions précédentes. Nous exploitons le cadre ontologique de l’approche narrative pour définir des règles d’inférence et des heuristiques permettant de raisonner sur les processus d’analyse dans leur ensemble (e.g. étapes, configurations) lors de la recherche. Nous utilisons également le réseau sémantique sous-jacent à cette modélisation ontologique pour renforcer l’assistance aux acteurs en leur fournissant des outils d’inspection et de compréhension lors de la recherche. Cette assistance a été mise en œuvre dans un de nos prototypes, et évaluée empiriquementThis thesis in computer science focuses on the problem of capitalizing analysis processes of elearning traces within the Learning Analytics (LA) community. The aim is to allow these analysis processes to be shared, adapted and reused. Currently, this capitalization is limited by two important factors: the analysis processes are dependent on the analysis tools that implement them - their technical context - and the pedagogical context for which they are conducted. This prevents them from being shared, but also from being simply reused outside their original contexts, even if the new contexts are similar. The objective of this thesis is to provide models and methods for the capitalisation of analysis processes of elearning traces, as well as to assist the various actors involved in the analysis, particularly during the reuse phase. To do this, we answer the following three scientific questions: how to share and combine analysis processes implemented in different analysis tools; how to reuse an existing analysis process to meet another analysis need; how to assist the different actors in the development and exploitation of analysis processes; and how to support them in the development and exploitation of analysis processes. Our first contribution, resulting from a synthesis of the state of the art, is the formalization of a cycle of elaboration and exploitation of the analysis processes, in order to define the different stages, the different actors and their different roles. This formalization is accompanied by a definition of capitalization and its properties. Our second contribution responds to the first barrier related to the technical dependence of current analysis processes and their sharing. We propose a meta-model that allows to describe the analysis processes independently of the analysis tools. This meta-model formalizes the description of the operations used in the analysis processes, the processes themselves and the traces used, in order to avoid the technical constraints caused by these tools. This formalism, common to the analysis processes, also makes it possible to consider their sharing. It has been implemented and evaluated in one of our prototypes. Our third contribution deals with the second lock on the reuse of analysis processes. We propose an ontological framework for analysis processes, which allows semantic elements to be directly introduced, in a structured way, during the description of analysis processes. This narrative approach thus enriches the previous formalism and makes it possible to satisfy the properties of understanding, adaptation and reuse necessary for capitalisation. This ontological approach was implemented and evaluated in another of our prototypes. Finally, our last contribution responds to the last lock identified and concerns new assistances to actors, in particular a new method of researching analysis processes, based on our previous proposals. We use the ontological framework of the narrative approach to define inference rules and heuristics to reason about the analysis processes as a whole (e.g. steps, configurations) during the research. We also use the semantic network underlying this ontological modeling to strengthen assistance to actors by providing them with inspection and understanding tools during the research. This assistance was implemented in one of our prototypes, and empirically evaluated
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Saada, Hajer. "Exploiting Model Transformation Examples for Easy Model Transformation Handling (Learning and Recovery)." Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20223/document.
Анотація:
L'Ingénierie Dirigée par les Modèles (IDM) est un domaine de recherche en pleine émergence qui considère les modèles comme des éléments de base. Chaque modèle est conforme à un autre modèle, appelé son méta-modèle, qui définit sa syntaxe abstraite et ses concepts. Dans un processus IDM, différents types de modèles sont manipulés par des transformations de modèles. Une transformation génère un modèle dans un langage cible à partir d'un modèle dans un langage source. Pour concevoir une transformation, les développeurs doivent avoir une bonne connaissance des méta-modèles concernés ainsi que des langages de transformation, ce qui rend cette tâche difficile. Dans cette thèse, nous proposons d'assister l'écriture des transformations et plus généralement de comprendre comment une transformation opère. Nous adhérons à l'approche de transformation de modèles par l'exemple qui propose de créer une transformation de modèles à partir d'exemples de transformation. Cela permet d'utiliser la syntaxe concrète définie pour les méta-modèles, et cela évite donc de requérir que les développeurs aient une bonne maîtrise des méta-modèles utilisés. Dans ce contexte, nous proposons deux contributions. La première consiste à définir une méthode pour générer des règles de transformation opérationnelles à partir d'exemples. Nous nous basons sur une approche qui utilise l'Analyse Relationnelle de Concepts (ARC) comme technique d'apprentissage pour obtenir des patrons de transformation à partir d'un appariement de type 1-1 entre les modèles. Nous développons une technique pour extraire des règles de transformation opérationnelles à partir de ces patrons. Ensuite, nous utilisons le langage et le moteur de règles JESS pour exécuter ces règles. Nous étudions aussi comment mieux apprendre des règles de transformations à partir d'exemples, en utilisant séparément chaque exemple ou en réunissant tous les exemples. La deuxième contribution consiste à récupérer les traces de transformation à partir d'exemples de transformation. Ces traces peuvent être utilisées par exemple pour localiser des erreurs durant l'exécution des programmes de transformation ou vérifier la couverture de tous les modèles d'entrée par une transformation. Dans notre contexte, nous supposons que ces traces vont servir pour un futur apprentissage des règles de transformation. Nous traitons tout d'abord le problème de récupération des traces avec des exemples provenant d'un programme de transformation. Nous proposons une approche basée sur une méta-heuristique multi-objectifs pour générer des traces sous forme d'appariement de type n-m entre des éléments de modèles. La fonction objectif s'appuie sur une similarité lexicale et structurelle entre ces éléments. Une extension de cette méthode est proposée pour traiter le problème plus général de l'appariement entre modèlesModel Driven Engineering (MDE) considers models as first class artifacts. Each model conforms to another model, called its metamodel which defines its abstract syntax and its semantics.Various kinds of models are handled successively in an MDE development cycle. They are manipulated using, among others, programs called model transformations. A transformation takes as input a model in a source language and produces a model in a target language. The developers of a transformation must have a strong knowledge about the source and target metamodels which are involved and about the model transformation language. This makes the writing of the model transformation difficult.In this thesis, we address the problem of assisting the writing of a model transformation and more generally of understanding how a transformation operates.We adhere to the Model Transformation By example (MTBE) approach, which proposes to create a model transformation using examples of transformation. MTBE allows us to use the concrete syntaxes defined for the metamodels. Hence, the developers do not need in-depth knowledge about the metamodels. In this context, our thesis proposes two contributions.As a first contribution, we define a method to generate operational transformation rules from transformation examples. We extend a previous approach which uses Relational Concept Analysis as a learning technique for obtaining transformation patterns from 1-1 mapping between models. We develop a technique for extracting relevant transformation rules from these transformation patterns and we use JESS language and engine to make the rules executable. We also study how we better learn transformation rules from examples, using transformation examples separately or by gathering all the examples.The second contribution consists in recovering transformation traces from transformation examples. This trace recovery is useful for several purposes as locating bugs during the execution of transformation programs, or checking the coverage of all input models by a transformation. In our context, we expect also that this trace will provide data for a future model transformation learning technique. We first address the trace recovery problem with examples coming from a transformation program. We propose an approach, based on a multi-objective meta-heuristic, to generate the textit{many-to-many} mapping between model constructs which correspond to a trace. The fitness functions rely on the lexical and structure similarity between the constructs. We also refine the approach to apply it to the more general problem of model matching
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Roy, Chandan. "An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting." Doctoral thesis, Linköpings universitet, Interaktiva och kognitiva system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123198.
Анотація:
Introduction: Tropical Cyclones (TCs) inflict considerable damage to life and property every year. A major problem is that residents often hesitate to follow evacuation orders when the early warning messages are perceived as inaccurate or uninformative. The root problem is that providing accurate early forecasts can be difficult, especially in countries with less economic and technical means. Aim: The aim of the thesis is to investigate how cyclone early warning systems can be technically improved. This means, first, identifying problems associated with the current cyclone early warning systems, and second, investigating if biologically based Artificial Neural Networks (ANNs) are feasible to solve some of the identified problems. Method: First, for evaluating the efficiency of cyclone early warning systems, Bangladesh was selected as study area, where a questionnaire survey and an in-depth interview were administered. Second, a review of currently operational TC track forecasting techniques was conducted to gain a better understanding of various techniques’ prediction performance, data requirements, and computational resource requirements. Third, a technique using biologically based ANNs was developed to produce TC track and intensity forecasts. Systematic testing was used to find optimal values for simulation parameters, such as feature-detector receptive field size, the mixture of unsupervised and supervised learning, and learning rate schedule. Five types of 2D data were used for training. The networks were tested on two types of novel data, to assess their generalization performance. Results: A major problem that is identified in the thesis is that the meteorologists at the Bangladesh Meteorological Department are currently not capable of providing accurate TC forecasts. This is an important contributing factor to residents’ reluctance to evacuate. To address this issue, an ANN-based TC track and intensity forecasting technique was developed that can produce early and accurate forecasts, uses freely available satellite images, and does not require extensive computational resources to run. Bidirectional connections, combined supervised and unsupervised learning, and a deep hierarchical structure assists the parallel extraction of useful features from five types of 2D data. The trained networks were tested on two types of novel data: First, tests were performed with novel data covering the end of the lifecycle of trained cyclones; for these test data, the forecasts produced by the networks were correct in 91-100% of the cases. Second, the networks were tested with data of a novel TC; in this case, the networks performed with between 30% and 45% accuracy (for intensity forecasts). Conclusions: The ANN technique developed in this thesis could, with further extensions and up-scaling, using additional types of input images of a greater number of TCs, improve the efficiency of cyclone early warning systems in countries with less economic and technical means. The thesis work also creates opportunities for further research, where biologically based ANNs can be employed for general-purpose weather forecasting, as well as for forecasting other severe weather phenomena, such as thunderstorms.
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Haapanen, Rollenhagen Svante. "Automatic Music Recommendation for Businesses : Using a two-stage Membership model for track recommendation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303007.
Анотація:
This thesis proposes a two-stage recommendation system for providing music recommendations based on seed playlists as inputs. The goal is to help businesses find relevant and brand-fit music to play in their venues. The problem of recommending music using machine learning has been investigated quite a bit in both academia and the industry, with collaborative filtering and content-based filtering being the major approaches used. One of the difficulties of creating a recommendation system is how to evaluate it. In this thesis, both a quantitative and a qualitative evaluation are made to determine how well the results correspond to the actual quality of recommendations. The application of recommending music to businesses also poses different problems than a service directed at end consumers, mostly related to how many track recommendations are needed. A two-stage approach was used with Stage 1 producing candidates and a Stage 2 model using a neural network comparing five tracks from the playlist with a candidate was used to rank said candidates. The results show that the Stage 2 model has substantially better results in both the qualitative and quantitative evaluation compared to Stage 1. The quality of the recommendations from the whole system is not completely satisfactory, and some possible reasons for this are discussed, including improving the Stage 1 candidate generator (which was not modified in the scope of this thesis).Automatisk musikrekommendation med hjälp av maskininlärning har utforskats av både industrin och akademin genom åren, där två huvudsakliga metoder utkristalliserats: collaborative filtering samt content-based filtering. I det här arbetet har en content-based modell tagits fram, uppdelad i två stadier: Steg 1 som genererar kandidater som Steg 2 sedan ordnade om med hjälp av ett neuralt nätverk som jämförde 5 låtar i taget från en spellista med motsvarande kandidater genererade av Steg 1 En av svårigheterna med att skapa automatiska rekommendationer är utvärderingen av den. I det här arbetet har både en kvantitativ och kvalitativ studie utförts för att försäkra att resultaten motsvarar den faktiska kvaliten hos rekommendationerna. Slutmålet med att hjälpa företag med musikrekommendation ställer också unika problem att lösa i jämförelse med en tjänst för privatpersoner, framförallt relaterat till storleken på de returnerade rekommendationerna. Resultaten visade att Steg 2 lyckades rangordna rekommendationerna från Steg 1 på ett sätt som gav högre poäng i både den kvantitativa och kvalitativa utvärderingen av systemen. De slutgiltiga resultaten var inte helt tillfredsställande, och potentialla orsaker till detta diskuteras. Dessa inkluderar Steg 1 (som inte modifierades inom ramen för detta arbete). Utvärderingen visade dock att de kvantitativa utvärderingsramarna verkar motsvara den upplevda kvaliten hos rekommendationerna baserat på den kvalitativa utvärderingen.
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Toussaint, Ben-Manson. "Apprentissage automatique à partir de traces multi-sources hétérogènes pour la modélisation de connaissances perceptivo-gestuelles." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAM063/document.
Анотація:
Les connaissances perceptivo-gestuelles sont difficiles à saisir dans les Systèmes Tutoriels Intelligents. Ces connaissances sont multimodales : elles combinent des connaissances théoriques, ainsi que des connaissances perceptuelles et gestuelles. Leur enregistrement dans les Systèmes Tutoriels Intelligents implique l'utilisation de plusieurs périphériques ou capteurs couvrant les différentes modalités des interactions qui les sous-tendent. Les « traces » de ces interactions –aussi désignées sous le terme "traces d'activité"- constituent la matière première pour la production de services tutoriels couvrant leurs différentes facettes. Les analyses de l'apprentissage ou les services tutoriels privilégiant une facette de ces connaissances au détriment des autres, sont incomplets. Cependant, en raison de la diversité des périphériques, les traces d'activité enregistrées sont hétérogènes et, de ce fait, difficiles à modéliser et à traiter. Mon projet doctoral adresse la problématique de la production de services tutoriels adaptés à ce type de connaissances. Je m'y intéresse tout particulièrement dans le cadre des domaines dits mal-définis. Le cas d'étude de mes recherches est le Système Tutoriel Intelligent TELEOS, un simulateur dédié à la chirurgie orthopédique percutanée. Les propositions formulées se regroupent sous trois volets : (1) la formalisation des séquences d'interactions perceptivo-gestuelles ; (2) l'implémentation d'outils capables de réifier le modèle conceptuel de leur représentation ; (3) la conception et l'implémentation d'outils algorithmiques favorisant l'analyse de ces séquences d'un point de vue didactiquePerceptual-gestural knowledge is multimodal : they combine theoretical and perceptual and gestural knowledge. It is difficult to capture in Intelligent Tutoring Systems. In fact, its capture in such systems involves the use of multiple devices or sensors covering all the modalities of underlying interactions. The "traces" of these interactions -also referred to as "activity traces"- are the raw material for the production of key tutoring services that consider their multimodal nature. Methods for "learning analytics" and production of "tutoring services" that favor one or another facet over others, are incomplete. However, the use of diverse devices generates heterogeneous activity traces. Those latter are hard to model and treat.My doctoral project addresses the challenge related to the production of tutoring services that are congruent to this type of knowledge. I am specifically interested to this type of knowledge in the context of "ill-defined domains". My research case study is the Intelligent Tutoring System TELEOS, a simulation platform dedicated to percutaneous orthopedic surgery.The contributions of this thesis are threefold : (1) the formalization of perceptual-gestural interactions sequences; (2) the implementation of tools capable of reifying the proposed conceptual model; (3) the conception and implementation of algorithmic tools fostering the analysis of these sequences from a didactic point of view
35
Strollo, William A. ""An Amazing Aptness for Learning Trades:" The Role of Enslaved Craftsmen in Charleston Cabinetmaking Shops." VCU Scholars Compass, 2017. https://scholarscompass.vcu.edu/etd/5193.
Анотація:
This paper examines the role of enslaved craftsmen in Charleston cabinetmaking shops during the late-eighteenth century and how wealthy Charlestonians’ desire fashionable goods fueled the demand for this labor force. The first chapter examines the rise of the wealthy Charlestonians and the origins of their taste for fashionable goods. The second chapter explores the increased use of enslaved craftsmen in Charleston cabinetmaking shops during the last half of the eighteenth century and how they affected the production of fashionable cabinet goods.
36
Björkstrand, David. "LEARNING SCENE SPECIFIC RECONSTRUCTION OF MONTE CARLO PATH TRACED IMAGE SEQUENCES WITHOUT ADDITIONAL CLEAN DATA." Thesis, Umeå universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-164719.
Анотація:
When using deep learning models for reconstruction of one path per pixel Monte Carlo path traced image sequences, reconstruction of unseen features can be a concern. This can be solved by training the model on the same scene it is supposed to reconstruct images from. Learning to specialize with additional clean targets would be extremely time consuming, instead training with additional noisy targets saves time as additional noisy images is tremendously faster to render. This thesis shows that a model trained without clean targets on the same scene it is reconstructing images from can under certain conditions out performa model trained on clean targets from different scenes. It also shows that first training a model on clean targets followed by noisy targets can help with instability issues one can encounter when only training with noisy targets. Lastly, the thesis shows how there is not much of an improvement going from 400 to 1000 training examples or going from noisy targets rendered with one path per pixel to targets rendered with eight paths per pixel.
37
Schmiers, Tina. "Getting Europe back on Track? Learning Experiences during Interrail and how a free Interrail Ticket could foster Global Citizenship." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-324047.
Анотація:
This study investigates learning experiences and outcomes during the train travel phenomenon Interrail. It especially focuses on transformational learning and whether and in what scope these learning outcomes correlate with the concept of global citizenship. It further analyses how the proposal of a free Interrail ticket, that is currently debated within the European Commission, could foster global citizenship in the wider context of Education for Sustainable Development. Although there has been much research on educative benefits of travel, Interrail in general and as an informal learning environment in particular, is an under-researched phenomenon. By providing a deeper understanding about transformative learning processes and outcomes during the specific case of Interrail in the context of sustainable development, this study contributes towards closing this niche. This research was carried out in form of a qualitative case study research. In total, 18 in-depth interviews were conducted with young adults representing 13 different nationalities. The interviews were thoroughly analysed by applying Jack Mezirows´ transformative learning theory and the concept of global citizenship. The results were completed with an additional documentation analysis. The study results reveal that Interrail with its specific characteristics and elements may provide an informal learning environment that can foster and promote both transformative learning and global citizenship to the individual traveller. The identified patterns and commonalities of learning experiences and outcomes were summarized within the main topics of personal development, critical thinking and reflection, cultural sensitivity and pluralism, shaping identity and sense of belonging, broadening view and change of behavior or action. Implementing a free Interrail ticket could thus arguably contribute to greater accessibility and more equal opportunities for youth to discover, experience and learn from travelling through Europe by train. Subsequently, this could help to foster Education for Sustainable Development and global citizenship. Based on the study results it is suggested, that transformative learning during Interrail could be enhanced through providing incentives and formal guidance in critical thinking and engagement in rational discourse in formal education.
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Blassoples, Cindy Faith. "The determinants of fit between the world of work and Tertiary learning:A tracer study of Cape Peninsula University of Technology (CPUT) Marketing Diploma graduates." Thesis, Cape Peninsula University of Technology, 2011. http://hdl.handle.net/20.500.11838/953.
Анотація:
Dissertation (MTech: Business Administration))-- Cape Peninsula University of Technology, 2011A quantitative research study was conducted in order to gain insight and knowledge into the various destinations CPUT Marketing graduates end up after completing their course of study. A cohort of students that graduated between 2001-2010 was used in this research. The motivation for the study stemmed from the researcher’s experience working at CPUT, lecturing and the researcher’s interaction with the students. The ultimate objective of the study was to trace the graduates, identify their employment status and observe if they are employed in the area for which they have studied.The literature study covers areas that relate to how students choose what to study, graduate skills, the workforce and graduate employment and unemployment. These areas were reviewed from different sources and authors that specialize in graduate development.The researcher elected to work with CPUT graduates as the researcher too is an alumnus of CPUT and was familiar with the policies and procedures of the institution.Results of the research confirmed that tracer studies are an essential tool for tracking graduates and the findings of tracer studies are beneficial for future curriculum development. Although tracer studies yield valuable insight into graduate trajectories they undervalued and underutilized. Furthermore, the results confirm that graduates are employed in the sectors for which they studied or associated sectors. Moreover co-operative education should be further explored to yield better results and perhaps secure employment for the student after graduation.The recommendation is that academic staff revisits the curriculum and better incorporate scarce skills such as critical thinking skills and also institute a formal tracking system that can be used to benefit the department.
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Djouad, Tarek. "Ingénierie des indicateurs d'activités à partir de traces modélisées pour un environnement informatique d'apprentissage humain." Phd thesis, Université Claude Bernard - Lyon I, 2011. http://tel.archives-ouvertes.fr/tel-00756070.
Анотація:
L'exploitation des traces d'interaction lors de tâches d'apprentissage permet différents types de retour d'expérience : retour immédiat pour l'apprenant sur sa tâche, retour d'expérience au niveau d'un groupe de pairs, retour d'expérience vers le tuteur en situation d'apprentissage, retour d'expérience vers les concepteurs de formation. Ces retours d'expérience s'expriment le plus souvent sous une forme synthétique : des indicateurs. Ce travaille apporte des solutions originales aux deux facettes indispensables à toute ingénierie des indicateurs : 1) intégration d'un système à base de traces comme nouvelle brique disponible pour la conception d'EIAH (intégration dans un framework de type Moodle) ; 2) Elaboration d'un processus intégré de transformations explicites de traces modélisées préparant à un calcul explicite d'indicateurs. Les connaissances de modélisation des traces, des transformations et de la description de la formule d'indicateur sont capitalisées, facilitant la réutilisation et la constitution de bibliothèques d'indicateurs " prêts à l'emploi ". Pour illustrer l'approche, nous avons développé un jeu de modèles de traces et de transformations adaptées à une situation cible choisie pour sa richesse interactive. Ce jeu de modèles pourra concerner l'apprenant seul, mais aussi le groupe de pairs et éventuellement le groupe classe pour révéler certains phénomènes, tels que la collaboration, non visibles au niveau de l'individu seul. L'outil développé, pour faire la démonstration de l'approche proposée, a été testé en vraie grandeur sur plusieurs terrains universitaires et est disponible en téléchargement pour Moodle.
40
Andersson, Natalia. "Searching For Success. : An overview of factors relating to academic achievement." Thesis, Umeå universitet, Pedagogiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-89528.
Анотація:
The purpose of this three-part study is to acquire greater knowledge of success in school and the factors that affects it, in order to better understand the school-related reality that students face every day. It is made up of a document study of some of the currently leading literature on academic and other types of success and of the Swedish steering documents that regulate the Swedish school system and a questionnaire based survey on what Swedish high school students believe it takes to succeed in school. Largely, the study finds that both inner factors, like personality traits and soft skills, and outer factors like school organization and good teachers, have a massive impact on academic outcome and therefore also adult outcome. The study largely finds that there are much empirical evidence suggesting that certain things affect achievement both positively and negatively. Nothing is left up to chance.
41
Chen, Sheng-Bo. "Examining the Effect of Self-Regulated Learning on Cognitive Engagement in Mastery-Based Online Courses: A Learning Analytics Perspective." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1577788376743384.
42
Galan, Roberto Fernandez. "Odor coding and memory traces in the antennal lobe of honeybee." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2003. http://dx.doi.org/10.18452/14997.
Анотація:
In dieser Arbeit werden zwei wesentliche neue Ergebnisse vorgestellt. Das erste bezieht sich auf die olfaktorische Kodierung und das zweite auf das sensorische Gedaechtnis. Beide Phaenomene werden am Beispiel des Gehirns der Honigbiene untersucht. In Bezug auf die olfaktorische Kodierung zeige ich, dass die neuronale Dynamik waehrend der Stimulation im Antennallobus duftspezifische Trajektorien beschreibt, die in duftspezifischen Attraktoren enden. Das Zeitinterval, in dem diese Attraktoren erreicht werden, betraegt unabhaengig von der Identitaet und der Konzentration des Duftes ungefaehr 800 ms. Darueber hinaus zeige ich, dass Support-Vektor Maschinen, und insbesondere Perzeptronen, ein realistisches und biologisches Model der Wechselwirkung zwischen dem Antennallobus (dem kodierenden Netwerk) und dem Pilzkoerper (dem dekodierenden Netzwerk) darstellen. Dieses Model kann sowohl Reaktionszeiten von ca. 300 ms als auch die Invarianz der Duftwahrnehmung gegenueber der Duftkonzentration erklaeren. In Bezug auf das sensorische Gedaechtnis zeige ich, dass eine einzige Stimulation ohne Belohnung dem Hebbschen Postulat folgend Veraenderungen der paarweisen Korrelationen zwischen Glomeruli induziert. Ich zeige, dass diese Veranderungen der Korrelationen bei 2/3 der Bienen ausreichen, um den letzten Stimulus zu bestimmen. In der zweiten Minute nach der Stimulation ist eine erfolgreiche Bestimmung des Stimulus nur bei 1/3 der Bienen moeglich. Eine Hauptkomponentenanalyse der spontanen Aktivitaet laesst erkennen, dass das dominante Muster des Netzwerks waehrend der spontanen Aktivitaet nach, aber nicht vor der Stimulation das duftinduzierte Aktivitaetsmuster bei 2/3 der Bienen nachbildet. Man kann deshalb die duftinduzierten (Veraenderungen der) Korrelationen als Spuren eines Kurzzeitgedaechtnisses bzw. als Hebbsche "Reverberationen" betrachtet werden.Two major novel results are reported in this work. The first concerns olfactory coding and the second concerns sensory memory. Both phenomena are investigated in the brain of the honeybee as a model system. Considering olfactory coding I demonstrate that the neural dynamics in the antennal lobe describe odor-specific trajectories during stimulation that converge to odor-specific attractors. The time interval to reach these attractors is, regardless of odor identity and concentration, approximately 800 ms. I show that support-vector machines and, in particular perceptrons provide a realistic and biological model of the interaction between the antennal lobe (coding network) and the mushroom body (decoding network). This model can also account for reaction-times of about 300 ms and for concentration invariance of odor perception. Regarding sensory memory I show that a single stimulation without reward induces changes of pairwise correlation between glomeruli in a Hebbian-like manner. I demonstrate that those changes of correlation suffice to retrieve the last stimulus presented in 2/3 of the bees studied. Succesful retrieval decays to 1/3 of the bees within the second minute after stimulation. In addition, a principal-component analysis of the spontaneous activity reveals that the dominant pattern of the network during the spontaneous activity after, but not before stimulation, reproduces the odor-induced activity pattern in 2/3 of the bees studied. One can therefore consider the odor-induced (changes of) correlation as traces of a short-term memory or as Hebbian reverberations.
43
Rodriguez, Mijael, and Albin Söderholm. "Measuring Student Alertness Using the X2-30 Eye-Tracker : A study in the suitability of the X2-30 eye-tracker to measure alertness in a learning environment." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186438.
Анотація:
This study has investigated the suitability of the eye-tracker X2-30 from Tobii when measuring a student’s alertness level. To be able to determine the suitability of the X2-30 two different environments and two different subjects has been used. The environments were a lecture and webinars, and the two subjects were the two male authors of this study. The results indicate that the eye-tracker X2-30 can be useful when it’s used under optimal circumstances (i.e. webinars), since it needs to have few disturbing factors when gathering data. These factors regard the subjects not moving out of the tracking area, i.e. the area of which the X2-30 is able to track the eye, and consequently it also means that the subject needs to be careful not to move the hardware. When used under optimal circumstances it was possible to obtain accurate data regarding pupil behaviour and somewhat accurate data regarding blink rate, making data relevant and the equipment suitable for measuring of alertness under the correct circumstances.Denna studie undersöker lämpligheten hos Tobii ABs X2-30 eye-tracker för att mäta en students vakenhet. För att avgöra lämpligheten så har tester gjorts i två olika miljöer och med två olika försökspersoner. Miljöerna var en föreläsning och ett flertal webinars medan försökspersonerna var de två manliga författarna av denna studie. Resultaten indikerar att X2-30 kan vara användbar när den används under optimala omständigheter, det vill säga webinars, då den kräver så få störande faktorer som möjligt. Dessa faktorer rör utrustningens mätzon och att försökspersonen inte lämnar denna, samt att hårdvaran inte flyttas under mätning. När utrustningen användes under optimala förhållanden så var det möjligt att få precis data rörande pupillens beteende och ganska korrekt data rörande blinkfrekvens vilket gör utrustningen lämplig för mätning av vakenhet under rätt omständigheter.
44
Emteu, Tchagou Serge Vladimir. "Réduction à la volée du volume des traces d'exécution pour l'analyse d'applications multimédia de systèmes embarqués." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAM051/document.
Анотація:
Le marché de l'électronique grand public est dominé par les systèmes embarqués du fait de leur puissance de calcul toujours croissante et des nombreuses fonctionnalités qu'ils proposent.Pour procurer de telles caractéristiques, les architectures des systèmes embarqués sont devenues de plus en plus complexes (pluralité et hétérogénéité des unités de traitements, exécution concurrente des tâches, ...).Cette complexité a fortement influencé leur programmabilité au point où rendre difficile la compréhension de l'exécution d'une application sur ces architectures.L'approche la plus utilisée actuellement pour l'analyse de l'exécution des applications sur les systèmes embarqués est la capture des traces d'exécution (séquences d'événements, tels que les appels systèmes ou les changements de contexte, générés pendant l'exécution des applications).Cette approche est utilisée lors des activités de test, débogage ou de profilage des applications.Toutefois, suivant certains cas d'utilisation, les traces d'exécution générées peuvent devenir très volumineuses, de l'ordre de plusieurs centaines de gigaoctets.C'est le cas des tests d'endurance ou encore des tests de validation, qui consistent à tracer l'exécution d'une application sur un système embarqué pendant de longues périodes, allant de plusieurs heures à plusieurs jours.Les outils et méthodes d'analyse de traces d'exécution actuels ne sont pas conçus pour traiter de telles quantités de données.Nous proposons une approche de réduction du volume de trace enregistrée à travers une analyse à la volée de la trace durant sa capture.Notre approche repose sur les spécificités des applications multimédia, qui sont parmi les plus importantes pour le succès des dispositifs populaires comme les Set-top boxes ou les smartphones.Notre approche a pour but de détecter automatiquement les fragments (périodes) suspectes de l'exécution d'une application afin de n'enregistrer que les parties de la trace correspondant à ces périodes d'activités.L'approche que nous proposons comporte deux étapes : une étape d'apprentissage qui consiste à découvrir les comportements réguliers de l'application à partir de la trace d'exécution, et une étape de détection d'anomalies qui consiste à identifier les comportements déviant des comportements réguliers.Les nombreuses expériences, réalisées sur des données synthétiques et des données réelles, montrent que notre approche permet d'obtenir une réduction du volume de trace enregistrée d'un ordre de grandeur avec d'excellentes performances de détection des comportements suspectsThe consumer electronics market is dominated by embedded systems due to their ever-increasing processing power and the large number of functionnalities they offer.To provide such features, architectures of embedded systems have increased in complexity: they rely on several heterogeneous processing units, and allow concurrent tasks execution.This complexity degrades the programmability of embedded system architectures and makes application execution difficult to understand on such systems.The most used approach for analyzing application execution on embedded systems consists in capturing execution traces (event sequences, such as system call invocations or context switch, generated during application execution).This approach is used in application testing, debugging or profiling.However in some use cases, execution traces generated can be very large, up to several hundreds of gigabytes.For example endurance tests, which are tests consisting in tracing execution of an application on an embedded system during long periods, from several hours to several days.Current tools and methods for analyzing execution traces are not designed to handle such amounts of data.We propose an approach for monitoring an application execution by analyzing traces on the fly in order to reduce the volume of recorded trace.Our approach is based on features of multimedia applications which contribute the most to the success of popular devices such as set-top boxes or smartphones.This approach consists in identifying automatically the suspicious periods of an application execution in order to record only the parts of traces which correspond to these periods.The proposed approach consists of two steps: a learning step which discovers regular behaviors of an application from its execution trace, and an anomaly detection step which identifies behaviors deviating from the regular ones.The many experiments, performed on synthetic and real-life datasets, show that our approach reduces the trace size by an order of magnitude while maintaining a good performance in detecting suspicious behaviors
45
Warsop, Thomas E. "Three-dimensional scene recovery for measuring sighting distances of rail track assets from monocular forward facing videos." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/8994.
Анотація:
Rail track asset sighting distance must be checked regularly to ensure the continued and safe operation of rolling stock. Methods currently used to check asset line-of-sight involve manual labour or laser systems. Video cameras and computer vision techniques provide one possible route for cheaper, automated systems. Three categories of computer vision method are identified for possible application: two-dimensional object recognition, two-dimensional object tracking and three-dimensional scene recovery. However, presented experimentation shows recognition and tracking methods produce less accurate asset line-of-sight results for increasing asset-camera distance. Regarding three-dimensional scene recovery, evidence is presented suggesting a relationship between image feature and recovered scene information. A novel framework which learns these relationships is proposed. Learnt relationships from recovered image features probabilistically limit the search space of future features, improving efficiency. This framework is applied to several scene recovery methods and is shown (on average) to decrease computation by two-thirds for a possible, small decrease in accuracy of recovered scenes. Asset line-of-sight results computed from recovered three-dimensional terrain data are shown to be more accurate than two-dimensional methods, not effected by increasing asset-camera distance. Finally, the analysis of terrain in terms of effect on asset line-of-sight is considered. Terrain elements, segmented using semantic information, are ranked with a metric combining a minimum line-of-sight blocking distance and the growth required to achieve this minimum distance. Since this ranking measure is relative, it is shown how an approximation of the terrain data can be applied, decreasing computation time. Further efficiency increases are found by decomposing the problem into a set of two-dimensional problems and applying binary search techniques. The combination of the research elements presented in this thesis provide efficient methods for automatically analysing asset line-of-sight and the impact of the surrounding terrain, from captured monocular video.
46
Dollinger, Hannah J. "INCREASING PHYSICAL ACTIVITY IN MIDDLE SCHOOLERS WITH INTELLECTUAL DISABILITY USING GOAL SETTING AND FITNESS TRACKERS." UKnowledge, 2019. https://uknowledge.uky.edu/edsrc_etds/72.
Анотація:
The purpose of the study was to evaluate the effects of goal setting and fitness trackers to increase daily step counts in adolescents with intellectual disability. An A-B-A-B withdrawal research design was implemented to evaluate the effectiveness of the intervention. The results indicated that goal setting and fitness trackers were effective in increasing daily step counts for two out of three participants.
47
Tawfik, Aly M. "Incorporating Perceptions, Learning Trends, Latent Classes, and Personality Traits in the Modeling of Driver Heterogeneity in Route Choice Behavior." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/37338.
Анотація:
Driver heterogeneity in travel behavior has repeatedly been cited in the literature as a limitation that needs to be addressed. In this work, driver heterogeneity is addressed from four different perspectives. First, driver heterogeneity is addressed by models of driver perceptions of travel conditions: travel distance, time, and speed. Second, it is addressed from the perspective of driver learning trends and models of driver-types. Driver type is not commonly used in the vernacular of transportation engineering. It is a term that was developed in this work to reflect driver aggressiveness in route switching behavior. It may be interpreted as analogous to the commonly known personality-types, but applied to driver behavior. Third, driver heterogeneity is addressed via latent class choice models. Last, personality traits were found significant in all estimated models. The first three adopted perspectives were modeled as functions of variables of driver demographics, personality traits, and choice situation characteristics. The work is based on three datasets: a driving simulator experiment, an in situ driving experiment in real-world conditions, and a naturalistic real-life driving experiment. In total, the results are based on three experiments, 109 drivers, 74 route choice situations, and 8,644 route choices. It is assuring that results from all three experiments were found to be highly consistent. Discrepancies between predictions of network-oriented traffic assignment models and observed route choice percentages were identified and incorporating variables of driver heterogeneity were found to improve route choice model performance. Variables from all three groups: driver demographics, personality traits, and choice situation characteristics, were found significant in all considered models for driver heterogeneity. However, it is extremely interesting that all five variables of driver personality traits were found to be, in general, as significant as, and frequently more significant than, variables of trip characteristics â such as travel time. Neuroticism, extraversion and conscientiousness were found to increase route switching behavior, and openness to experience and agreeable were found to decrease route switching behavior. In addition, as expected, travel time was found to be highly significant in the models that were developed. However, unexpectedly, travel speed was also found to be highly significant, and travel distance was not as significant as expected. Results of this work are highly promising for the future of understanding and modeling of heterogeneity of human travel behavior, as well as for identifying target markets and the future of intelligent transportation systems.Ph. D.
48
Lopez, Cueva Patricia. "Debugging Embedded Multimedia Application Execution Traces through Periodic Pattern Mining." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-01006213.
Анотація:
La conception des systèmes multimédia embarqués présente de nombreux défis comme la croissante complexité du logiciel et du matériel sous-jacent, ou les pressions liées aux délais de mise en marche. L'optimisation du processus de débogage et validation du logiciel peut aider à réduire sensiblement le temps de développement. Parmi les outils de débogage de systèmes embarqués, un puissant outil largement utilisé est l'analyse de traces d'exécution. Cependant, l'évolution des techniques de tra¸cage dans les systèmes embarqués se traduit par des traces d'exécution avec une grande quantité d'information, à tel point que leur analyse manuelle devient ingérable. Dans ce cas, les techniques de recherche de motifs peuvent aider en trouvant des motifs intéressants dans de grandes quantités d'information. Concrètement, dans cette thèse, nous nous intéressons à la découverte de comportements périodiques sur des applications multimédia. Donc, les contributions de cette thèse concernent l'analyse des traces d'exécution d'applications multimédia en utilisant des techniques de recherche de motifs périodiques fréquents. Concernant la recherche de motifs périodiques, nous proposons une définition de motif périodique adaptée aux caractéristiques de la programmation paralléle. Nous proposons ensuite une représentation condensée de l'ensemble de motifs périodiques fréquents, appelée Core Periodic Concepts (CPC), en adoptant une approche basée sur les relations triadiques. De plus, nous définissons quelques propriétés de connexion entre ces motifs, ce qui nous permet de mettre en oeuvre un algorithme efficace de recherche de CPC, appelé PerMiner. Pour montrer l'efficacité et le passage à l'échelle de PerMiner, nous réalisons une analyse rigoureuse qui montre que PerMiner est au moins deux ordres de grandeur plus rapide que l'état de l'art. En plus, nous réalisons un analyse de l'efficacité de PerMiner sur une trace d'exécution d'une application multimédia réelle en présentant l'accélération accompli par la version parallèle de l'algorithme. Concernant les systèmes embarqués, nous proposons un premier pas vers une méthodologie qui explique comment utiliser notre approche dans l'analyse de traces d'exécution d'applications multimédia. Avant d'appliquer la recherche de motifs fréquents, les traces d'exécution doivent ˆetre traitées, et pour cela nous proposons plusieurs techniques de pré-traitement des traces. En plus, pour le post-traitement des motifs périodiques, nous proposons deux outils : un outil qui trouve des pairs de motifs en compétition ; et un outil de visualisation de CPC, appelé CPCViewer. Finalement, nous montrons que notre approche peut aider dans le débogage des applications multimédia à travers deux études de cas sur des traces d'exécution d'applications multimédia réelles.
49
Johnson-Reese, Shelia M. "On Track for Graduation: An Investigation of Causal Factors Related to Student Outcomes in a Credit Recovery Program in a Metro Atlanta School District." DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 2016. http://digitalcommons.auctr.edu/cauetds/44.
Анотація:
This study examined the relationship between credit recovery outcomes and select causal factors. In this study, credit recovery was defined as the extent to which students successfully complete the following courses: coordinate algebra, biology, physical science, and analytic geometry. Independent variables explored in this research were student motivation, student engagement, self-regulation, blended learning models, and formative assessments.
A mixed method design was used to triangulate the quantitative data with the teachers’ perceptions data collected from the qualitative data. The qualitative data examined how teachers used formative assessments to improve student learning, the
perception of the effectiveness of the program, and how credit recovery helped students to graduate from high school. The quantitative data found that there was no significant relationship between the independent variables in the study and credit recovery outcomes.
Additionally, the data revealed that there was no significant relationship between teacher perceptions and credit recovery outcomes. Although there was no significant relationship between the dependent and independent variables in the study, the data did indicate there was a significant relationship between gender and credit recovery outcomes. The study found there was a highly significant relationship between formative assessments and student motivation, validating what research has already demonstrated about the effectiveness of formative assessments and its potential to engage and motivate students. The research also found that there was a highly significant relationship between blended learning and student motivation, suggesting implications for how blended learning can be used to engage and motivate students in credit recovery programs.
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Bernardo, Alexandre. "Features for the Classification and Clustering of Music in Symbolic Format." Master's thesis, Department of Informatics, University of Lisbon, 2008. http://hdl.handle.net/10451/13947.
Анотація:
Music Information Retrieval is, nowadays, a highly active branch of research and development in the computer science field, and focuses several topics, including music genre classification. The work presented in this paper focus on Track and Genre Classification of music stored using MIDI format, To address the problem of MIDI track classification, we extract a set of descriptors that are used to train a classifier implemented by a Neural Network, based on the pitch levels and durations that describe each track. Tracks are classified into four classes: Melody, Harmony, Bass and Drums. In order to characterize the musical content from each track, a vector of numeric descriptors, normally known as shallow structure description, is extracted. Then they are used as inputs for the classifier which was implemented in the Matlab environment. In the Genre Classification task, two approaches are used: Language Modeling, in which a transition probabilities matrix is created for each type of track (Melody, Harmony, Bass and Drums) and also for each genre; and an approach based on Neural Networks, where a vector of numeric descriptors is extracted from each track (Melody, Harmony, Bass and Drums) and fed to a Neural Network Classifier. Six MIDI Music Corpora were assembled for the experiments, from six different genres, Blues, Country, Jazz, Metal, Punk and Rock. These genres were selected because all of them have the same base instruments, such as bass, drums, piano or guitar. Also, the genres chosen share some characteristics between them, so that the classification isn't trivial, and tests the classifiers robustness. Track Classification experiments using all descriptors and best descriptors were made, showing that using all descriptors is a wrong approach, as there are descriptors which confuse the classifier. Using carefully selected descriptors proved to be the best way to classify these MIDI tracks. Genre Classification experiments showed that the Single-Instrument Classifiers achieved the best results. Four genres achieved higher than 80% success rates: Jazz, Country, Metal and Punk. Future work includes: genetic algorithms; structurize tracks and songs; merge all presented classifiers into one full Automatic Genre Classification System