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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Student Perceptions On Learning By Design Method In Web-based Learning Environment: A Case Study

Akman, Evrim 01 May 2010 (has links) (PDF)
The purpose of this study was to investigate the perceptions of students in an implementation of &ldquo / Learning by Design&rdquo / method through a web based learning environment. The information gathered from the students enrolled in the undergraduate course / &ldquo / Foundations of Distance Education&rdquo / in 2009 Summer School and 2009-2010 Fall Semesters was evaluated. The course was given in blended form, i.e. face to face lessons and online instructional activities were performed together. In the web based part of the course, several educational modules of an open source learning management system (LMS), such as quizzes, forums, lesson pages, wiki pages, mail interface etc. were used. The students were responsible for implementing an educational course site on the LMS platform, using the course curriculum applications. Within the scope of this thesis, the perceptions of the students about course-related projects, and online and classroom activities were investigated through interviews and questionnaires. The academic development of students was also considered in the study. Additionally, several informal interviews were also done with the instructor of the course in order to investigate his perceptions about the conduct of the course. Questionnaire results have been analyzed quantitatively and face to face interview results have been analyzed qualitatively. Both quantitative and qualitative data indicated that the students&rsquo / perceptions about how the course was conducted and the learning by design activities were generally positive. Especially the project work, which was assigned as a requisite of the learning by design method, was pointed out as a positive factor in students&#039 / learning of the subject matter both in the questionnaires and in the face to face interviews. Another important finding of the interview and questionnaire results was that the communication between the instructor and the students contributed positively to not only learning the course content but the quality of the projects as well. As an outcome of this study, many important factors, which lead to successful results in implementation of learning by design method in a web based environment, have been identified. These results are presented in detail in the &#039 / Discussion and Recommendations&#039 / section.
32

Reinforcement learning and reward estimation for dialogue policy optimisation

Su, Pei-Hao January 2018 (has links)
Modelling dialogue management as a reinforcement learning task enables a system to learn to act optimally by maximising a reward function. This reward function is designed to induce the system behaviour required for goal-oriented applications, which usually means fulfilling the user’s goal as efficiently as possible. However, in real-world spoken dialogue systems, the reward is hard to measure, because the goal of the conversation is often known only to the user. Certainly, the system can ask the user if the goal has been satisfied, but this can be intrusive. Furthermore, in practice, the reliability of the user’s response has been found to be highly variable. In addition, due to the sparsity of the reward signal and the large search space, reinforcement learning-based dialogue policy optimisation is often slow. This thesis presents several approaches to address these problems. To better evaluate a dialogue for policy optimisation, two methods are proposed. First, a recurrent neural network-based predictor pre-trained from off-line data is proposed to estimate task success during subsequent on-line dialogue policy learning to avoid noisy user ratings and problems related to not knowing the user’s goal. Second, an on-line learning framework is described where a dialogue policy is jointly trained alongside a reward function modelled as a Gaussian process with active learning. This mitigates the noisiness of user ratings and minimises user intrusion. It is shown that both off-line and on-line methods achieve practical policy learning in real-world applications, while the latter provides a more general joint learning system directly from users. To enhance the policy learning speed, the use of reward shaping is explored and shown to be effective and complementary to the core policy learning algorithm. Furthermore, as deep reinforcement learning methods have the potential to scale to very large tasks, this thesis also investigates the application to dialogue systems. Two sample-efficient algorithms, trust region actor-critic with experience replay (TRACER) and episodic natural actor-critic with experience replay (eNACER), are introduced. In addition, a corpus of demonstration data is utilised to pre-train the models prior to on-line reinforcement learning to handle the cold start problem. Combining these two methods, a practical approach is demonstrated to effectively learn deep reinforcement learning-based dialogue policies in a task-oriented information seeking domain. Overall, this thesis provides solutions which allow truly on-line and continuous policy learning in spoken dialogue systems.
33

Specifika domácí přípravy žáků na anglický jazyk / Specifics of pupils' home preparation for English lessons

Smrčková, Kamila January 2017 (has links)
(in English) This diploma thesis deals with the instruction of home preparation of the lower secondary school students for English lessons. It describes the pupils, teachers and parents attitudes to English as a second language and determines home preparation from points of view of particular groups of respondents. The empirical part of this thesis is addressed to learning strategies and learning techniques used by pupils of the particular school.
34

Mobile Learning Effectiveness in Higher Education

Yaqub, Naveed, Iqbal, Atif January 2010 (has links)
This research investigates mobile learning effectiveness in higher education. Mobile learning is composition of two words Mobile and Learning. In simple words mobile learning is mobility of learners by using mobile technologies in learning environment. Many researches addressed mobile learning but few of them covered mobile learning effectiveness. This study explores mobile learning effectiveness with the help of learning theories and models. Behaviorist, cognitive, humanistic, situational, and mobile learning theories are discussed that elaborate social, psychological, and philosophical aspects of learning.  Detailed evolution of learning is also part of this report that covers the literature of distance learning, electronic learning as well as formal and informal learning. Three effective learning models are taken in consideration: the Garrison’s Community of Inquiry, the Swan’s Interactivity and Online Learning, and the Danaher and his colleagues’ model of mobile learning and teaching evaluation model. Danaher’s model is selected as a conceptual framework of the study that is composed of three elements that are engagement, presence and flexibility. Engagement is the active participation of the learner in learning activities. Presence means being there, physically or mentally, in learning activity or place. Flexibility is how easy and facilitative the system is for teachers and students. These three elements are used to determine mobile learning effectiveness.  Survey method was used as our research approach. Empirical data was collected from Linnaeus University (prev. Växjö University) Sweden, by using two separate questionnaires for students and teachers. Collected data was analyzed with respect to learning theories and the theoretical model. The result reveals the potential of mobile learning as an effective mode of learning in terms of engagement and presence but flexibilty approved to be weaker in mobile learning.
35

Tiefes Reinforcement Lernen auf Basis visueller Wahrnehmungen

Lange, Sascha 19 May 2010 (has links)
Die vorliegende Arbeit widmet sich der Untersuchung und Weiterentwicklung selbständig lernender maschineller Lernverfahren (Reinforcement Lernen) in der Anwendung auf visuelle Wahrnehmungen. Zuletzt wurden mit der Einführung speicherbasierter Methoden in das Reinforcement Lernen große Fortschritte beim Lernen an realen Systemen erzielt, aber der Umgang mit hochkomplexen visuellen Eingabedaten, wie sie z.B. von einer digitalen Kamera aufgezeichnet werden, stellt weiterhin ein ungelöstes Problem dar. Bestehende Methoden sind auf den Umgang mit niedrigdimensionalen Zustandsbeschreibungen beschränkt, was eine Anwendung dieser Verfahren direkt auf den Strom von Bilddaten bisher ausschließt und den vorgeschalteten Einsatz klassischer Methoden des Bildverstehens zur Extraktion und geeigneten Kodierung der relevanten Informationen erfordert. Einen Ausweg bietet der Einsatz von so genannten `tiefen Autoencodern'. Diese mehrschichtigen neuronalen Netze ermöglichen es, selbstorganisiert niedrigdimensionale Merkmalsräume zur Repräsentation hochdimensionaler Eingabedaten zu erlernen und so eine klassische, aufgabenspezifische Bildanalyse zu ersetzen. In typischen Objekterkennungsaufgaben konnten auf Basis dieser erlernten Repräsentationen bereits beeindruckende Ergebnisse erzielt werden. Im Rahmen der vorliegenden Arbeit werden nun die tiefen Autoencodernetze auf ihre grundsätzliche Tauglichkeit zum Einsatz im Reinforcement Lernen untersucht. Mit dem ``Deep Fitted Q''-Algorithmus wird ein neuer Algorithmus entwickelt, der das Training der tiefen Autoencodernetze auf effiziente Weise in den Reinforcement Lernablauf integriert und so den Umgang mit visuellen Wahrnehmungen beim Strategielernen ermöglicht. Besonderes Augenmerk wird neben der Dateneffizienz auf die Stabilität des Verfahrens gelegt. Im Anschluss an eine Diskussion der theoretischen Aspekte des Verfahrens wird eine ausführliche empirische Evaluation der erzeugten Merkmalsräume und der erlernten Strategien an simulierten und realen Systemen durchgeführt. Dabei gelingt es im Rahmen der vorliegenden Arbeit mit Hilfe der entwickelten Methoden erstmalig, Strategien zur Steuerung realer Systeme direkt auf Basis der unvorverarbeiteten Bildinformationen zu erlernen, wobei von außen nur das zu erreichende Ziel vorgegeben werden muss.
36

Machine Learning Based Failure Detection in Data Centers

Piran Nanekaran, Negin January 2020 (has links)
This work proposes a new approach to fast detection of abnormal behaviour of cooling, IT, and power distribution systems in micro data centers based on machine learning techniques. Conventional protection of micro data centers focuses on monitoring individual parameters such as temperature at different locations and when these parameters reach certain high values, then an alarm will be triggered. This research employs machine learning techniques to extract normal and abnormal behaviour of the cooling and IT systems. Developed data acquisition system together with unsupervised learning methods quickly learns the physical dynamics of normal operation and can detect deviations from such behaviours. This provides an efficient way for not only producing health index for the micro data center, but also a rich label logging system that will be used for the supervised learning methods. The effectiveness of the proposed detection technique is evaluated on an micro data center placed at Computing Infrastructure Research Center (CIRC) in McMaster Innovation Park (MIP), McMaster University. / Thesis / Master of Science (MSc)
37

Artificial intelligence-based clinical classification of diseases: Utilizing gut microbiota as a feature for supervised learning and diagnostic screening of inflammatory bowel diseases

Manandhar, Ishan January 2021 (has links)
No description available.
38

Le nuove tecnologie come valore aggiunto del CLIL / Adding Value to CLIL through the New Technology

LEONE, VINCENZA 31 March 2011 (has links)
Questa tesi è il risultato di uno studio sul CLIL e le nuove tecnologie per la didattica nato da un insieme di fattori: il desiderio di investigare l’uso delle nuove tecnologie a scuola, considerando le possibili implicazioni, e il bisogno di migliorare la qualità dell’apprendimento linguistico attraverso la creazione di nuovi stimoli per gli studenti. Tale studio è costituito da una parte teorica e una pratica di ricerca sul campo in cui si sono presi in considerazione diversi gradi di scuola e anche corsi universitari. La ricerca ha dimostrato l’influenza positiva delle nuove tecnologie come valore aggiunto al CLIL e ha riconosciuto il ruolo chiave dell’insegnante in questo tipo di approccio bifocale. / This thesis is the result of a research study in CLIL and Technologies that arose from the combination of different factors: the desire of investigate the implementation of new technologies at school, considering the possible implication, and the need to improve the quality of language learning giving new stimuli to the students. It is based on a theoretical study and an action research which investigated different school levels and university courses. The research proved the positive stimulus of new technologies as value-added to CLIL and recognised the key role of the teacher in such a double-focus approach.
39

Differences in the vocational rehabilitation process between African Americans and European Americans with specific learning disabilities on acceptance, services, and reasons for closure

Elmore Williams, Precious Denise, January 1900 (has links)
Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.
40

Supporting Workplace Learning: Supervisory and Peer Support Effect on Novice Firefighter Informal Learning Engagement

Kauser, Frederick L. 18 May 2017 (has links)
No description available.

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