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Dissertations / Theses on the topic 'Learning content'
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Roberts, Jonathan Ralph. "Learning-based procedural content generation." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/learningbased-procedural-content-generation(1af8d23d-8ceb-416b-b4ba-d7a2970b47ef).html.
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Procedural Content Generation (PCG) has become one of the hottest topics in Computational Intelligence and Artificial Intelligence (AI) game research in the past few years. PCG is the process of automatically creating content for video games, rather than by hand, and can offer great benefits for video games companies by helping to bring costs down and quality up. By guiding the process with AI it can be enhanced further and even be made to personalize content for target players. Among the current research into PCG, search-based approaches overwhelmingly dominate. While search-based algorithms have been shown to have great promise and produce several success stories there are a number of open challenges remaining. In this thesis, we present the Learning-Based Procedural Content Generation (LBPCG) framework, which is an alternative, novel approach designed to address some of these challenges. The major difference between the LBPCG framework and contemporary approaches is that the LBPCG is designed to learn about the problem space, freeing itself from the necessity for hard-coded information by the game developers. In this thesis we apply the LBPCG to a concrete example, the classic first-person shooter Quake, and present results showing the potential of the framework in generating quality content.
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Jones, Christopher Richard. "Context, content and cooperation : an ethnographic study of collaborative learning online." Thesis, Manchester Metropolitan University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267538.
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Ntuli, Esther, and Arnold Nyarambi. "Learning in a Global Context: Education Diplomacy in Primary Grade Content Preparation." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etsu-works/8218.
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The article shares the authors' thoughts about the concept of education diplomacy and its relevance in developing content for elementary grade levels. They emphasize the importance of learning about education diplomacy at an early age in order to develop adaptability among human beings. The piece offers insights on developing content for teacher preparation programs to provide elementary teachers with tools to teach about education diplomacy to the future generation. It also opens up a discussion on the importance of the intersecting time-tested skills, knowledge, and dispositions required by education diplomats in understanding and applying the concept.
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Hooper, Hugh R. "Computers and content-based language learning." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28072.
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Can a computer database be used to augment a content-based approach to developing academic discourse? This document reports on the integration of these three areas in student tasks in a unit of work (biology) taught by a content teacher and a language specialist to a class of grade 7 students in a Vancouver elementary
school. The objectives of the study were 1) to investigate the connections between biology content, the academic discourse of classification and a computer database, and 2) to identify if each area was in fact related to the knowledge structures of classification and description. The research method focussed on, ethnographic observations, interviews and recordings of the students and the teachers as they worked through the unit. Analysis of the findings seems to suggest that there are connections
between biology content, academic discourse of classification
and a computer database, and that each area is related to the knowledge structure of classification and description. This finding further suggests that student tasks at the computer have the potential for developing academic discourse and the learning of content. This potential may deserve further investigation by both teachers and researchers.Education, Faculty of
Language and Literacy Education (LLED), Department of
Graduate
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Берест, Олег Борисович, Олег Борисович Берест, and Oleh Borysovych Berest. "Modern technologies for learning content creation." Thesis, Сумський державний університет, 2012. http://essuir.sumdu.edu.ua/handle/123456789/29464.
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One of the teacher’s main task is to make his subject as more creative as it can be possible for students to interest them in it. There are many ways to make your lesson more cognitive and useful (for instance, usage of free open educational resources), but nowadays visual interactive learning tools become more popular and popular. And the problem is where to find or how to create necessary staff for you.
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Collins, Ronald W. "Transfer of learning between related and less related tasks using content specific and content general learning strategies." FIU Digital Commons, 1990. http://digitalcommons.fiu.edu/etd/2409.
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This study compared learning strategies in an effort to determine which strategy would be most beneficial to transfer of learning. A number of approaches were suggested in the related literature for maximizing learning, one of which was to use "learning how to learn," also known by the term content general learning strategy. This study hypothesized that the use of content general learning strategies would produce more transfer of learning across both related and less related tasks than content specific learning strategies. Both learning strategies were combined with either a visual and semantic method of encoding or a semantic only method of encoding. A factorial analysis of covariance (ANCOVA) which combines regression analysis with analysis of variance tested the null hypothesis that the adjusted population means were equal for the covariate of the pretest and the dependent variable of the posttest. Analysis procedures of the ANCOVA on data results reflect that for related and less related tasks, content general with visual and semantic encoding outperformed all other methods tested. The results indicate that a general learning strategy (learning how to learn) is more productive for learning achievement in situations where transfer of learning is desired.
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Svensson, Martin, and Oskar Pettersson. "Case study: Extending content metadata by appending user context." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-743.
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Recent developments in modern computing and wireless networks allow mobile devices to be connected to the Internet regardless of their physical location. These mobile devices, such as smart phones and PDAs, have turned into powerful multimedia units allowing users to become producers of rich media content. This latest development contributes to the ever-growing amount of digital material existing on the World Wide Web, and at the same time creates a new information landscape that combines content coming from both, the wired and mobile Internet. Thus, it is important to understand the context or settings in which mobile devices are used, and what is the digital content produced by the different users. In order to gain more knowledge about this domain, we have investigated how to extend the standard metadata related to content with a metadata domain describing the context, or settings in which the content has been created.
In order to limit the scope of our work, we have focused our efforts in a specific case taking place in a project called AMULETS. The AMULETS-project contains all of the elements we need in order to resemble the contextual setting in a metadata model. Combined with the technical metadata associated to the digital content, we try to display the benefits of capturing the different attributes of the context that were present when the content was generated. Additionally, we have created a proof-of-concept Entity Relation (ER)-diagram which proposes how the metadata models can be implemented in a relational database. As the nature of the thesis is design-oriented, a model has been developed and it will be illustrated throughout this report. The aim of the thesis is to show how it is possible to design new metadata models that combine both relevant attributes of the context and content in order to develop new educational activities supported by location-based services.
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Silva, Muñoz Lydia. "Ontology-based metadata for e-learning content." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2004. http://hdl.handle.net/10183/6207.
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Atualmente a popularidade da Web incentiva o desenvolvimento de sistemas hipermídia dedicados ao ensino a distância. Não obstante a maior parte destes sistemas usa os mesmos recursos do ensino tradicional, apresentado o conteúdo como páginas HTML estáticas, não fazendo uso das novas tecnologias que a Web oferece. Um desafío atual é desenvolver sistemas educativos que adaptem seu conteúdo ao estilo de aprendizagem, contexto e nível de conhecimento de cada aluno. Outro assunto de pesquisa é a capacidade de interoperar na Web reutilizando objetos de ensino. Este trabalho apresenta um enfoque que trata esses dois assuntos com as tecnologias da Web Semântica. O trabalho aqui apresentado modela o conhecimento do conteúdo educativo e do perfil do aluno pelo uso de ontologias cujo vocabulário é um refinamento de vocabulários padrões existentes na Web como pontos de referência para apoiar a interoperabilidade semântica. As ontologias permitem a representação numa linguagem formal dos metadados relativos a objetos de ensino simples e das regras que definem suas possíveis formas de agrupamento para desenvolver objetos mais complexos. Estes objetos mais complexos podem ser projetados para se adequar ao perfil de cada aluno por agentes inteligentes que usam a ontologia como origem de suas crenças. A reutilização de objetos de ensino entre diferentes aplicações é viabilizada pela construção de um perfil de aplicação do padrão IEEE LOM-Learning Object Metadata.Nowadays, the popularity of the Web encourages the development of Hypermedia Systems dedicated to e-learning. Nevertheless, most of the available Web teaching systems apply the traditional paper-based learning resources presented as HTML pages making no use of the new capabilities provided by the Web. There is a challenge to develop educative systems that adapt the educative content to the style of learning, context and background of each student. Another research issue is the capacity to interoperate on the Web reusing learning objects. This work presents an approach to address these two issues by using the technologies of the Semantic Web. The approach presented here models the knowledge of the educative content and the learner’s profile with ontologies whose vocabularies are a refinement of those defined on standards situated on the Web as reference points to provide semantics. Ontologies enable the representation of metadata concerning simple learning objects and the rules that define the way that they can feasibly be assembled to configure more complex ones. These complex learning objects could be created dynamically according to the learners’ profile by intelligent agents that use the ontologies as the source of their beliefs. Interoperability issues were addressed by using an application profile of the IEEE LOM- Learning Object Metadata standard.
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Lorenz, Anja. "Kooperationsunterstützung in einem Learning Content Management System (LCMS)." Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-82022.
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Learning Content Management Systeme (LCMS) unterstützen die professionelle Erstellung, Verwaltung und Auslieferung von Lernmaterialien [BHMH02]. Die Speicherung der hierfür verarbeiteten Lerninhalte in einem zentralen Repository ermöglicht neben deren Wiederverwendung auch den Zugriff für mehrere Nutzer und somit das Zusammenführen der verschiedenen Kompetenzen, die während der Erstellung benötigt werden: Die mithilfe der Lernmaterialien zu vermittelnden Inhalte müssen nicht nur fachlich richtig, sondern auch didaktisch, gestalterisch und technisch für ein oder mehrere Zielgruppen individuell aufbereitet worden sein. Dabei reichen die Zielgruppen von verschiedenen Abteilungen bis hin zu Lernern mit verschiedenen Muttersprachen und Kulturen in international agierenden Unternehmen und Bildungseinrichtungen. Die Arbeit der Nutzer mit dem LCMS wird durch verschiedene Mechanismen und Funktionalitäten erheblich vereinfacht, ihre Zusammenarbeit untereinander blieb bisher aber weitestgehend unbeachtet. Das Promotionsvorhaben, das in Kooperation mit der chemmedia AG erfolgt, setzt an diesem Punkt an. Als Vorbild und somit zur Identifikation von Kommunikations- und Kooperationskonzepten werden Social- Software-Anwendungen herangezogen, bei denen die gemeinsame Content-Erstellung scheinbar unproblematisch stattfindet. Als methodische Klammer wird die DIN EN ISO/IEC 19796 [Deu09] herangezogen. Sie gibt einerseits die für die Analyse nötige Strukturierung der Prozesse bei der Lernangebotserstellung vor und liefert außerdem die für die Evaluation benötigten Qualitätskriterien.
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Periasamy, Radhakrishnan. "Machine learning in hypermedia using digital image content." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310680.
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Marks, Lori J. "Learning Strategies for Reading, Writing, and Content Areas." Digital Commons @ East Tennessee State University, 1995. https://dc.etsu.edu/etsu-works/3574.
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Marter, Matthew John. "Learning to recognise visual content from textual annotation." Thesis, University of Surrey, 2019. http://epubs.surrey.ac.uk/850052/.
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This thesis explores how machine learning can be applied to the task of learning to recognise visual content from different forms of textual annotation, bringing together computer vision and natural language processing. The data used in the thesis is taken from real world sources including broadcast television and photographs harvested from the internet. This leads to very few constraints on the data meaning there can be large variations in lighting, facial expression, visual properties of objects and camera angles. These sources provide the levels of data required to support modern machine learning approaches. However, annotation and or ground truth are not available and potentially expensive to obtain. This work therefore, will employ weak textual annotation in the form of subtitles, scripts, captions and tags. The use of weak textual annotation means that different techniques are also required to handle the natural language that is used to describe the visual content. Character identification is a challenge that requires a different approach due to the similarities that will be shared between all faces. As with location recognition, the script is aligned with the video using subtitles. Faces are detected using a face detector and facial landmarks are regressed. These facial landmarks are used to create a descriptor for the face. Multiple techniques are used to assign the faces identities from the script. In the first technique, facial descriptors are clustered to the number of characters and the size of the clusters matched with the screen time of the character. In the second technique, a random forest is trained to differentiate between different faces, and the splitting criteria are used to reduce the dimensionality of the facial features. The reduced dimensionality allows a distribution of facial features to be created per scene. Then rules are created to separate scenes and identify distributions for individual characters. As well as this, data harvested from the internet is used to learn the appearance of the actors in the video and then matched to the characters. Using the various techniques give a character labelling performance of up to 82.75% accuracy using a SIFT-based descriptor and up to 96.82% using a state of the art descriptor. Automatic caption generation for images is a relatively new and complex topic as it requires both understanding of the visual content in the image and the formation of natural language. Deep learning is powerful for object recognition and provides excellent performance on image recognition data sets. Pretrained convolutional neural networks (CNNs) were fine tuned using the parts of speech (POS) extracted from the natural language captions. A probabilistic language model can be created from the captions in the training data and be used to recreate new sentences for unseen images. To better model more complex language rules, a recurrent neural network (RNN) is used to generate sentences directly from features extracted from a CNN. An RNN that uses attention to look at different parts of an image can also utilise the final layers of a CNN to provide context for the whole image. Location recognition, character identification and RNNs are combined to automatically generate descriptions for broadcast television using character and location names. This creates a full pipeline for automatically labelling an unseen episode of a television series. Compared with ground truth input of location and characters, only a small drop in performance occurs when using labels predicted by computer vision and machine learning techniques. Using ground truth, a CIDEr score of 1.585 is achieved compared with 1.343 for a fully predicted system. Data providing emotional context for words and images allow the RNN to be used to manipulate the emotional context for images. Subjective testing shows that the output captions are more emotive than captions generated without emotional context 74.85% of the time, and are almost equal to human written captions. Adjusting the emotional context is shown to generate captions that alter the content to reflect the emotion. The fusion of computer vision and natural language processing through machine learning represents an important step for both fields.
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Dawod, Zainb. "Enhancing student learning journeys with semantically annotated content." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/16208.
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There is an increasing interest in developing existing Special Educational Needs (SEN) teaching methods due to recent concerns regarding the number of SEN pupils in schools. Communication is difficult for students when they have little or no clear speech. Consequently, a range of communication systems are used as an alternative to speech, including symbols, pictures or gestures. Importantly, helping students to better communicate also improves their education, friendships and independence. However, it is acknowledged that creating these educational resources is time consuming and expensive, and the learning results are not recognised as being as effective as required. Semantic Web technology has had an impact in the educational field and offers the required linkages for more engagement with Web content. There is, however, a considerable gap in Semantic Web research between the contributions in the mainstream educational field and research undertaken into special educational needs (SEN) students. This thesis presents an augmented World Wide Web (WWW) vision utilising annotation to more effectively support diverse special educational needs students. Students are supported in part by a SEN Teaching Platform (SENTP), one artefact from this design science research. Poetry is used as a website teaching material because of its significant impact on special needs students as it is a difficult topic to understand. The first stage of the research is to select the appropriate tools for testing annotation techniques in a real SEN environment. Later, a design of the proposed SEN teaching platform is built based on a Semantic Web annotation tool (Amaya) coordinated with a web application. Design is evaluated by conducting a pilot study in schools caring for special needs students (SEN). Evaluations were carried out at two schools, interviewing nine participants (Teachers, Teaching Assistant) in the UK. SENTP is tested for using Semantic Web technology to benefit the education of SEN students by utilizing Semantic Web annotation tools. This research further improves the SENTP with additional support for cognitive load using specific annotation formats within the Amaya annotation tool. Field testing is carried out at six UK schools with twenty-two participants being interviewed. Cognitive load principles are shown to improve both learning and class behaviour, also supporting teachers in the production of educational content. The pilot study and field testing results reveal that the proposed approach is effective. Following this, designed artefacts are synthesised within a wider design blueprint that articulates how this new world of annotated digital media is designed, deployed and consumed. Finally, SENTP ontology is created using OWL language and Protégé 5. The main goal of this ontology is to produce a wider design SENTP ontology that can be adapted to wider teaching purposes.
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Mirri, Silvia <1975>. "Rich media content adaptation in e-learning systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/375/.
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The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services.
Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education.
Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in
enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or
enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome
constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic
learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student.
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Reese, Debbie Denise. "Metaphor and Content: An Embodied Paradigm for Learning." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/26564.
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Through a direct application of two cognitive science theories, conceptual metaphor (Lakoff & Johnson, 1980, 1999) and structure mapping (Gentner, 1983, 1989; Gentner & Markman, 1995), this project defined an instructional design model for the design, development, and assessment of metaphor-enhanced, computer-mediated learning environments. It used the model to produce an instructional product with a metaphor-based interface. The project also built a parallel learning environment that employed a concept map interface. To test the metaphor-based productâ s effectiveness at enabling learners to build rich mental models of a complex, abstract concept, the project ran fifty-seven preservice teachers (55 female, 2 male; mean age of 21) through the instruction, randomly assigning half to the concept map interface environment and half to the metaphor-based interface environment. Participants completed four essay-type assessment questions. Trained raters, blind to participant assignment, isolated any of the 13 targeted concepts present within participantsâ protocols and, through consensus, constructed a concept map for each participant, representing that participantâ s mental model of the targeted domain. Map attributes were translated into four weighted subscores (nodes, branches, levels, and cross-links) and summed. Comparison across the two groups indicated no significant difference for richness of mental model, t(55)=-.72, p> .05, although the discussion suggests methods for increasing the power in subsequent experimental sessions. A significant interaction between Subscore and Achievement, F(3,51)=33.42, p< .01, suggests that concept map cross-links are much more sensitive to differences in domain integration and the general richness of a participantâ s mental model than the level and branch subscores. This result has implications for classroom application. Concept maps have taken a place as a learnerâ s, a teacherâ s, and a researcherâ s tool. With cross-domain validation and domain-specific extensions, specification of the relative sensitivity of various subscales, that is, the structure of the concept map, will enable educators to justify weighting scales and identify learner achievement. Credible concept map weighting scales also enhance learnersâ self-reliant and impartial assessment of personal growth in domain-specific knowledge. Results suggest that learners who have difficulty integrating domain concepts require direct, explicit instruction to help them to make connections between disparate conceptual strands.Ph. D.
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Chafik, Sanaa. "Machine learning techniques for content-based information retrieval." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL008/document.
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Avec l’évolution des technologies numériques et la prolifération d'internet, la quantité d’information numérique a considérablement évolué. La recherche par similarité (ou recherche des plus proches voisins) est une problématique que plusieurs communautés de recherche ont tenté de résoudre. Les systèmes de recherche par le contenu de l’information constituent l’une des solutions prometteuses à ce problème. Ces systèmes sont composés essentiellement de trois unités fondamentales, une unité de représentation des données pour l’extraction des primitives, une unité d’indexation multidimensionnelle pour la structuration de l’espace des primitives, et une unité de recherche des plus proches voisins pour la recherche des informations similaires. L’information (image, texte, audio, vidéo) peut être représentée par un vecteur multidimensionnel décrivant le contenu global des données d’entrée. La deuxième unité consiste à structurer l’espace des primitives dans une structure d’index, où la troisième unité -la recherche par similarité- est effective.Dans nos travaux de recherche, nous proposons trois systèmes de recherche par le contenu de plus proches voisins. Les trois approches sont non supervisées, et donc adaptées aux données étiquetées et non étiquetées. Elles sont basées sur le concept du hachage pour une recherche efficace multidimensionnelle des plus proches voisins. Contrairement aux approches de hachage existantes, qui sont binaires, les approches proposées fournissent des structures d’index avec un hachage réel. Bien que les approches de hachage binaires fournissent un bon compromis qualité-temps de calcul, leurs performances en termes de qualité (précision) se dégradent en raison de la perte d’information lors du processus de binarisation. À l'opposé, les approches de hachage réel fournissent une bonne qualité de recherche avec une meilleure approximation de l’espace d’origine, mais induisent en général un surcoût en temps de calcul.Ce dernier problème est abordé dans la troisième contribution. Les approches proposées sont classifiées en deux catégories, superficielle et profonde. Dans la première catégorie, on propose deux techniques de hachage superficiel, intitulées Symmetries of the Cube Locality sensitive hashing (SC-LSH) et Cluster-Based Data Oriented Hashing (CDOH), fondées respectivement sur le hachage aléatoire et l’apprentissage statistique superficiel. SCLSH propose une solution au problème de l’espace mémoire rencontré par la plupart des approches de hachage aléatoire, en considérant un hachage semi-aléatoire réduisant partiellement l’effet aléatoire, et donc l’espace mémoire, de ces dernières, tout en préservant leur efficacité pour la structuration des espaces hétérogènes. La seconde technique, CDOH, propose d’éliminer l’effet aléatoire en combinant des techniques d’apprentissage non-supervisé avec le concept de hachage. CDOH fournit de meilleures performances en temps de calcul, en espace mémoire et en qualité de recherche.La troisième contribution est une approche de hachage basée sur les réseaux de neurones profonds appelée "Unsupervised Deep Neuron-per-Neuron Hashing" (UDN2H). UDN2H propose une indexation individuelle de la sortie de chaque neurone de la couche centrale d’un modèle non supervisé. Ce dernier est un auto-encodeur profond capturant une structure individuelle de haut niveau de chaque neurone de sortie.Nos trois approches, SC-LSH, CDOH et UDN2H, ont été proposées séquentiellement durant cette thèse, avec un niveau croissant, en termes de la complexité des modèles développés, et en termes de la qualité de recherche obtenue sur de grandes bases de données d'informationThe amount of media data is growing at high speed with the fast growth of Internet and media resources. Performing an efficient similarity (nearest neighbor) search in such a large collection of data is a very challenging problem that the scientific community has been attempting to tackle. One of the most promising solutions to this fundamental problem is Content-Based Media Retrieval (CBMR) systems. The latter are search systems that perform the retrieval task in large media databases based on the content of the data. CBMR systems consist essentially of three major units, a Data Representation unit for feature representation learning, a Multidimensional Indexing unit for structuring the resulting feature space, and a Nearest Neighbor Search unit to perform efficient search. Media data (i.e. image, text, audio, video, etc.) can be represented by meaningful numeric information (i.e. multidimensional vector), called Feature Description, describing the overall content of the input data. The task of the second unit is to structure the resulting feature descriptor space into an index structure, where the third unit, effective nearest neighbor search, is performed.In this work, we address the problem of nearest neighbor search by proposing three Content-Based Media Retrieval approaches. Our three approaches are unsupervised, and thus can adapt to both labeled and unlabeled real-world datasets. They are based on a hashing indexing scheme to perform effective high dimensional nearest neighbor search. Unlike most recent existing hashing approaches, which favor indexing in Hamming space, our proposed methods provide index structures adapted to a real-space mapping. Although Hamming-based hashing methods achieve good accuracy-speed tradeoff, their accuracy drops owing to information loss during the binarization process. By contrast, real-space hashing approaches provide a more accurate approximation in the mapped real-space as they avoid the hard binary approximations.Our proposed approaches can be classified into shallow and deep approaches. In the former category, we propose two shallow hashing-based approaches namely, "Symmetries of the Cube Locality Sensitive Hashing" (SC-LSH) and "Cluster-based Data Oriented Hashing" (CDOH), based respectively on randomized-hashing and shallow learning-to-hash schemes. The SC-LSH method provides a solution to the space storage problem faced by most randomized-based hashing approaches. It consists of a semi-random scheme reducing partially the randomness effect of randomized hashing approaches, and thus the memory storage problem, while maintaining their efficiency in structuring heterogeneous spaces. The CDOH approach proposes to eliminate the randomness effect by combining machine learning techniques with the hashing concept. The CDOH outperforms the randomized hashing approaches in terms of computation time, memory space and search accuracy.The third approach is a deep learning-based hashing scheme, named "Unsupervised Deep Neuron-per-Neuron Hashing" (UDN2H). The UDN2H approach proposes to index individually the output of each neuron of the top layer of a deep unsupervised model, namely a Deep Autoencoder, with the aim of capturing the high level individual structure of each neuron output.Our three approaches, SC-LSH, CDOH and UDN2H, were proposed sequentially as the thesis was progressing, with an increasing level of complexity in terms of the developed models, and in terms of the effectiveness and the performances obtained on large real-world datasets
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Bodin, Erik. "Video content annotation automation using machine learning techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-155751.
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Annotations describing semantic content within video material is essential for ecient search of such content, e.g. allowing for search engine queries to return only relevant segments of video clips within large content management systems. However, manual annotation of video material is a dull and time-consuming task, eectively lowering thequality and quantity of such annotations. In this rapport a system to automate most of the process is suggested. The system learns from video material with user-provided annotationsto infer annotations for new material automatically, without requiring any system changes between dierent user-created labeling schemes. The prototype of such a system presentedin this rapport, evaluated on a few concepts, is showing promising results for concepts with high inuence on the scene environments.Annotering av semantiskt innehall av videomaterial ar kritiskt for eektiv sokning inomsadant material, vilket i sin tur mojliggor t.ex. att forfragningar till sokmotorer kanreturerna endast relevanta segment av videoklipp inom stora videohanteringssystem.Manuell annotering ar dock en trakig och tidsodande uppgift, vilket medfor lag kvalite ochliten mangd av sadana annoteringar. I denna uppsats foreslas ett system for attautomatisera det mesta av den processen. Systemet lar sig fran manuellt annoteratvideomaterial att inferera annoteringar for nytt material automatiskt, utan att kravaandringar pa systemet mellan olika anvandarskapta koncept att annotera. Prototypen somar presenterad i denna uppsats och utvarderad pa ett antal koncept visar lovande resultatfor koncept som har hogt inytande pa scenmiljoerna.
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Dias, Pedro Ricardo Gomes. "Recommending media content based on machine learning methods." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/6581.
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Dissertação para obtenção do Grau de Mestre em
Engenharia InformáticaInformation is nowadays made available and consumed faster than ever before. This information technology generation has access to a tremendous deal of data and is left with the heavy burden of choosing what is relevant. With the increasing growth of media sources, the amount of content made available to users has become overwhelming and in need to be managed. Recommender systems emerged with the purpose of providing personalized and meaningful content recommendations based on users’ preferences and usage history. Due to their utility and commercial potential, recommender systems integrate many audiovisual content providers and represent one of their most important and valuable services. The goal of this thesis is to develop a recommender system based on matrix factorization methods, capable of providing meaningful and personalized product recommendations to individual users and groups of users, by taking into account users’ rating patterns and biased tendencies, as well as their fluctuations throughout time.
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Lorenz, Anja, and Lars Fassmann. "Lernmaterialien effektiv aufbereiten und wiederverwenden." Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-82101.
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Hochwertige Schulungsmaterialien für die unternehmensinterne Weiterbildung sind ein erster wichtiger Schritt hin zu einem effektiven Wissensmanagement. Einmal erstellt, können digitale Lerninhalte immer wieder eingesetzt werden. Allerdings ist die Pflege und Anpassung an die Anforderungen verschiedener Zielgruppen und Auslieferungsformate mit herkömmlicher E-Learning-Autorensoftware sehr aufwändig. Nicht so bei serverbasierter Software – sie ermöglicht die Planung, Erstellung, Auslieferung, Verwaltung und Pflege wiederverwendbarer digitaler Lernmaterialien. Dies ist der Ausgangspunkt für eine Vielzahl individueller Weiterbildungsangebote – ohne erneuten Aufwand für die Erstellung der Lerninhalte.
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Müller, Lars [Verfasser], and W. [Akademischer Betreuer] Stork. "From Context to Content: Designing Sensor Support for Reflective Learning / Lars Müller. Betreuer: W. Stork." Karlsruhe : KIT-Bibliothek, 2014. http://d-nb.info/1064504213/34.
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Drabløs, Lars Are Holth. "Computer Assisted Language Learning towards 2010 : Mobile Learning, User generated Content and Convergence." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9796.
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Many topics have been touched in this thesis. I would like to conclude with some answers to the questions raised in the initial problem description and point out further challenges in some cases. We have seen that there exist several approaches for CALL, with virtual learning communities as one example. The community presented here, moodle.org, is an open source framework and let any user register for free and manage a course. In that way may this framework be used by school institutions, professional language course providers and other users who feel free to organize a course. This environment is quite formal in nature, because most of the use at the portal is related to a registered course. Another portal, italki.com, offers language learning after the tandem method and users are free to search among all (visible) profiles on the sites to find a match. This is a more informal framework as the users are not connected to any established educational institution, they do not necessarily follow a curriculum and the learning is not instructed to follow any pedagogical principles. These portals may be accessed both in stationary and mobile environments (by mobile browsers). In the case of mobile environments there exist many challenges: Developers of the site are requested to take special considerations of how some material is to be structured to fit the interface at the users terminal. One of the considerations at moodle.org was for instance to limit graphical content (illustrated in chapter 5.2.1), as this takes up much space on the screen and uses quite a bit bandwidth to download. Other challenges can be related to media richness and context awareness discussed in chapter two. One example could for instance be a video conference lecture held at a moodle course. If some of the users are in a mobile environment without the possibility to transfer video (because of terminal or bandwidth limitation), they should still be given the option of following the lecture by audio transmission. This will reduce the richness of the lecture, but they will be able to catch up the most essential things. BBC offers another kind of framework which is typically meant for beginner learners in a language. The material in Language steps is instructional and interactive, as it requires response and apprehension from the users. This makes it most suitable for stationary environments, but the content could be presented in a mobile environment to. The 3 Rearranging the dialogue task will probably be suitable for a touch screen handheld. The content in the different modules could also be categorized to fit the current response flexibility of the user. An example of different categories was given in chapter 2. Another framework presented from the BBC portal was their show The Flatmates. This is an internet based soap show where the episodes can be followed by downloadable tracks or simply be read. The users may contribute to the show with discussion about the characters and give feedback about how the show should continue. This is a good example of how the Internet can be used as a platform for participation among users. There also exist mobile applications like KODIs dictionary and Coolgorillas audio phrase books. These can be categorized as referential tools and can be used in many settings, remarking that the audio phrase books in most cases are suited for beginners on vacation in the target language country. Chapter 6 discussed general possibilities and challenges related to technology and market trends. Web 2.0 was presented as the future trend of Internet usage and web design with key words as creativity, information sharing and collaboration between users (and companies). A survey, held by the Norwegian institute ITU has showed that Norwegian teenagers at average participate in 3,4 network societies. Facebook was the most popular. The biggest reason to participate in the networks was to meet friends. Only 8 percent answered that the networks provided help for school related topics. This shows that most of the interaction in these networks are informal among the teenagers. Could we still expect more participation in school related topics in such networks? The answer is yes, and no. The technology exists to promote school related subjects in these networks, but it would be a challenge to mix the pupils (and the teachers) roles in such a situation, as depicted in chapter 6.3. Hans Christian Arnseth also points out in [46] that the question about using more web 2.0 applications in the school system is much about ideology What do we regard as proper learning and how can/should technology be used in the education?. At last were some general challenges related to technology presented, with issues around convergence, human aspects, business models and policy as the main issues. Copyright policy and business models can be even more complicated in the evolution of web 2.0 interfaces, where content sharing and user participation goes hand in hand.
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Broman, Karolina. "Chemistry: content, context and choices : towards students' higher order problem solving in upper secondary school." Doctoral thesis, Umeå universitet, Institutionen för naturvetenskapernas och matematikens didaktik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-95956.
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Chemistry is often claimed to be difficult, irrelevant, and uninteresting to school students. Even students who enjoy doing science often have problems seeing themselves as being scientists. This thesis explores and challenges the negative perception of chemistry by investigating upper secondary students’ views on the subject. Based on students’ ideas for improving chemistry education to make the subject more interesting and meaningful, new learning approaches rooted in context-based learning (CBL) are presented. CBL approaches are applied in several countries to enhance interest, de-emphasise rote learning, and improve students’ higher order thinking. Students’ views on upper secondary school chemistry classes in combination with their problem- solving strategies and application of chemistry content knowledge when solving context-based chemistry tasks were investigated using a mixed methods approach. Questionnaire responses, written solutions to chemistry problems, classroom observations, and think-aloud interviews with upper secondary students at the Natural Science Programme and with experts working on context- based chemistry tasks were analysed to obtain a general overview and explore specific issues in detail. Several students were identified who had positive feelings about chemistry, found it interesting, and chose to continue with it beyond the compulsory level, mainly with the aim of future university studies or simply because they enjoyed it. Their suggestions for improving school chemistry by connecting it to everyday life prompted an exploration of CBL approaches. Studies on the cognitive learning outcomes arising from the students’ work on context-based tasks revealed that school chemistry heavily emphasises the recall of memorised facts. However, there is evidence of higher order thinking when students’ problem-solving processes are scaffolded using hints based on the Model of Hierarchical Complexity in Chemistry (MHC-C). In addition, the contextualisation of problems is identified as something that supports learning rather than distracting students. To conclude, the students in this thesis are interested in chemistry and enjoy chemistry education, and their motives for choosing to study chemistry at the post-compulsory level are related to their aspirations; students’ identity formation is important for their choices. Because students are accustomed to recalling facts and solving chemistry problems that have “one single correct answer”, they find more open problems that demand higher order thinking (e.g. knowledge transfer) unfamiliar and complex, suggesting that such processes should be practiced more often in school chemistry.Kemi är ett skolämne som generellt anses vara både svårt, irrelevant och ointressant för ungdomar. Trots att det ändå finns ungdomar som uppskattar naturvetenskap i allmänhet och kemi i synnerhet, har de ofta problem att se sig själva som naturvetare eller kemister. Denna avhandling undersöker och ifrågasätter den negativa bilden av kemiämnet genom att till en början studera gymnasieelevers syn på kemi. Med utgångspunkt från naturvetarelevers förslag för att förbättra kemiundervisningen och göra ämnet mer intressant och meningsfullt, anknyter avhandlingen därefter till kontextbaserad kemi. Kontextbaserade kurser används i flera länder för att öka elevernas intresse, minska fokuseringen på utantillkunskaper och utveckla elevernas mer avancerade tänkande; med andra ord med målet att uppnå ett meningsfullt lärande. Vid kontextbaserade angreppssätt utgår man från ett sammanhang (kontexten), ofta något personligt eller samhälleligt, som ska vara relevant och intressant. Från dessa kontexter koncentreras därefter undervisningen på de ämneskunskaper man behöver ha för att förstå sammanhanget (s.k. need-to-know). Syftet med avhandlingen är att undersöka naturvetarelevers syn på gymnasiekemin, både deras intresse för ämnet och deras skäl att välja det naturvetenskapliga programmet på gymnasiet, samt elevernas problemlösningsförmåga och användande av ämneskunskaper när de löser kontextbaserade kemiuppgifter. Skälet att studera naturvetarelever på gymnasiet är att dessa elever uppfattas som möjliga framtida naturvetare eftersom de själva har valt naturvetenskaplig inriktning efter den obligatoriska grundskolan. Med hjälp av olika metoder (enkäter, klassrums- observationer, skriftliga lösningar till kemiuppgifter och intervjuer med både elever och experter som löser kemiuppgifter) har analyser genomförts för att dels får en allmän överblick, dels för att utforska specifika delar i detalj både gällande kognitiva och affektiva aspekter av lärande. Resultaten visar att flertalet elever har en positiv inställning till kemi, många tycker att ämnet är intressant och har valt att fortsätta läsa kemi efter den obligatoriska grundskolan främst med målet att studera vidare på universitetsnivå, men också eftersom de specifikt uppskattar kemi. Gymnasieeleverna lyfter fram lärarna som viktiga och lärarstyrda kemilektioner anses positivt, speciellt om lärarna är strukturerade i sin undervisning. Ett vanligt skäl till att välja naturvetenskapsprogrammet är också att man aktivt väljer utbildning med utgångspunkt från vilken skola man vill gå på, något som i denna avhandling tolkas som ett identitetsskapande. Elevernas förslag för att förbättra skolkemin genom att anknyta kemin till vardagen låg till grund för avhandlingens fortsatta inriktning mot kontextbaserade angreppssätt. Analyser av elevernas kognitiva resultat när de löser kontextbaserade kemiuppgifter visar att dagens skolkemi tydligt fokuserar på att memorera faktakunskaper. Eleverna är vana att använda utantillkunskaper när de löser kemiuppgifter eftersom uppgifterna, enligt eleverna, efterfrågar ”det rätta svaret”. Däremot visar studierna också att ett mer avancerat tänkande kan uppnås när elevernas problemlösning stöds av hjälp och ledtrådar som baseras på ett specifikt ramverk, MHC-C (Model of Hierarchical Complexity in Chemistry). När det gäller ämneskunskaperna som krävs för att lösa de kontextbaserade kemiuppgifterna är vissa kemibegrepp viktiga tröskelbegrepp (sk. threshold concepts). Med hjälp av medvetenhet om tröskelbegrepp, som exempelvis polaritet och elektronegativitet för löslighetsuppgifter inom den organiska kemin, kan en större helhetsförståelse för övergripande begrepp (crosscutting disciplinary concepts) som förhållandet mellan kemiska ämnens struktur och egenskaper förhoppningsvis uppnås. När det gäller affektiva resultat anser eleverna att kontexterna i uppgifterna både var intressanta och relevanta, främst när en personlig anknytning var tydlig. Dessutom visade sig kontexterna i uppgifterna vara positiva för lärandet, inte en distraktionsfaktor. Sammanfattningsvis konstateras att svenska elever på naturvetenskaps- programmet är intresserade av kemi och uppskattar kemiundervisningen, speciellt om kemin knyts till vardagen och att lärarna har en tydlig struktur i sin undervisning. Elevernas skäl att välja fortsatta kemistudier efter den obligatoriska grundskolan kan knytas till deras utbildningssträvan men också att elevers identitetsskapande är viktigt för deras gymnasieval. Med hjälp av kontextbaserade angreppssätt kan kemiundervisningen göras mer intressant och relevant samtidigt som elevernas problemlösningsförmåga kan utvecklas. När eleverna möter mer öppna frågor som kräver förklaringar och resonemang är de ovana vid detta och uppfattar uppgifterna komplicerade, samtidigt som de uppskattar denna typ av uppgifter eftersom de uppfattas relevanta och intressanta. Slutsatsen blir att elevernas förmåga till problemlösning av öppna frågor som både kräver faktakunskaper men också förklaringar och resonemang måste tränas oftare inom ramen för skolans kemi för att utveckla elevernas meningsfulla lärande.
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Mosier, Angela Dawn. "Teachers' Challenges in Implementing Personalized Learning in Content Areas." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5908.
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Despite the national trend of assessments for gauging student mastery of prescribed curriculum standards which has placed assessment preparation at the forefront of classroom practices, teachers at a midwestern school promoting personalized learning for students, demonstrated inconsistency in implementation among content areas. An explanatory sequential mixed-methods study based on expectancy-value theory was used to define the challenges that arise as teachers implemented personalized learning in their content area. The research questions addressed the implementation of 5 personalized learning elements in secondary content areas, how teachers implement each element, and teachers' challenges in implementing personalized learning in their classroom. The quantitative research component utilized ANOVA and Tukey post hoc tests to analyze 182 secondary teacher responses to a strategic plan survey regarding the frequency at which personalized learning elements were used in instruction. Statistically significant differences were found for 3 elements: knowing your learners, student voice and choice, and technology integration. A maximum variation sample was used to select 8 participants from diverse content areas for the qualitative data collection. Emerging themes on personalized learning implementation were extracted from classroom observation and interview data using descriptive coding, and then validated through member checking. Results indicated that teachers seek more training on personalized learning elements, content area learning, and time to plan personalized instruction. If teachers' ability to deliver personalized learning in their content areas improved, students would receive higher quality instruction resulting in increased academic achievement.
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Wilson, Margaret. "The learning needs of dental hygienists, content and delivery." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ40144.pdf.
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Habgood, Matthew Peter Jacob. "The effective integration of digital games and learning content." Thesis, University of Nottingham, 2007. http://eprints.nottingham.ac.uk/10385/.
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This thesis is concerned with how the coveted user-engagement of digital games can be usefully harnessed for educational goals. Educational software has traditionally used gaming elements as a separate reward for completing learning content. The early "edutainment" sector became synonymous with this cursory "chocolate-covered broccoli" approach (Bruckman, 1999): tagging games on to learning content in order to make it more palatable. However, such methods have often proved ineffective (Kerawalla & Crook, 2005; Trushell, Burrell, & Maitland, 2001) and have been criticised for combining the worst elements of both games and education (Papert, 1998) as well as for following extrinsically motivating design models (Lepper, 1985; Parker & Lepper, 1992). This thesis provides a theoretical and empirical exploration of game designs that follow a more integrated approach. Five studies are described which detail the development and evaluation of a new theory for creating intrinsic integration based on integrating learning content with the game mechanics of a game. This includes the development of Zombie Division: a game that teaches mathematics to children through swordplay with skeletal opponents. Two experimental studies examine the motivational differences between integrated and non-integrated versions of Zombie Division by measuring time-on-task. Two more examine the educational effectiveness of integrated and non-integrated versions by measuring learning gains for a fixed amount of time-on-task. Statistically significant results are found which suggest that the integrated version is motivationally and educationally more effective than the extrinsic equivalent. Full results and implications are discussed.
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Govindarajan, Hariprasath. "Self-Supervised Representation Learning for Content Based Image Retrieval." Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166223.
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Automotive technologies and fully autonomous driving have seen a tremendous growth in recent times and have benefitted from extensive deep learning research. State-of-the-art deep learning methods are largely supervised and require labelled data for training. However, the annotation process for image data is time-consuming and costly in terms of human efforts. It is of interest to find informative samples for labelling by Content Based Image Retrieval (CBIR). Generally, a CBIR method takes a query image as input and returns a set of images that are semantically similar to the query image. The image retrieval is achieved by transforming images to feature representations in a latent space, where it is possible to reason about image similarity in terms of image content. In this thesis, a self-supervised method is developed to learn feature representations of road scenes images. The self-supervised method learns feature representations for images by adapting intermediate convolutional features from an existing deep Convolutional Neural Network (CNN). A contrastive approach based on Noise Contrastive Estimation (NCE) is used to train the feature learning model. For complex images like road scenes where mutiple image aspects can occur simultaneously, it is important to embed all the salient image aspects in the feature representation. To achieve this, the output feature representation is obtained as an ensemble of feature embeddings which are learned by focusing on different image aspects. An attention mechanism is incorporated to encourage each ensemble member to focus on different image aspects. For comparison, a self-supervised model without attention is considered and a simple dimensionality reduction approach using SVD is treated as the baseline. The methods are evaluated on nine different evaluation datasets using CBIR performance metrics. The datasets correspond to different image aspects and concern the images at different spatial levels - global, semi-global and local. The feature representations learned by self-supervised methods are shown to perform better than the SVD approach. Taking into account that no labelled data is required for training, learning representations for road scenes images using self-supervised methods appear to be a promising direction. Usage of multiple query images to emphasize a query intention is investigated and a clear improvement in CBIR performance is observed. It is inconclusive whether the addition of an attentive mechanism impacts CBIR performance. The attention method shows some positive signs based on qualitative analysis and also performs better than other methods for one of the evaluation datasets containing a local aspect. This method for learning feature representations is promising but requires further research involving more diverse and complex image aspects.
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Li, Shang-Wen Ph D. Massachusetts Institute of Technology. "Improving learning experience in MOOCs with educational content linking." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108989.
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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 153-163).
Since the first MOOC (Massive Open Online Course) in 2011, there have been over 4,000 MOOCs on various subjects on the Web, serving over 35 million learners. MOOCs have shown the ability to transcend time and space, democratize knowledge dissemination, and bring the best education in the world to every learner. However, the disparate distances between participants, the size of the learner population, and the heterogeneity of the learner backgrounds make it difficult for instructors to interact with learners in a timely manner, which adversely affects their learning outcome. To address these challenges, in this thesis, we propose a framework of educational content linking. By linking pieces of learning content scattered in the various course materials into an easily accessible structure, we hypothesize that this framework will guide learners and improve content navigation.
Since most instruction and knowledge acquisition in MOOCs takes place when learners are surveying course materials, better content navigation may help learners find supporting information to clear up confusion and improve the learning outcome. To support our conjecture, we present end-to-end studies to investigate our framework around two research questions. We first ask, does manually generated linking improve learning? To investigate this question, we choose two STEM courses, statistics and programming language, and demonstrate how the annotation of linking among course materials can be accomplished with collaboration between course staff and online workers. With this annotation, we implement an interface that can simultaneously present learning materials and visualize the linking among them. In a large-scale user study, we observe that this interface enables users to find desired course materials more efficiently, and retain more concepts more readily.
This result supports the notion that manual linking does indeed improve learning outcomes. Second, we ask, can learning content be generated using machine learning methods? For this question, we propose an automatic linking algorithm based on conditional random fields. We demonstrate that automatically generated linking can still lead to better learning, although the magnitude of the improvement over the unlinked interface is smaller. We conclude that the proposed linking framework can be implemented at scale with machine learning techniques.
by Shang-Wen Li.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Reyes, Elba Iris. "Classroom discourse communicative competency of bilingual students with learning disabilities during content learning in three learning environments." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186706.
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Using language as a tool to engage in social activity and mediate learning is a human experience. For some, that experience is limited as a result of language/learning problems or by experiences in environments that have not fostered language development. Language minority students who have learning disabilities are also challenged to create meaning in a language that is not native and that may be limited, particularly as it relates to academic learning. This study examined the influence of three learning environments on the communicative competencies of bilingual students with learning disabilities and the influence of those environments on the students' learning. Students were at least two years below expected grade level in reading. During the study, they used their grade level textbooks as they engaged in learning Social Studies content. Results indicate that dialogic, interactive learning environments influence the communicative competencies students demonstrate as well as their content learning.
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Hilmer, Günter. "Separation of educational and technical content in educational hypermedia." Göttingen Cuvillier, 2009. http://d-nb.info/1000421678/04.
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Saroop, Sahil. "Exploring Mediatoil Imagery: A Content-Based Approach." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35334.
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The future of Alberta’s bitumen sands, also known as “oil sands” or “tar sands,” and their place in Canada’s energy future has become a topic of much public debate. Within this debate, the print, television, and social media campaigns of those who both support and oppose developing the oil sands are particularly visible. As such, campaigns around the oil sands may be seen as influencing audience perceptions of the benefits and drawbacks of oil sands production. There is consequently a need to study the media materials of various tar sands stakeholders and explore how they differ. In this setting, it is essential to gather documents and identify content within images, which requires the use of an image retrieval technique such as a content-based image retrieval (CBIR) system. In a CBIR system, images are represented by low-level features (i.e. specific structures in the image such as points, edges, or objects), which are used to distinguish pictures from one another.
The oil sands domain has to date not been mapped using CBIR systems. The research thus focuses on creating an image retrieval system, namely Mediatoil-IR, for exploring documents related to the oil sands. Our aim is to evaluate various low-level representations of the images within this context. To this end, our experimental framework employs LAB color histogram (LAB) and speeded up robust features (SURF) in order to typify the imagery. We further use machine learning techniques to improve the quality of retrieval (in terms of both accuracy and speed). To achieve this aim, the extracted features from each image are encoded in the form of vectors and used as a training set for learning classification models to organize pictures into different categories. Different algorithms were considered such as Linear SVM, Quadratic SVM, Weighted KNN, Decision Trees, Bagging, and Boosting on trees. It was shown that Quadratic SVM algorithm trained on SURF features is a good approach for building CBIR, and is used in building Mediatoil-IR.
Finally, with the help of created CBIR, we were able to extract the similar documents and explore the different types of imagery used by different stakeholders. Our experimental evaluation shows that our Mediatoil-IR system is able to accurately explore the imagery used by different stakeholders.
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Lorenz, Anja, and Lars Fassmann. "Lernmaterialien effektiv aufbereiten und wiederverwenden." Büro für Medien Oliver Lehnert e.K, 2010. https://monarch.qucosa.de/id/qucosa%3A19645.
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Hochwertige Schulungsmaterialien für die unternehmensinterne Weiterbildung sind ein erster wichtiger Schritt hin zu einem effektiven Wissensmanagement. Einmal erstellt, können digitale Lerninhalte immer wieder eingesetzt werden. Allerdings ist die Pflege und Anpassung an die Anforderungen verschiedener Zielgruppen und Auslieferungsformate mit herkömmlicher E-Learning-Autorensoftware sehr aufwändig. Nicht so bei serverbasierter Software – sie ermöglicht die Planung, Erstellung, Auslieferung, Verwaltung und Pflege wiederverwendbarer digitaler Lernmaterialien. Dies ist der Ausgangspunkt für eine Vielzahl individueller Weiterbildungsangebote – ohne erneuten Aufwand für die Erstellung der Lerninhalte.
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Dimova, Svetoslava. "Foreign Language for Content: Aiming to Develop Lifelong Learning Dispositions." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/msit_diss/97.
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ABSTRACT
FOREIGN LANGUAGE FOR CONTENT: AIMING TO DEVELOP
LIFELONG LEARNING DISPOSITIONS
by
Svetoslava Dimova
In the context of emphasis on English language, mathematics and science within the American educational system (No Child Left Behind, 2001), foreign language education appears to be increasingly dissociated from educational priorities. Ways to create relevant goals and optimize the effects of foreign language teaching emerge through the use of communication technologies and connections to academic content.
This qualitative study explores the relationship between high school students’ skills in French as a foreign language (L2), their cognitive strategies during reading in L2 for academic content, and their motivation to read authentic French texts. The following questions guided the study: 1) How do students internalize the task of self-selected online reading in L2 for content understanding pertaining to their History of the Americas course? 2) What processes and skills do students evidence and draw upon to locate and read for information in L2?, and 3) What are the implications for building a theory of student motivations for extensive reading in L2 beyond the classroom context?
The study was realized in the setting of an International Baccalaureate (IB) program, where 4 key informants were selected, and analysis was presented in the form of 4 case studies. Informants’ French language proficiency ranged from intermediate-mid to advanced levels (ACTFL Guidelines, 1999). Data collection occurred during 8 weeks and included three rounds of formal, phenomenological interviews, classroom observations, and students’ learning journals. Data were analyzed through the lens of Activity theory (Engeström, 1999) and motivation theory (Keller, 2008) in order to determine emerging themes.
While both L2 skills and interest in historical content influenced the task completion, and informants used multiple strategies to search and read, internalization and motivation aspects related to acquiring content superseded those related to increasing language skills. Informants’ differences in attitudes toward the curriculum integrative task were additionally caused by their ideas of content appropriateness in a L2 course. Development of cultural awareness and critical thinking was also primarily shaped by interest in content. Findings from the analysis suggested further directions for L2 classroom instruction that could lead to developing students’ lifelong learning dispositions.
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Carrignon, Simon 1987. "Content-dependent biases in social learning strategies : a multiscale approach." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/668133.
Full textAbstract:
In this thesis, we have quantified the influence of content-dependent biases in social learning
strategies. Our theoretical framework combines agent-based models and Bayesian inference to measure content-dependent biases in large-scale social learning strategies. Our first empirical study measures the impact of social transmission biases in Twitter. The novelty of the second study is two-fold: ours is one of the rare uses of computational modelling in historical Roman Studies and one of the first tests of the impact of success bias across large spatial and temporal scales.
El contenido de lo que aprendemos socialmente moldea la evolución de la cultura humana. En esta tesis hemos cuantificado la influencia de diferentes estrategias de aprendizaje social analizando procesos culturales en diferentes escalas. Se propone un marco teórico que combina los modelos basados en agentes y la inferencia bayesiana para detectar sesgos dependientes de contenido en la evolución cultural. El análisis se realizará sobre tres escenarios diferentes: un escenario teórico, que revela el potencial del sesgo de éxito, y dos casos de estudio empirico que representan distintas escalas espacio-temporales. En el primer caso, se estudia la influencia de transmisión social dependiendo del contenido de diferentes clases de noticias online, mientras que en el segundo se analiza la influencia de los sesgos de éxito en los cambios de distribución de vajillas en el este del Imperio Romano.The content of what we learn shapes the evolution of human culture and society. In this thesis, we have quantified the influence of content-dependent biases in social learning strategies. Our theoretical framework combines agent-based models and Bayesian inference to measure content-dependent biases in large-scale social learning strategies. Our first empirical study measures the impact of social transmission biases in Twitter. The novelty of the second study is two-fold: ours is one of the rare uses of computational modelling in historical Roman Studies and one of the first tests of the impact of success bias across large spatial and temporal scales.
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Foo, Chia Mun. "Learning Requires Attention for Binding Affective Reinforcement to Information Content." Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/scripps_theses/555.
Full textAbstract:
Humans are limited in their capacity to process information about the environment; to choose the most salient details to process, we have to make rapid value appraisals and prioritize our attentional resources. In this proposed study, it is expected that attention is required to learn from affective information. Learning is measured by the difference between update (the difference between the first and second estimation) and the estimation error (the difference between the average likelihood and the first estimation). Using a belief-updating paradigm, participants will be asked to estimate their likelihood of encountering a negative event, once before and once after they receive the average likelihood information. By comparing the difference in estimations after being exposed to desirable or undesirable information and a positive or negative reinforcer across three levels of attentional load, the effects of attention on learning from affective reinforcement can be examined. It is proposed that attention mediates learning from affective information. This is demonstrated by the failure to learn differentially from affective information under high attentional load, while in a no load condition participants will learn differentially according to the type of news and affective reinforcer that they receive. The expected result would indicate that attention is a necessity for optimal learning outcomes, especially when learning from affective information. This has implications in the effectiveness of communicating affective information, such as in the health care field.
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Marks, Lori J., and Tina M. Hudson. "Peer Assisted Learning Strategies for Reading and Content Area Instruction." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/3672.
Full text
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Song, Yale. "Structured video content analysis : learning spatio-temporal and multimodal structures." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90003.
Full textAbstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 141-154).
Video data exhibits a variety of structures: pixels exhibit spatial structure, e.g., the same class of objects share certain shapes and/or colors in image; sequences of frames exhibit temporal structure, e.g., dynamic events such as jumping and running have a certain chronological order of frame occurrence; and when combined with audio and text, there is multimodal structure, e.g., human behavioral data shows correlation between audio (speech) and visual information (gesture). Identifying, formulating, and learning these structured patterns is a fundamental task in video content analysis. This thesis tackles two challenging problems in video content analysis - human action recognition and behavior understanding - and presents novel algorithms to solve each: one algorithm performs sequence classification by learning spatio-temporal structure of human action; another performs data fusion by learning multimodal structure of human behavior. The first algorithm, hierarchical sequence summarization, is a probabilistic graphical model that learns spatio-temporal structure of human action in a fine-to-coarse manner. It constructs a hierarchical representation of video by iteratively summarizing the video sequence, and uses the representation to learn spatio-temporal structure of human action, classifying sequences into action categories. We developed an efficient learning method to train our model, and show that its complexity grows only sublinearly with the depth of the hierarchy. The second algorithm focuses on data fusion - the task of combining information from multiple modalities in an effective way. Our approach is motivated by the observation that human behavioral data is modality-wise sparse, i.e., information from just a few modalities contain most information needed at any given time. We perform data fusion using structured sparsity, representing a multimodal signal as a sparse combination of multimodal basis vectors embedded in a hierarchical tree structure, learned directly from the data. The key novelty is in a mixed-norm formulation of regularized matrix factorization via structured sparsity. We show the effectiveness of our algorithms on two real-world application scenarios: recognizing aircraft handling signals used by the US Navy, and predicting people's impression about the personality of public figures from their multimodal behavior. We describe the whole procedure of the recognition pipeline, from the signal acquisition to processing, to the interpretation of the processed signals using our algorithms. Experimental results show that our algorithms outperform state-of-the-art methods on human action recognition and behavior understanding.
by Yale Song.
Ph. D.
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Wendeborn, Thomas, André Schneider, and Marios Karapanos. "Lernplattformen oder Content-Halden? Learning-Management-Systeme in der Schulpraxis." TUDpress, 2018. https://tud.qucosa.de/id/qucosa%3A33657.
Full text
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Curran, Maura K. "Language intervention for causal adverbial production and science content learning." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5742.
Full textAbstract:
Language serves as an essential resource to learn about cause and effect throughout childhood. Causal adverbial sentences use causal conjunctions (e.g., because, so) to join two clauses to express cause-effect relationships (Diessel & Hetterle, 2011). Causal adverbial sentences are frequently used to explain causal relationships in academic contexts, such as elementary school science and social studies classes (Kinzie et al., 2014; Williams et al., 2014). Children with specific language impairment (SLI) are at risk for failure in these academically relevant language skills. Here, a multiple probe design was used to examine the effect of language intervention focused on causal adverbials on both causal adverbials and acquisition of academic content for preschool/kindergarten children with SLI. Child performance on sentence elicitation probes of causal adverbials and an untreated control structure were analyzed. Six of seven participants exhibited gains at some level in production of causal adverbials containing because. Performance on daily probes of science content learning, and science unit tests indicate that participants are able to learn science content, but the magnitude of gains may not relate to skill in causal adverbial production. Language intervention for young children with SLI can effectively treat complex syntactic targets such as causal adverbials in the context of science instruction, but it is unclear whether this can affect science content learning.
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Likarish, Peter F. "Early detection of malicious web content with applied machine learning." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/4871.
Full textAbstract:
This thesis explores the use of applied machine learning techniques to augment traditional methods of identifying and preventing web-based attacks. Several factors complicate the identification of web-based attacks. The first is the scale of the web. The amount of data on the web and the heterogeneous nature of this data complicate efforts to distinguish between benign sites and attack sites. Second, an attacker may duplicate their attack at multiple, unexpected locations (multiple URLs spread across different domains) with ease. Third, attacks can be hosted nearly anonymously; there is little cost or risk associated with hosting or publishing a web-based attack. In combination, these factors lead one to conclude that, currently, the webs threat landscape is unfavorably tilted towards the attacker.
To counter these advantages this thesis describes our novel solutions to web se- curity problems. The common theme running through our work is the demonstration that we can detect attacks missed by other security tools as well as detecting attacks sooner than other security responses. To illustrate this, we describe the development of BayeShield, a browser-based tool capable of successfully identifying phishing at- tacks in the wild. Progressing from specific to a more general approach, we next focus on the detection of obfuscated scripts (one of the most commonly used tools in web-based attacks). Finally, we present TopSpector, a system we've designed to forecast malicious activity prior to it's occurrence. We demonstrate that by mining Top-Level DNS data we can produce a candidate set of domains that contains up to 65% of domains that will be blacklisted. Furthermore, on average TopSpector flags malicious domains 32 days before they are blacklisted, allowing the security community ample time to investigate these domains before they host malicious activity.
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Kinkade, Scott Edward. "A Content Analysis of Medical School Problem-Based Learning Cases." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984174/.
Full textAbstract:
Problem-based learning (PBL) was developed for use in medical education to incorporate more active, learner-centered instruction. Central to problem-based learning is the problem, which in medical education is usually case a case presentation, revealed in stages to allow learners to form and research learning objectives. The purpose of this study was to identify themes present across the PBL cases, including the patient-centeredness of the cases. Content analysis was used to examine 62 PBL cases that comprised the first and second years' core curriculum at a public medical school. The cases included a patient population similar to the local population, but care was more hospital-centric than would be expected from the actual patterns of medical utilization in the United States. Analyzing along two axes of patient-centeredness, the PBL cases demonstrated a good understanding of the patient (knowing the patient), but other qualities such as shared decision making was not as exemplified. Medical educators can use the results to understand elements that contribute to patient-centeredness and apply the analysis framework to evaluate future cases.
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Low, Marylin G. "Content-based language learning : an educational journey beyond language training." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/28423.
Full textAbstract:
Recent development in language teaching beyond the functional approach focusses on content-based language learning. This thesis reports on issues raised in the implementation and evaluation of a content-based curriculum designed for international students participating in a summer English language program. Data for evaluating the curriculum is qualitative and includes information from interviews and questionnaires completed by instructors involved in teaching on the program. Instructors' concerns of content-based language teaching focus primarily on implementing this approach in the classroom and on the design of student tasks. Implementation strategies and priorities for the development of tasks in a content-based curriculum are identified. The conclusion deals with issues in content-based teaching at the implementation stage and at the task design level.Education, Faculty of
Language and Literacy Education (LLED), Department of
Graduate
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Lin, Hong-Xin, and 林弘信. "Context-Sensitive Content Representation for Mobile Learning." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/39648464375311360327.
Full textAbstract:
碩士東海大學
資訊工程與科學系
93
Mobile learning means that the learning contents can be displayed anytime, anywhere, and with any kind of presenting device. Nowadays, Learning Content Management Systems (LCMSs) usually provide convenient authoring tools to help instructors to construct their learning contents, which may include static document such as powerpoint, word, pdf document and dynamic multimedia document such as video and audio files, and then integrate these learning contents to provide learners with proper contents rendering through access devices. However, most of LCMSs are based on desktop computer environments, rather than mobile devices. Context-Sensitivity is an application of software system’s ability to sense and analyze context from various sources. In this paper, we develop a Context-Sensitive Middleware (CSM) for LCMS to transform the same learning contents to different mobile devices, so mobile learning can be supported.
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Vause, Lyn. "Content and Context: Professional Learning Communities in Mathematics." Thesis, 2009. http://hdl.handle.net/1807/19136.
Full textAbstract:
Abstract:
This is a case study of a mathematics professional learning community. It illustrates the experience of eight Grade 2 teachers as they collaborate to improve their students'understanding of mathematics. In this inquiry, I worked as a participant-observer with the teachers over the course of five months as a witness to their expanding understanding of mathematics and learning. The case study describes two manifestations: the experiences of the teachers as they develop their knowledge of the mathematical learning of young children; and secondly, the teachers' growth as a professional learning community committed to improving the mathematical understanding of their students and of themselves.
Collectively, the findings from this study extend other conversations on both
professional learning communities and the development of teachers' knowledge about
mathematical learning (often called pedagogical content knowledge). This work shows that opportunities for professional learning that are self-directed, context and content specific, within a milieu that is collegial and supportive, enable teachers to bridge the elusive gap between theory and practice.
The specific questions addressed are as follows:
1. How does participation in a professional learning community affect teachers‘
iii pedagogical content knowledge and their understanding of students‘ learning of
mathematics?
2. How do primary teachers develop an effective mathematics professional learning community?
In mathematics, professional development often focuses on the creation of effective
lesson design. This study differed in some key ways. Although good lesson design was
valued and employed, the stimulus for teacher learning was the observation of the
students as they struggled with new complex concepts. From these observations, the
teachers became astute at recognizing particular consistencies and inconsistencies in the mathematical learning of the one hundred plus students they each observed within this project. Together, as a professional learning community, the teachers became adept at using external resources such as research and other resource materials to search the reasons and solutions for students‘ difficulty with mathematical concepts. Teachers' cognitive dissonance as they tried new instructional approaches and shared successes and
failures with their colleagues provided the foundation for their growth in pedagogical
content knowledge.
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Shepherd, Jaclyn Sandra. "Music content in state early learning guidelines: a content analysis." Thesis, 2015. https://hdl.handle.net/2144/15203.
Full textAbstract:
As a result of the Good Start, Grow Smart Initiative (GSGS) in 2002, states began developing Early Learning Guidelines (ELGs), which are utilized by state funded programs for children ages 3 to 5. Although GSGS recommended that states include literacy, language, and pre-reading skills in ELGs, many states developed more comprehensive documents that included broader ranges of skills and activities consistent with each state's conceptualization of what constitutes quality learning environments for this age group. Consequently, music content, if included in ELGs, may vary from state to state.
Three national standards documents may have informed music standards included in ELGs, such as The National Music Standards for Prekindergarten, Head Start Child Development and Early Learning Framework, and the National Association for the Education of Young Children (NAEYC) All-Criteria Document. I conducted a content analysis of state ELGs: 1) to determine what musical behaviors and activities states have codified as official knowledge within quality learning environments for young children, and 2) to ascertain the extent to which the musical content reflects music standards included in national prekindergarten standards documents. Findings indicated that the broadly-framed Head Start and NAEYC music indicators were well-represented in state ELGs. The majority of ELGs have addressed two of the Content Standards of The National Music Standards for Prekindergarten, "Singing and Playing Instruments" (88%) and "Responding to Music" (74%). The Content Standards "Creating Music" and "Understanding Music" were addressed in far fewer ELGs (27% and 33%, respectively). The more prescriptive Achievement Standards were less frequently included in ELGs. Additionally, 14.33% of all music-related indictors included in state ELGs did not reflect the music content of any of the national standards and guidelines; rather, the indicators represented additional music content (for example, audience skills), music activities that promote social and emotional development, and facilitating learning in other curriculum areas. When ELGs were examined through a conceptual framework of policy and Developmentally Appropriate Practice, a co-mingling of standards and guidelines constructs was found, suggesting that state ELG committees attempted to balance the opposing segments, resulting in re-contextualization of the content selected for inclusion in the ELGs.
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Tu, Kuo-Ming, and 杜國銘. "Designing Context Ontology and Context Acquisition for Ubiquitous Content Access in Web-Based Learning Environments." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/5xw4yj.
Full textAbstract:
碩士國立中央大學
網路學習科技研究所
94
Ubiquitous access enables context aware interactivity between learners and content in Web-based learning environments. We envision that the first step toward ubiquitous learning is to provide context aware learning content by finding right collaborative learners, right learning content and right learning services in the right place at the right time. The major contributions of this paper are the development of our context representation and context acquisition. We utilize ontology to formally describe contextual information pertaining to learners and learning content. Based on this ontology, we construct context acquisition mechanism for intelligent learning content discovery and access based on learners’ surrounding context.
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Ying-Wen, Huang. "Graph/Image Retrieval for e-Learning Content." 2005. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-0112200611300130.
Full text
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Huang, Yi-ming, and 黃亦銘. "Mobile Blogging System for Learning Content Management." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/25798471401357974779.
Full textAbstract:
碩士國立成功大學
工程科學系碩博士班
95
Over the years, due to the rapid developing in science and technology, many advances have been made in the area of multimedia learning contents development. In this paper, we employ a multi-agent technique to develop an M-learning system based on 3G Network, wireless and MANET. Following that, the proposed M-learning platform provides the efficient mobile learning environment via the application of Zone_Net which is based on Zone-based, Mobile Blog, information retrieval (IR) and RSS Aggregation. Moreover, by utilizing the Zone-Based scheme, the system offers properly learning contents to learners without bandwidth squandering. This paper offers a solution by designing a mobile blogging system combining web services to enable mobile blogging users to appreciate what you think is what you write. Further, we can receive different learners’ blog articles by the RSS aggration or the RSS reader. Also, IR techniques are applied to design the Mobile IR so that users can find the dependency between terms and articles exactly.
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Lin, Je-min, and 林哲民. "Computer-Supported Collaborative Learning Content Management System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/39198743280688292466.
Full textAbstract:
碩士大同大學
資訊工程學系(所)
100
In past decade, people spend more and more time on internet learning new knowledge. E-Learning has become one of the popular ways of learning. User can break the restriction on time and place and gain their knowledge free. （Computer-Supported Collaborative Learning, CSCL）is an interaction of messages technology among users to improve the knowledge sharing and distribution. Social network is also a tool to support the web service more collaborative in specific area. However, most of social network system put their key point on the web sight and management and they might be lack of supporting on detail contents. Due to the used mark language HTML which is focus on composing. The social network service provides reliable articles not automation processing for program. Machine can also use the information to calculate theory. This research builds a learning group management platform on Drupal. Tutor can design a management CSCL script. Users can learn collaboratively. Through this system, tutor can figure out the situation and estimate the effect on learning. By the semantic technology, the information not only presents the web pages but provides more complex calculation to implement theory.
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Wu, Bo-Han, and 吳柏漢. "Personalized Vocabulary Learning System with Web Content." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/42687332570406385559.
Full textAbstract:
碩士國立暨南國際大學
資訊工程學系
94
There are many materials for English learning on the Internet, such as text, video, audio and image. Sometimes if we meet some words that we don’t understand while reading an English page, we may consult an online dictionary. Nowadays online dictionary provides not only the meaning of the word, but also the pronunciation, example sentences, synonyms, antonyms, collocation, translation, and etc. But after consulting the online dictionary and know what the word means, we may easily forget the word if we don’t use them often. How to use these data and make users memorize them is an important topic. The result of this research is to design a useful tool to help user learning English vocabulary. This tool is combined with the Internet Explorer and can be used on almost all Web pages. We collect the resources from the Internet and integrate them to provide to the user. Our system also includes the WordNet to provide the words’ relations. The system also record users’ actions when they use this system. The record can be used to help users memorizing the words.
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Huang, Ying-Wen, and 黃盈文. "Graph/Image Retrieval for e-Learning Content." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/12274722991384350579.
Full textAbstract:
碩士元智大學
資訊工程學系
93
The goal of legend retrieval is to provide related information retrieval for the handed legend. Hence, it is necessary to retrieve the correct legend from database for the query legend. The processed legends can be properly divided into two categories: graph and image. The proposed method consists two phases: legend extract and legend retrieval. In the extraction stage, the legend images are first converted from RGB into YIQ color spaces to get Y values as gray-level images. The foreground is then separated from background for the legend image so as to get the characteristics of legend for later legend extraction and retrieval. Since each legend may not occupy the whole legend image, the region enclosing the legend only should be detected first to reduce processing time as well as increase retrieval accuracy. In the retrieval stage, features are extracted for each legend to proceed legend matching. The features used in our method include aspect ratio, number of legend components and spatial histograms of pixel number, border length and gray level. Finally, the strategy of type-based matching is adopted to evaluate the similarity between the query legend and each database legend using different similarity measures according to the type of the query legend. In this way, the correct legend can be retrieved which in turn facilitates the information retrieval for the legend.