Relevant bibliographies by topics / Learning objects

Academic literature on the topic 'Learning objects'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Learning objects"

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Dodani, Mahesh H. "The Dark Side of Object Learning: Learning Objects." Journal of Object Technology 1, no. 5 (2002): 37. http://dx.doi.org/10.5381/jot.2002.1.5.c3.

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Saleh, Mostafa S. "Building Interoperable Learning Objects Using Reduced Learning Object Metadata." E-Learning and Digital Media 2, no. 3 (September 2005): 299–313. http://dx.doi.org/10.2304/elea.2005.2.3.9.

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The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards to describe these objects in order to support interoperability. IEEE Learning Object Metadata (LOM) is the most dominant standard for describing learning objects, in which 76 different elements are used to describe the different aspects of e-learning. Nonetheless, it will still be time consuming to build these learning objects. This paper introduces a model for building Global Interoperable Learning Objects (GILO) for the e-learning community. This is achieved by using a reduced set of the LOM elements, and giving a unique global ID to the learning object. This will enable software agents to query these learning object repositories, to automatically deliver the required material to the e-learning consumer.
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Vetromille-Castro, Rafael, Anne Marie Moor, Gabriela Bohlmann Duarte, and Nairana Hoffmann Sedrez. "From Learning Objects to Language Learning Objects." International Journal of Computer-Assisted Language Learning and Teaching 3, no. 2 (April 2013): 82–96. http://dx.doi.org/10.4018/ijcallt.2013040105.

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Learning Objects (LOs) have increasingly become of interest to users and researchers of Information and Communication Technologies (Wiley, 2002; Gibson, 2002; Leffa, 2006). There are several definitions, an ample discussion and criticism in relation to what can be considered a LO. Leffa (2006) indicates the state of the art of LOs and points to the lack of theoretical support in the production of such resources. Therefore, since more attention has been paid to technological aspects than to pedagogical ones in the development of LOs, the authors consider it necessary to have a theoretical basis that supports the design of such objects and makes them congruent to the learning of foreign languages (FL) with an emphasis on communication. Hence, this paper proposes a definition of Language Learning Objects (LLOs) that attend to the principles of Communicative Language Teaching (Canale & Swain, 1980; Ellis, 1999, 2005; Paiva, 2009) and Pedagogical and Design Usability (Vetromille-Castro, 2003).
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Clarke, Alex, Philip J. Pell, Charan Ranganath, and Lorraine K. Tyler. "Learning Warps Object Representations in the Ventral Temporal Cortex." Journal of Cognitive Neuroscience 28, no. 7 (July 2016): 1010–23. http://dx.doi.org/10.1162/jocn_a_00951.

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The human ventral temporal cortex (VTC) plays a critical role in object recognition. Although it is well established that visual experience shapes VTC object representations, the impact of semantic and contextual learning is unclear. In this study, we tracked changes in representations of novel visual objects that emerged after learning meaningful information about each object. Over multiple training sessions, participants learned to associate semantic features (e.g., “made of wood,” “floats”) and spatial contextual associations (e.g., “found in gardens”) with novel objects. fMRI was used to examine VTC activity for objects before and after learning. Multivariate pattern similarity analyses revealed that, after learning, VTC activity patterns carried information about the learned contextual associations of the objects, such that objects with contextual associations exhibited higher pattern similarity after learning. Furthermore, these learning-induced increases in pattern information about contextual associations were correlated with reductions in pattern information about the object's visual features. In a second experiment, we validated that these contextual effects translated to real-life objects. Our findings demonstrate that visual object representations in VTC are shaped by the knowledge we have about objects and show that object representations can flexibly adapt as a consequence of learning with the changes related to the specific kind of newly acquired information.
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Dunning, Jeremy, Kellie Donoghue, Abtar Kaur, and David Daniels. "Re-Purposeable Learning Objects Based on Teaching and Learning Styles." International Journal of Wireless Networks and Broadband Technologies 2, no. 4 (October 2012): 1–11. http://dx.doi.org/10.4018/ijwnbt.2012100101.

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The interactive, multimedia learning object has become an important part of high quality online education. The cost of producing such learning objects can be prohibitive. Re-purposeable learning objects made with learning object templates allow instructors with little or no programming experience to produce highly interactive and immersive learning objects. These learning object templates are based on key styles of teaching and learning and can be used to create and customize new learning objects within those styles, without creating new source code. The templates allow instructors to create learning objects simply by inserting text, and media (images, movies, etc.) because they closely mimic specific teaching strategies.
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Markovic, Suzana. "E-learning objects: Knowledge objects." Bizinfo Blace 6, no. 1 (2015): 35–42. http://dx.doi.org/10.5937/bizinfo1501035m.

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Assis, Luciana, Ana Carolina Rodrigues, Alessandro Vivas, Cristiano Grijó Pitangui, Cristiano Maciel Silva, and Fabiano Azevedo Dorça. "Relationship Between Learning Styles and Learning Objects." International Journal of Distance Education Technologies 20, no. 1 (January 2022): 1–18. http://dx.doi.org/10.4018/ijdet.296698.

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The automation of learning object recommendation and learning styles detection processes has attracted the interest of many researchers. Some works consider Learning Styles to recommend Learning Objects. On the other hand, other works automatically detect Learning Styles, analyzing the behavior of students in Intelligent Tutorial Systems in relation to the use of Learning Objects. Taking into account that advances in this field of research have been constantly presented in recent years, this paper analyzes the results of works discovered through a Systematic Literature Review. The main objective was to discover and document the relationships between Learning Styles and Learning Objects considered by researchers, in order to provide accurate content recommendations. The results show inconsistencies in the process, indicating that more and more in-depth research is still needed to allow a more accurate understanding of how to consider Learning Styles in the Learning Object recommendation process.
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Plessis, Jacques Du, and Alex Koohang. "Securing learning in learning objects." International Journal of Innovation and Learning 4, no. 2 (2007): 197. http://dx.doi.org/10.1504/ijil.2007.011694.

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Abad, Cristina L. "Learning through creating learning objects." ACM SIGCSE Bulletin 40, no. 3 (August 25, 2008): 255–59. http://dx.doi.org/10.1145/1597849.1384340.

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Smith, Linda B. "Learning to Recognize Objects." Psychological Science 14, no. 3 (May 2003): 244–50. http://dx.doi.org/10.1111/1467-9280.03439.

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A theory of object recognition requires a theory of shape. Despite considerable empirical and theoretical research, however, a definition of object shape has proved elusive. Two experiments provide new insights by showing that children's object recognition changes dramatically during the period between 17 and 25 months. During this time, children develop the ability to recognize stylized three-dimensional caricatures of known and novel objects. This ability is linked to the number of object names in children's vocabularies, suggesting that category learning may be a driving force behind the developmental changes.
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Dissertations / Theses on the topic "Learning objects"

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SILVA, DIVA DE SOUZA E. "MODELING LEARNING OBJECTS COMPOSITION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8668@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
O desenvolvimento de conteúdos instrucionais utilizando as novas tecnologias de informação é um processo caro, demorado e complexo, que aponta para o estabelecimento de novas metodologias. É neste contexto que surge o conceito de Objeto de Aprendizagem (LO), cujo enfoque está em promover a reutilização do conteúdo. Entretanto, ao considerar o reuso de conteúdo, também se observa uma necessidade de seqüência - lo para formar conteúdos mais elaborados ou mais complexos. Nesta tese adota-se uma estratégia de representar LOs cada vez menores, representando separadamente conteúdo e prática, aqui denominados Objetos Componentes (OCs). Para a estruturação do conteúdo, adaptou-se uma proposta já existente e definiu-se um esquema conceitual adequado à representação de atividades (ou práticas) de aprendizagem. Com vista à composição dos OCs, foi igualmente definido um esquema conceitual envolvendo conteúdos e práticas. Assim, com base em um algoritmo de seqüenciamento de OCs, um professor pode compreender melhor a forma de implementar um objeto complexo, como uma aula ou um curso, reduzindo erros e eventuais omissões na implementação da solução. Este seqüenciamento deve seguir uma metodologia e deve ser especificado de modo não ambíguo. É neste contexto que também é apresentada uma linguagem para especificação de seqüências de objetos de aprendizagem, com uma sintaxe adequada à descrição das possíveis formas de seqüenciamento de LOs. Finalmente, descreve-se um estudo de caso ilustrando a utilização dos esquemas conceituais desenvolvidos, do algoritmo proposto e da linguagem de especificação de seqüências OCs.
The development of instructional content using new Information Technologies is an expensive, time-consuming and complex process that leads to the development of new methodologies. It was in this context that the concept of Learning Objects (LOs) was proposed as an approach that promotes content reuse. However, if content is expressed as small LOs, it is also necessary to sequence them in order to build more elaborated and complex content. In this thesis we adopt a strategy to represent smaller LOs, modeling not only content but also practice, called Component Objects (COs) herein. In order to structure content we adapted an existing proposal and defined a conceptual schema to structure learning practices (or activities). We also defined a conceptual schema for composing these COs. Then, based on these conceptual schemas it was possible to propose an algorithm for sequencing COs, which supports a teacher/professor to better control the implementation of a complex content such as a class or a course, thus reducing errors and eventual omissions in its implementation. The sequencing process must follow a methodology and must be specified in a nonambiguous way. It is in this context that we also present a specification language for sequences of LOs, with a syntax that is adequate to the description of the possible ways of sequencing LOs. Finally, we describe a case study that shows the conceptual schemas that were proposed and the use of the sequencing algorithm and the specification language.
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Rodríguez-Jiménez, Othoniel. "Hierarchical, adaptive learning objects /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3091962.

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Soto, Barra Claudia Naiomi. "Reconocimiento rápido de objetos usando objects proposals y deep learning." Tesis, Universidad de Chile, 2017. http://repositorio.uchile.cl/handle/2250/150337.

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Ingeniera Civil Eléctrica
El reconocimiento (o detección) de objetos es un área activa y en continua mejora de la visión computacional. Recientemente se han introducido distintas estrategias para mejorar el desempeño y disminuir los costos y el tiempo de detección. Entre estas, se encuentran la generación de Object Proposals (regiones en la imágen donde hay alta probabilidad de encontrar un objeto) para acelerar la etapa de localización, como respuesta al paradigma de ventana deslizante; el cada vez más popular uso de redes Deep Learning y, en particular, para la clasi cación y detección de imágenes, las redes convolucionales (CNN). Si bien existen diversos trabajos que utilizan ambas técnicas, todos ellos se centran en tener una buena performance en conocidas bases de datos y competencias en lugar de estudiar su comportamiento en problemas reales y el efecto que tiene la modi cación de arquitecturas de redes convencionales y la elección adecuada de un sistema de generación de proposals. En este trabajo de título, entonces, se tiene como objetivo principal el caracterizar métodos de generación de proposals para su uso en el reconocimiento de objetos con redes CNN, comparando el desempeño tanto de los proposals generados como del sistema completo en bases de datos fabricadas manualmente. Para estudiar el sistema completo, se comparan dos estructuras conocidas, llamadas R-CNN y Fast R-CNN, que utilizan de distintas formas ambas técnicas (generación de proposals y detección) y donde se considera en el estado del arte mejor Fast R-CNN. Se propone en este trabajo que esta hipótesis no es del todo cierta en el caso de que se trabaje con un número su cientemente bajo de proposals (donde las bases de datos acá construidas se enfocan en precisamente asegurar una cantidad baja de objetos de tamaños similares presentes en cada una: objetos sobre super cies y objetos de una sala de estar) y se acelere el proceso de clasi cación alterando el tamaño de entrada de la red convolucional utilizada. Se eligieron tres métodos de generación de Proposals de la literatura a partir de su desempe ño reportado, y fueron comparados en distintos escenarios sus tiempos de procesamiento, calidad de proposals generados (mediante análisis visual y numérico) en función del número generados de estos. El método llamado BING presenta una ventaja sustancial en términos del tiempo de procesamiento y tiene un desempeño competitivo medido con el recall (fracción de los objetos del ground truth correctamente detectados) para las aplicaciones escogidas. Para implementar R-CNN se entrenan dos redes del tipo SqueezeNet pero con entradas reducidas y seleccionando los 50 mejores proposals generados por BING se encuentra que para una red de entrada 64x64 se alcanza casi el mismo recall (~ 40%) que se obtiene con el Fast R-CNN original y con una mejor precisión, aunque es 5 veces más lento (0.75s versus 0.14s). El sistema R-CNN implementado en este trabajo, entonces, no sólo acelera entre 10 y 20 veces la etapa de generación de proposals en comparación a su implementación original, si no que el efecto de reducir la entrada de la red utilizada logra disminuir el tiempo de detección a uno que es sólo 5 veces más lento que Fast R-CNN cuando antes era hasta 100 veces más lento y con un desempeño equivalente.
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Reid, Sheri Lynn. "Search for hidden objects by pigeons: Place learning vs "object permanence"." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/9707.

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Mental representation of hidden objects by pigeons was tested for. Experiment 1 used a series of Piagetian tests of "object permanence" to measure pigeons' capacity to find a stationary food target behind a screen. Performance on these tests did not differ significantly from chance in spite of manipulations designed to enhance the motivational value of the hidden object. Experiment 2 used operant contingencies to test whether pigeons could mentally represent a moving dot on a computer monitor that temporarily "disappeared" behind a screen. Two target durations were used (12 and 24 seconds) for the dot to move across a computer screen. Pigeons were reinforced if their first keypeck occurred when the dot was hidden but not if it occurred when the dot was visible. Phase 1 consisted of target-12 trials, phase 2 consisted of target-24 trials, and phase 3 consisted of alternating sessions of target-12 and target-24 trials. Results demonstrate that while pigeons were able to use timing strategies to respond correctly with an unconstrained choice method, evidence for the use of mental representations by pigeons was inconclusive. Both experiments are discussed in terms of the mechanisms used by pigeons to find hidden objects.
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Alsubaei, Mutlag. "Creating a personalised learning environment using learning objects." Thesis, University of Salford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491030.

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A paradigm shift has occurred in the learning field with the emergence, advances and proliferation of the latest, rapid technologies coupled with improvements in the understanding of learning environments and advances in instructional design. This takes the traditional notions of learning and transports it into the modern world to forge new learning environments that offer substantial benefits over traditional learning environments. Part of this revolution is headed by the learning object paradigm. This research focuses on the development of a personalised learning environment using learning objects as the primary tool and the basis to facilitate the production of a fully robust system and environment that offer learners personalised learning and the benefits that such learning brings.
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VELLOSO, SUSANA ROSICH SOARES. "SQLLOMINING: FINDING LEARNING OBJECTS USING MACHINE LEARNING METHODS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=10970@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
Objetos de Aprendizagem ou Learning Objects (LOs) são porções de material didático tais como textos que podem ser reutilizados na composição de outros objetos maiores (aulas ou cursos). Um dos problemas da reutilização de LOs é descobri-los em seus contextos ou documentos texto originais tais como livros, e artigos. Visando a obtenção de LOs, este trabalho apresenta um processo que parte da extração, tratamento e carga de uma base de dados textual e em seguida, baseando-se em técnicas de aprendizado de máquina, uma combinação de EM (Expectation-Maximization) e um classificador Bayesiano, classifica-se os textos extraídos. Tal processo foi implementado em um sistema chamado SQLLOMining, que usa SQL como linguagem de programação e técnicas de mineração de texto na busca de LOs.
Learning Objects (LOs) are pieces of instructional material like traditional texts that can be reused in the composition of more complex objects like classes or courses. There are some difficulties in the process of LO reutilization. One of them is to find pieces of documents that can be used like LOs. In this work we present a process that, in search for LOs, starts by extracting, transforming and loading a text database and then continue clustering these texts, using a machine learning methods that combines EM (Expectation- Maximization) and a Bayesian classifier. We implemented that process in a system called SQLLOMining that uses the SQL language and text mining methods in the search for LOs.
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Liu, Yuanliang. "Design of learning objects to support constructivist learning environments." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4304.

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Thesis (M.S.)--University of Missouri-Columbia, 2005.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (December 13, 2006) Includes bibliographical references.
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Dagiene, Valentina, and Inga Zilinskiene. "Localization of Learning Objects in Mathematics." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-79623.

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Mathematics learning seems to be a demanding and time-consuming task for many learners. Information and communication technology (ICT) is an attractive tool of learning for students at any level and it can provide an effective atmosphere for understanding mathematics. The question is how to combine mathematics teaching contents, approaches, curricula, and syllabus with new media. The key issue in European educational policy (and other countries as well) is exchange and sharing digital learning resources (learning objects) among countries. In order to accumulate the practice of various countries and use the best digital resources created by different countries, it is necessary to localize learning objects (LO). The paper deals with some problems connected with localization of LO, developed for mathematics education, and presents some solution. Software localization is mainly referred to as language translation (e.g., translation of user interface texts and help documents). However, there are many other important elements depending on the country and people who will use the localized software. In this paper, the main attention is paid to localization of learning objects used for teaching and learning mathematics.
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Yin, Zheng. "Study of metadata for learning objects." Thesis, University of Ottawa (Canada), 2004. http://hdl.handle.net/10393/26819.

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Metadata is descriptive information for data. The purpose of metadata is to facilitate describing, managing and discovering resources in huge distributed repositories. Metadata experts worldwide create the Dublin Core (DC), which acts as a fundamental core metadata standard on which industrial metadata standards based. For educational industry, the need is increasing for description and exploration of a learning object (LO) in distributed learning object repositories (LOR) worldwide. Several organizations aim to establish metadata standards for facilitating better identifying, exchanging and reusing learning objects according to their specific needs. The Institute of Electrical and Electronics Engineers (IEEE) published Learning Object Metadata (LOM), which is a credited standard on the global level since it best represents the characteristics of digital learning objects. Conversion from one metadata standard to another is necessary in case that people want to exchange and reuse learning objects tagged using different kinds of metadata standards. Mapping between the DC and the LOM is an essential job in many e-learning systems. In this thesis, we present a new web based metadata editor for the DC and LOM, and a Web Services oriented mapping tool between them. Other clients can use our editor to create DC or LOM metadata records when catalog their learning objects into our LOR, and integrate the mapping web services as a part of different systems regardless of different platforms, protocols, and displaying devices. Our objective is to promote the reusability and interoperability for both the DC and the LOM users, therefore benefit the learning object industry by lowering the cost of using metadata. The DC-LOM mapping tool is demonstrated in our e-learning system called UbiLearn developed at the MCRLab of University of Ottawa.
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Kabel, Suzanna Catharina. "Knowledge-rich indexing of learning objects." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2004. http://dare.uva.nl/document/74617.

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Books on the topic "Learning objects"

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Davidson, Kim. Learning with objects. Aberdeen: Marischal Museum, University of Aberdden, 1994.

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Duval, Erik, Steffan Ternier, and F. van Assche. Learning objects in context. Chesapeake, VA: Association for the Advancement of Computing in Education, 2009.

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Frantiska, Jr., Ed.D., Joseph. Creating Reusable Learning Objects. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32889-8.

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Needham, Amy Work. Learning About Objects in Infancy. New York, NY : Routledge, 2016.: Routledge, 2016. http://dx.doi.org/10.4324/9781315628783.

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Durbin, Gail. Learning from objects: [a teacher's guide]. (London): English Heritage, 1996.

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Ghedia, Navneet, Chandresh Vithalani, Ashish M. Kothari, and Rohit M. Thanki. Moving Objects Detection Using Machine Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90910-9.

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Barritt, Chuck. Creating a Reusable Learning Objects Strategy. New York: John Wiley & Sons, Ltd., 2004.

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Malik, D. S. Java programming: Guided learning with early objects. Boston, Mass: Course Technology / Cengage Learning, 2009.

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Malik, D. S. Java programming: Guided learning with early objects. Boston, Mass: Course Technology / Cengage Learning, 2009.

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Malik, D. S. Java programming: Guided learning with early objects. Boston, Mass: Course Technology / Cengage Learning, 2009.

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Book chapters on the topic "Learning objects"

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Frantiska, Joseph. "Learning Objects." In Visualization Tools for Learning Environment Development, 37–49. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67440-7_6.

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Boyle, Tom, and Erik Duval. "Learning Objects." In Technology Enhanced Learning, 137–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-02600-8_13.

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Silveira, Ricardo, Eduardo Gomes, and Rosa Vicari. "Intelligent Learning Objects." In Information and Communication Technologies and Real-Life Learning, 103–10. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/0-387-25997-x_12.

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Lacasa, Pilar. "Intelligent Objects." In Learning in Real and Virtual Worlds, 53–69. New York: Palgrave Macmillan US, 2013. http://dx.doi.org/10.1057/9781137312051_3.

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Frantiska, Joseph J. "Types of Learning Objects." In Creating Reusable Learning Objects, 11–15. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32889-8_5.

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Fournier-Viger, Philippe, Mehdi Najjar, André Mayers, and Roger Nkambou. "From Black-Box Learning Objects to Glass-Box Learning Objects." In Intelligent Tutoring Systems, 258–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11774303_26.

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Silveira, Ricardo Azambuja, Eduardo Rodrugues Gomes, Vinicius Heidrich Pinto, and Rosa Maria Vicari. "Intelligent Learning Objects: An Agent Based Approach of Learning Objects." In Intelligent Tutoring Systems, 886–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30139-4_108.

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Frantiska, Joseph J. "Learning Object Design Standards." In Creating Reusable Learning Objects, 5–7. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32889-8_3.

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Berger, Arthur Asa. "Learning Games and Activities." In The Objects of Affection, 169–74. New York: Palgrave Macmillan US, 2010. http://dx.doi.org/10.1057/9780230109902_6.

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van Toll, Wouter, Arjan Egges, and Jeroen D. Fokker. "Organizing Game Objects." In Learning C# by Programming Games, 189–209. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-59252-6_10.

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Conference papers on the topic "Learning objects"

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Skovira, Robert, Alex Koohang, Frederick Kohun, and Richard Will. "Panel Discussion - From Informing Objects to Learning Objects." In InSITE 2009: Informing Science + IT Education Conference. Informing Science Institute, 2009. http://dx.doi.org/10.28945/3362.

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Harman & Koohang (2005) stated that a learning object “ .. is not merely a chunk of information packaged to be used in instructional settings. A learning object, therefore, can include anything that has pedagogical value - digital or non-digital such as a case study, a film, a simulation, an audio, a video, an animation, a graphic image, a map, a book, or a discussion board so long as the object can be contextualized by individual learners. The learner must be able to make meaningful connections between the learning object and his/her experiences or knowledge he/she previously mastered. “ The above definition asserts that a learning object must have “pedagogical value” and that a learning object is 1) anything digital or non-digital such as a film, a simulation, or a case study, and 2) the ability of the learner to contextualize the object, i.e., the learner is capable of making “meaningful connections” between the object and his/her previous experiences and/or knowledge. Once the contextualization occurs, the object will have “pedagogical value” and it no longer merely an object, it is a learning object. Can all objects be contextualized? Is it necessary for all objects to be contextualized? What shall one call an “object” that is retrieved (and may even have some value other than pedagogical value and/or use) from an open access or commercial learning objects repository labeled as a “learning object” with no pedagogical value? If these objects are not learning objects, but have some sort of value and use, how shall one refer to these objects? Perhaps “informing objects”?
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Thaysen, Peter. "An Approach to Building Learning Objects." In Sixth International Conference on Higher Education Advances. Valencia: Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/head20.2020.11070.

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Designing for online education can be a complex endeavor and the way to approach this must be carefully considered. This article examines the case of Danish educational institution SmartLearning to map out and analyze the approach to online courses. The study find that SmartLearning approaches the online courses by setting up guidelines for educators on how to build learnings objects. The approach is to use three different elements, one focused on the content and learning goals for a course, one focused on the layout of the leaning management system, and one focusing on which didactic principles to apply. These three elements must work together in the learning object in order to assure learning and motivation of learners. The study also find some structure regarding this process and based on the analysis it is recommended to bind the development of learning objects and courses together through instructional design tools. This will aid the further development of combining the three elements into quality learning objects.
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Behr, André, José Cascalho, Hélia Guerra, Ana Costa, Manuela Parente, Andrea Botelho, Rosa Vicari, and Armando Mendes. "Re-Mar: Repository of Marine Learning Objects." In Workshop de Computação Aplicada à Gestão do Meio Ambiente e Recursos Naturais. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/wcama.2021.15745.

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Current literature shows the lack of learning object repositories exclusively related to environmental education and that there is no predominant software. This paper presents Re-Mar, a marine learning object repository based on open source software. Re-Mar is a part of an effort to promote ocean literacy through educational content for students and teachers. The repository is supported by computational technologies to catalog and organize learning objects to retrieve and reuse. Our prototype shows that is possible to store, catalog, retrieve, and link learning objects to support environmental education and coping with learning objects lifecycle. This is the first step to future aggregation of linked data, ontologies, and artificial intelligence aspects.
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Mustaro, Pollyana, and Ismar Silveira. "Learning Objects: Adaptive Retrieval through Learning Styles." In InSITE 2006: Informing Science + IT Education Conference. Informing Science Institute, 2006. http://dx.doi.org/10.28945/3009.

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Nowadays, the amount of information grows in an exponential way, mainly because of technological advances in media. This scenario claims for the development of different skills in order to increase learning abilities, making them personal and customizable. Such factor is significant in a changing society, which implies in a range of mechanisms which would allow to identify, in a non-intrusive way, which learning style some specific student would prefer to perform in order to build knowledge from some learning object under a learning context. This requires defining some strategies in order to recognize adult learner’s learning styles for some specific learning context. This work is based on theoretical references of Felder, Kolb and Gardner, proposing the implementation of a metadata annotation to identificate prime learning styles that are present in specific learning objects. This classification constitutes a starting point to recover learning objects from a repository according to apprentice’s profile and experiences. As a result, the effectiveness of the use of learning objects will be improved.
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Mohan, Permanand. "Learning Object Repositories." In InSITE 2005: Informing Science + IT Education Conference. Informing Science Institute, 2005. http://dx.doi.org/10.28945/2908.

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In order to reuse learning objects created by others, they must be made available to potential users on the Web, and services must be provided to allow users to discover, obtain rights to, and use these learning objects in their own instructional scenarios. In the learning object economy, these services are typically provided by learning object repositories, which are collections of learning objects that are accessible to users via a network without prior knowledge of the structure of the collections. This chapter discusses the important role played by learning object repositories in the learning object economy. The success of the learning objects' approach depends on users worldwide (such as instructors, learners, and software agents) being able to access and search for learning objects in different repositories in a uniform manner. The first part of the chapter explains how this can be achieved using a standardized approach for accessing and describing learning objects in a repository. Standardized access and retrieval is facilitated by implementing a specification from the IMS known as the Digital Repositories Interoperability (DRI) specification, while standardized search and discovery is facilitated by implementing a metadata standard such as the IEEE Learning Object Metadata (LOM) standard, described earlier in the book. There are different architectural approaches and business models that can be employed when designing a learning object repository and these are discussed next in the chapter. Typical architectural choices include using a centralized repository based on the client/server approach versus using several local repositories connected in a peer-to-peer fashion. Typical choices for business models include using an online broker for advertising and receiving payment for learning objects versus making the learning objects freely available. The advantages and disadvantages of the different approaches and models are carefully examined, and concrete examples of research prototypes and real-world deployments are provided wherever appropriate.
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Mogharreban, Namdar, and Dave Guggenheim. "Regaining the ‘Object’ of Learning Objects." In InSITE 2009: Informing Science + IT Education Conference. Informing Science Institute, 2009. http://dx.doi.org/10.28945/3361.

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Learning objects were to bring a seismic shift to the field of computer-based instruction by introducing transportability and reusability. Supposedly outfitted with the concepts taken from object-oriented (OO) design, learning objects have long promised dramatic savings of time and money in course and curricula development. However, they have failed to deliver the return on investment that seems a natural extension of their existence, in large part because the conceptual mechanisms adopted by OO design for transportability and reusability are lacking in learning objects. Object-oriented software development, first discovered in the 1960s, had ushered in a new era of programmatic coding and design by the 1990s. Instead of thinking in terms of “verbs,” or the processes that act upon information, developers could directly conceive of “nouns,” or the objects that define the world around us, and provide these objects with real-world attributes. These transportable and reusable objects would then possess a library of ready-to-use actions that provide both a rich feature set as well as isolation for the user from implementation complexity. Software languages designed with support for such concepts as classes, methods, instantiation, overloading, overriding, inheritance, polymorphism, and encapsulation, achieved this tectonic shift in computer engineering and resulted in dramatic improvements in reliability, reusability, and cost.
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Alsubaie, Mutlag, and Mustafa Alshawi. "Reusable Objects: Learning Object Creation Cycle." In 2009 Second International Conference on Developments in eSystems Engineering (DESE). IEEE, 2009. http://dx.doi.org/10.1109/dese.2009.63.

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Mogharreban, Namdar, and David Guggenheim. "Reusability and Learning Objects: Problems and a Proposed Solution." In InSITE 2008: Informing Science + IT Education Conference. Informing Science Institute, 2008. http://dx.doi.org/10.28945/3256.

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Learning objects have long promised dramatic savings of time and money in course and curricula development, but they have failed to deliver the return on investment that seems a natural extension of their existence - reusability. Because a single hour of online instruction can take up to 300 hours to develop (Kapp 2003), reusability is the core value message offered by learning object promoters, from the earliest days to the present. Yet, after 12 years of successive evolution, learning objects are still primarily a collection of stand-alone modules that rarely interconnect outside of strictly controlled regimes, such as those imposed by corporate and military training guidelines. Among the contributing factors to this impediment are definition of learning object, size of a learning object and aesthetics of a learning object. In response to this shortcoming, we propose to introduce a new entity - the learning pod. Engineered for reusability, the learning pod incorporates several modules that bring current technology to create an experientially seamless interconnection between disparate learning objects. These modules communicate with one another to build a consistent unit of instruction that uses several learning objects depending on the requirements. Several technologies including semantic web, XSL/XML and CSS are utilized to achieve presentation cohesiveness.
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L. Martin, Stephen. "Historical and Philosophical Foundations of Learning Objects." In InSITE 2005: Informing Science + IT Education Conference. Informing Science Institute, 2005. http://dx.doi.org/10.28945/2913.

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Briefly the objective of this presentation is to provide an overview of the origin of the concept and term of learning object in instructional design within the context of standardized, sharable, computer-based operations. Secondly, the philosophical foundations will be discussed mainly in terms of the framework of the crucial distinction between learning objects as mere external knowledge objects and the process of self-reflective learning that is needed to make the use of learning objects truly successful. Both the historical and philosophical foundations of learning objects will be treated in terms of the relationship between learning objects and learning subjects. The latter includes both instructional designers in the historical and practical development of learning objects, and the audience for which learning objects are intended to help educate. Particularly, historical and philosophical foundations should recognize the dual trajectory towards producing standardized small curricular units and at the same time affecting, educating and even transforming learners.
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Box, Ilona. "Submission and Peer Review of Learning Objects Using a Community-Based Repository." In InSITE 2004: Informing Science + IT Education Conference. Informing Science Institute, 2004. http://dx.doi.org/10.28945/2835.

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A community-based learning object repository supports the sharing and collaboration of learning object development within discipline or topic area communities. The repository is built using an object-oriented method and implemented using JADE, an object-oriented technology platform. The repository is a software system aimed at improving the creation, collection, quality assurance, and ultimately the accessibility of learning objects. The initiatives regarding learning objects and the double blind review process for research publications are the two key influences on the learning object repository design. The repository is a significant advance on existing learning object technology as 1) it is built using an object-oriented method and platform including the database; typically learning object collections are stored in relational databases, and 2) it incorporates an automated submission and double blind peer review process before learning objects are made public. The use of the repository by the learning object creators, reviewers, moderators, administrators and educators will determine the success of the product.
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Reports on the topic "Learning objects"

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Fitzpatrick, Paul. Object Lesson: Discovering and Learning to Recognize Objects. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada434695.

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Fitzpatrick, Paul M., Giorgio Metta, Lorenzo Natale, Sajit Rao, and Giulio Sandini. Learning about Objects through Action - Initial Steps towards Artificial Cognition. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada434778.

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Kemp, Charles C. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada434730.

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Modlo, Yevhenii O., and Serhiy O. Semerikov. Xcos on Web як перспективний засіб навчання моделювання технічних об’єктів бакалаврів електромеханіки. [б. в.], August 2018. http://dx.doi.org/10.31812/0564/2454.

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Research goals: to identify the perspective learning simulation tool for Bachelors of Electromechanics. Research objectives: to prove the feasibility of using the simulation system Xcos on Web as a tool of forming of future Bachelors of Electromechanics competence in modeling of technical objects. Research object: the use of imitative simulation systems to learning the Bachelors of Electromechanics. Research subject: the use Xcos on Web in learning modeling of technical objects the Bachelors of Electromechanics. Research methods used: the analysis of existing software usage experience. Research results. The imitative simulation system Xcos on Web is a promising cloud-based learning tool for Bachelor’s of Electromechanics modeling of technical objects. The main conclusions and recommendations: 1. The use of simulation systems, such as Scilab Xcos, is a necessary part of Bachelor of Electromechanics professional training. 2. Cloud-based learning environment built on the integrative usage of mobile Internet devices promotes the forming of Bachelor’s of Electromechanics professional competencies. 3. Implementation the full Scilab Xcos functionality at Xcos on Web creates conditions for transition in Bachelor’s of Electromechanics learning the simulation of technical objects to the use of mobile Internet devices.
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Machmudov, M. N. Distance learning course «Methods for optimizing the structures and modes of operation of objects». OFERNIO, June 2021. http://dx.doi.org/10.12731/ofernio.2021.24866.

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Bragdon, Sophia, Vuong Truong, and Jay Clausen. Environmentally informed buried object recognition. Engineer Research and Development Center (U.S.), November 2022. http://dx.doi.org/10.21079/11681/45902.

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The ability to detect and classify buried objects using thermal infrared imaging is affected by the environmental conditions at the time of imaging, which leads to an inconsistent probability of detection. For example, periods of dense overcast or recent precipitation events result in the suppression of the soil temperature difference between the buried object and soil, thus preventing detection. This work introduces an environmentally informed framework to reduce the false alarm rate in the classification of regions of interest (ROIs) in thermal IR images containing buried objects. Using a dataset that consists of thermal images containing buried objects paired with the corresponding environmental and meteorological conditions, we employ a machine learning approach to determine which environmental conditions are the most impactful on the visibility of the buried objects. We find the key environmental conditions include incoming shortwave solar radiation, soil volumetric water content, and average air temperature. For each image, ROIs are computed using a computer vision approach and these ROIs are coupled with the most important environmental conditions to form the input for the classification algorithm. The environmentally informed classification algorithm produces a decision on whether the ROI contains a buried object by simultaneously learning on the ROIs with a classification neural network and on the environmental data using a tabular neural network. On a given set of ROIs, we have shown that the environmentally informed classification approach improves the detection of buried objects within the ROIs.
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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concept of modeling and technological integration of various organizational forms and teaching methods based on the concept of mobility. Within this approach, the leading learning tools of bachelors of electromechanics are mobile Internet devices (MID) – a multimedia mobile devices that provide wireless access to information and communication Internet services for collecting, organizing, storing, processing, transmitting, presenting all kinds of messages and data. The authors reveals the main possibilities of using MID in learning to ensure equal access to education, personalized learning, instant feedback and evaluating learning outcomes, mobile learning, productive use of time spent in classrooms, creating mobile learning communities, support situated learning, development of continuous seamless learning, ensuring the gap between formal and informal learning, minimize educational disruption in conflict and disaster areas, assist learners with disabilities, improve the quality of the communication and the management of institution, and maximize the cost-efficiency. Bachelor of electromechanics competency in modeling of technical objects is a personal and vocational ability, which includes a system of knowledge, skills, experience in learning and research activities on modeling mechatronic systems and a positive value attitude towards it; bachelor of electromechanics should be ready and able to use methods and software/hardware modeling tools for processes analyzes, systems synthesis, evaluating their reliability and effectiveness for solving practical problems in professional field. The competency structure of the bachelor of electromechanics in the modeling of technical objects is reflected in three groups of competencies: general scientific, general professional and specialized professional. The implementation of the technique of using MID in learning bachelors of electromechanics in modeling of technical objects is the appropriate methodic of using, the component of which is partial methods for using MID in the formation of the general scientific component of the bachelor of electromechanics competency in modeling of technical objects, are disclosed by example academic disciplines “Higher mathematics”, “Computers and programming”, “Engineering mechanics”, “Electrical machines”. The leading tools of formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects are augmented reality mobile tools (to visualize the objects’ structure and modeling results), mobile computer mathematical systems (universal tools used at all stages of modeling learning), cloud based spreadsheets (as modeling tools) and text editors (to make the program description of model), mobile computer-aided design systems (to create and view the physical properties of models of technical objects) and mobile communication tools (to organize a joint activity in modeling).
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Merzlykin, Olexandr, and Iryna Topolova. Developing of Key Competencies by Means of Augmented Reality in Science and Language Integrated Learning. [б. в.], May 2018. http://dx.doi.org/10.31812/123456789/2897.

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Using of new learning and IC technologies is necessary for effective learning of modern students. That is why it can be reasonable to introduce augmented reality and content-language integrated learning in educational process. Augmented reality helps create firm links between real and virtual objects. Content and language integrated learning provides immersion in an additional language and creates challenging group and personal tasks in language and non-language subjects. Using these technologies in complex provides social and ICT mobility and creates positive conditions for developing 9 of 10 key competencies. The paper deals with the features, problems and benefits of these technologies’ implementation in secondary schools.
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Clausen, Jay, Vuong Truong, Sophia Bragdon, Susan Frankenstein, Anna Wagner, Rosa Affleck, and Christopher Williams. Buried-object-detection improvements incorporating environmental phenomenology into signature physics. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45625.

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The ability to detect buried objects is critical for the Army. Therefore, this report summarizes the fourth year of an ongoing study to assess environ-mental phenomenological conditions affecting probability of detection and false alarm rates for buried-object detection using thermal infrared sensors. This study used several different approaches to identify the predominant environmental variables affecting object detection: (1) multilevel statistical modeling, (2) direct image analysis, (3) physics-based thermal modeling, and (4) application of machine learning (ML) techniques. In addition, this study developed an approach using a Canny edge methodology to identify regions of interest potentially harboring a target object. Finally, an ML method was developed to improve automatic target detection and recognition performance by accounting for environmental phenomenological conditions, improving performance by 50% over standard automatic target detection and recognition software.
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Bulatetska, Lesya V., Vitaliy V. Bulatetskyi, Tetyana O. Hryshanovych, Yulia S. Pavlenko, Tetyana I. Cheprasova, and Andrey V. Pikilnyak. Operation system features and cloud services for lecturer work. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4443.

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The work proposes a conception of setup and use of teacher’s or lecturer’s workspace using common software and hardware products. The research object is a system built by using operating system capabilities in conjunction with office suite and public cloud service, as a foundation for teacher’s digital workspace. Research is made on how to set up, scale, and operate such a system, by studying the experience of national and foreign scientists and teachers, and using our own experience in educational processes, and working with operating systems and cloud services. As a result, we got a system which is easy to set up, learn, and apply by teachers without significant experience working remote education systems, and could be used for initial learning of remote education principles. It could be used as an initial step before migrating to specialized remote education systems. In the future, the system itself could be improved by adding additional objects into the system and a higher integration level between objects and external subjects.
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