Academic literature on the topic 'Electronic learning supports'
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Journal articles on the topic "Electronic learning supports"
Klement, Milan, and Jiří Dostál. "Evaluating Electronic Learning Supports." Procedia - Social and Behavioral Sciences 69 (December 2012): 907–14. http://dx.doi.org/10.1016/j.sbspro.2012.12.015.
Full textShamir, Adina, Ora Segal-Drori, and Ilana Goren. "Educational electronic book activity supports language retention among children at risk for learning disabilities." Education and Information Technologies 23, no. 3 (November 4, 2017): 1231–52. http://dx.doi.org/10.1007/s10639-017-9653-7.
Full textKumbár, Vojtěch, and Josef Filípek. "Students’ Preference of E-learning in Physical Subjects at Mendel University in Brno." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 63, no. 3 (2015): 775–80. http://dx.doi.org/10.11118/actaun201563030775.
Full textSukma, Trisya Afidah, Mundilarto Mundilarto, and Nadia Darma Putri. "Local wisdom-Based Electronic Book on Newton's Law." Jurnal Ilmiah Pendidikan Fisika Al-Biruni 8, no. 2 (October 30, 2019): 197–206. http://dx.doi.org/10.24042/jipfalbiruni.v0i0.4368.
Full textPan, Yongping, Chenguang Yang, Mahardhika Pratama, and Haoyong Yu. "Composite learning adaptive backstepping control using neural networks with compact supports." International Journal of Adaptive Control and Signal Processing 33, no. 12 (May 17, 2019): 1726–38. http://dx.doi.org/10.1002/acs.3002.
Full textAlsoud, Anas Ratib, and Ahmad Ali Harasis. "The Impact of COVID-19 Pandemic on Student’s E-Learning Experience in Jordan." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 5 (April 28, 2021): 1404–14. http://dx.doi.org/10.3390/jtaer16050079.
Full textHamzah, Imron, and Sriyani Mentari. "Development of Accounting E-Module to Support the Scientific Approach of Students Grade X Vocational High School." Journal of Accounting and Business Education 1, no. 1 (September 19, 2017): 78. http://dx.doi.org/10.26675/jabe.v1i1.9751.
Full textIshizu, Kenichi, Hiroshi Takemura, Kuniaki Kawabata, Hajime Asama, Taketoshi Mishima, and Hiroshi Mizoguchi. "Automatic Counting Robot Development Supporting Qualitative Asbestos Analysis -Asbestos, Air Bubbles, and Particles Classification Using Machine Learning-." Journal of Robotics and Mechatronics 22, no. 4 (August 20, 2010): 506–13. http://dx.doi.org/10.20965/jrm.2010.p0506.
Full textKurniawan, Rano, Henderi Henderi, and Fitria Nursetianingsih. "Penggunaan iPad Mendukung Pembelajaran pada Mahasiswa iLearning." CCIT Journal 6, no. 1 (September 10, 2012): 76–91. http://dx.doi.org/10.33050/ccit.v6i1.380.
Full textSorostinean, Radu, Arpad Gellert, and Bogdan-Constantin Pirvu. "Assembly Assistance System with Decision Trees and Ensemble Learning." Sensors 21, no. 11 (May 21, 2021): 3580. http://dx.doi.org/10.3390/s21113580.
Full textDissertations / Theses on the topic "Electronic learning supports"
Jury, Thomas W. "Electronic Performance Support for E-Learning Analysis and Design." NSUWorks, 2007. http://nsuworks.nova.edu/gscis_etd/621.
Full textHarris, Lisa, and Lisa Harris@rmit edu au. "Electronic Classroom, Electronic Community: Virtual Social Networks and Student Learning." RMIT University. Global Studies, Social Science and Planning, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080717.144715.
Full textNielsen, Niels Bech. "Using electronic voting systems data outside lectures to support learning." Connect to e-thesis. Move to record for print version, 2007. http://theses.gla.ac.uk/46/.
Full textMSc. (R) thesis submitted to the Department of Computing Science, Faculty of Information and Mathematical Sciences, University of Glasgow, 2007. Includes bibliographical references.
Sisarica, Anja. "Creativity support in games for motivated learning." Thesis, City University London, 2015. http://openaccess.city.ac.uk/14543/.
Full textNurjanah, Dade. "Awareness support for learning designers in collaborative authoring for adaptive learning." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/349328/.
Full textHalpern, Yonatan. "Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine." Thesis, New York University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10192124.
Full textMedical informatics plays an important role in precision medicine, delivering the right information to the right person, at the right time. With the introduction and widespread adoption of electronic medical records, in the United States and world-wide, there is now a tremendous amount of health data available for analysis.
Electronic record phenotyping refers to the task of determining, from an electronic medical record entry, a concise descriptor of the patient, comprising of their medical history, current problems, presentation, etc. In inferring such a phenotype descriptor from the record, a computer, in a sense, "understands'' the relevant parts of the record. These phenotypes can then be used in downstream applications such as cohort selection for retrospective studies, real-time clinical decision support, contextual displays, intelligent search, and precise alerting mechanisms.
We are faced with three main challenges:
First, the unstructured and incomplete nature of the data recorded in the electronic medical records requires special attention. Relevant information can be missing or written in an obscure way that the computer does not understand.
Second, the scale of the data makes it important to develop efficient methods at all steps of the machine learning pipeline, including data collection and labeling, model learning and inference.
Third, large parts of medicine are well understood by health professionals. How do we combine the expert knowledge of specialists with the statistical insights from the electronic medical record?
Probabilistic graphical models such as Bayesian networks provide a useful abstraction for quantifying uncertainty and describing complex dependencies in data. Although significant progress has been made over the last decade on approximate inference algorithms and structure learning from complete data, learning models with incomplete data remains one of machine learning’s most challenging problems. How can we model the effects of latent variables that are not directly observed?
The first part of the thesis presents two different structural conditions under which learning with latent variables is computationally tractable. The first is the "anchored'' condition, where every latent variable has at least one child that is not shared by any other parent. The second is the "singly-coupled'' condition, where every latent variable is connected to at least three children that satisfy conditional independence (possibly after transforming the data).
Variables that satisfy these conditions can be specified by an expert without requiring that the entire structure or its parameters be specified, allowing for effective use of human expertise and making room for statistical learning to do some of the heavy lifting. For both the anchored and singly-coupled conditions, practical algorithms are presented.
The second part of the thesis describes real-life applications using the anchored condition for electronic phenotyping. A human-in-the-loop learning system and a functioning emergency informatics system for real-time extraction of important clinical variables are described and evaluated.
The algorithms and discussion presented here were developed for the purpose of improving healthcare, but are much more widely applicable, dealing with the very basic questions of identifiability and learning models with latent variables - a problem that lies at the very heart of the natural and social sciences.
Latombe, Guillaume. "Fast incremental learning of stochastic context-free grammars in radar electronic support." Thèse, Montréal : École de technologie supérieure, 2006. http://proquest.umi.com/pqdweb?did=1251872141&sid=5&Fmt=2&clientId=46962&RQT=309&VName=PQD.
Full text"A thesis presented to the École de technologie supérieure in partial fulfillment of the thesis requirement for the degree of masters in automated manufacturing engineering". CaQMUQET Bibliogr.: f. [193]-199. Également disponible en version électronique. CaQMUQET
Liu, Shuangyan. "Intelligent support for group work in collaborative learning environments." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/46815/.
Full textHarrichunder, Rajen. "A learning support system for the Visual Simulation Environment." Master's thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-02022010-020139/.
Full textGouveia, Luis Manuel Borges. "A visualisation design for sharing knowledge : a virtual environment for collaborative learning support." Thesis, Lancaster University, 2001. http://eprints.lancs.ac.uk/11950/.
Full textBooks on the topic "Electronic learning supports"
Martinez-Ramon, Manuel. Support vector machines for antenna array processing and electromagnetics. [San Rafael, Calif.]: Morgan & Claypool Publishers, 2006.
Find full textBritish Library. Research and Development Department. and Library Information Technology Centre, eds. Copyright & course books: A study of policies, practices and attitudes regarding course readers and electronic publishing of learning support materials in higher education. (London): British Library Research and Development Department, 1995.
Find full textCentre, Library Information Technology, and British Library. Research and Development Department., eds. Copyright & course books: A study of policies, practices and attitudes regarding course readers and electronic publishing of learning support materials in higher education. London: British Library Research and Development Department, 1994.
Find full textDigital Knowledge Maps In Education Technologyenhanced Support For Teachers And Learners. Springer-Verlag New York Inc., 2013.
Find full textTrepulė, Elena, Airina Volungevičienė, Margarita Teresevičienė, Estela Daukšienė, Rasa Greenspon, Giedrė Tamoliūnė, Marius Šadauskas, and Gintarė Vaitonytė. Guidelines for open and online learning assessment and recognition with reference to the National and European qualification framework: micro-credentials as a proposal for tuning and transparency. Vytauto Didžiojo universitetas, 2021. http://dx.doi.org/10.7220/9786094674792.
Full text(Editor), Constantine Balanis, ed. Support Vector Machines for Antenna Array Processing and Electromagnetics (Synthesis Lectures on Computational Electromagnetics Lecture). Morgan & Claypool Publishers, 2007.
Find full textBook chapters on the topic "Electronic learning supports"
Celino, Adele, and Grazia Concilio. "Developing a Collaborative Learning Support System for a Natural Protected Area." In Knowledge Management in Electronic Government, 257–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24683-1_26.
Full textSchott, Franz. "Some Instructional Theory Driven Aspects of Electronic Technology Supported Distance/Distributed Learning." In Learning without Boundaries, 37–48. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1199-5_4.
Full textOjuroye, Olivia, and Adriana Wilde. "On the Feasibility of Using Electronic Textiles to Support Embodied Learning." In Perspectives on Wearable Enhanced Learning (WELL), 169–86. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-64301-4_8.
Full textBoonbrahm, Poonpong, Charlee Kaewrat, and Salin Boonbrahm. "Using Augmented Reality Interactive System to Support Digital Electronics Learning." In Learning and Collaboration Technologies. Technology in Education, 3–11. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58515-4_1.
Full textKlein, James D., and Frank Nguyen. "Comparing the Impact of Electronic Performance Support and Web-Based Training." In Multiple Perspectives on Problem Solving and Learning in the Digital Age, 229–41. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7612-3_15.
Full textTang, Yucheng, Riqiang Gao, Ho Hin Lee, Quinn Stanton Wells, Ashley Spann, James G. Terry, John J. Carr, Yuankai Huo, Shunxing Bao, and Bennett A. Landman. "Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records." In Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures, 13–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60946-7_2.
Full textYoo, Inwan, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, and Won-Ki Jeong. "ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features." In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 249–57. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67558-9_29.
Full textvan Sonsbeek, Tom, and Marcel Worring. "Towards Automated Diagnosis with Attentive Multi-modal Learning Using Electronic Health Records and Chest X-Rays." In Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures, 106–14. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60946-7_11.
Full textZhang, Rui, and Guozhen Liu. "Least Square Support Vector Machine for the Simultaneous Learning of a Function and Its Derivative." In Advanced Research on Electronic Commerce, Web Application, and Communication, 427–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20367-1_69.
Full textGil, Richard J., and Maria J. Martín-Bautista. "An Ontology-Learning Knowledge Support System to Keep e-Organization’s Knowledge Up-to-Date: A University Case Study." In Electronic Government and the Information Systems Perspective, 249–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22961-9_20.
Full textConference papers on the topic "Electronic learning supports"
Udoyen, Nsikan, and David W. Rosen. "Description Logic Representation of Finite Element Analysis Models for Automated Retrieval." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99451.
Full textTokuro Matsuo and Takayuki Fujimoto. "Electronic learning support system based on analogy reuse." In 2008 IEEE International Conference on Information Reuse and Integration. IEEE, 2008. http://dx.doi.org/10.1109/iri.2008.4583054.
Full textXiao-Dong Wang, Hao-Ran Zhang, and Chang-Jiang Zhang. "Signals recognition of electronic nose based on support vector machines." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1527528.
Full textLavrushina, Elena, Ruslan Bazhenov, Dmitry Luchanonov, Iuiiia Shtepa, Natalya Chalkina, and Natella Vashakidze. "MOODLE-BASED ELECTRONIC LEARNING AND TEACHING SUPPORT PACKS APPLICABLE IN BLENDED LEARNING." In 14th International Technology, Education and Development Conference. IATED, 2020. http://dx.doi.org/10.21125/inted.2020.1331.
Full textGül, İsmail, and Isin Erer. "Scanning strategy learning for electronic support receivers by robust principal component analysis." In Artificial Intelligence and Machine Learning in Defense Applications III, edited by Judith Dijk. SPIE, 2021. http://dx.doi.org/10.1117/12.2601109.
Full textSergeenkova, V., and E. Вalykina. "Experience in electronic support of academic subjects at the Department of Russian history of the Belarusian state University." In Historical research in the context of data science: Information resources, analytical methods and digital technologies. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1849.978-5-317-06529-4/462-468.
Full text"ELECTRONIC DOCUMENT CLASSIFICATION USING SUPPORT VECTOR MACHINE-AN APPLICATION FOR E-LEARNING." In The 1st International Workshop on Efficacy of E-Learning Systems. SciTePress - Science and and Technology Publications, 2005. http://dx.doi.org/10.5220/0002568401910198.
Full textClaude, Hadrien, Cyrille Enderli, Jean-Francois Grandin, and Olivier Pietquin. "Learning of scanning strategies for electronic support using predictive state representations." In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2015. http://dx.doi.org/10.1109/mlsp.2015.7324365.
Full textQureshi, S. "Learning in the network form: implications for electronic group support." In Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences. IEEE, 1996. http://dx.doi.org/10.1109/hicss.1996.493198.
Full textHarrer, Andreas, Sam Zeini, and Niels Pinkwart. "The effects of electronic communication support on presence learning scenarios." In th 2005 conference. Morristown, NJ, USA: Association for Computational Linguistics, 2005. http://dx.doi.org/10.3115/1149293.1149317.
Full textReports on the topic "Electronic learning supports"
Turanova, Larisa, and Andrey Styugin. Electronic course "PEDAGOGICAL SUPPORT OF PUPILS IN A DISTRIBUTED PROFORIENTATION CLASS IN THE CONDITIONS OF ELECTRONIC LEARNING". Science and Innovation Center Publishing House, November 2020. http://dx.doi.org/10.12731/pedagogical_support.
Full textBraslavskaya, Elena, and Tatyana Pavlova. English for IT-Specialists. SIB-Expertise, June 2021. http://dx.doi.org/10.12731/er0464.21062021.
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