Letteratura scientifica selezionata sul tema "Online learning methods"
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Articoli di riviste sul tema "Online learning methods"
Tarasenko, M. "ONLINE LEARNING: INTERACTIVE METHODS". Pedagogy of the formation of a creative person in higher and secondary schools 2, n. 77 (2021): 49–53. http://dx.doi.org/10.32840/1992-5786.2021.77-2.9.
Testo completoTekin, Cem, e Mingyan Liu. "Online Learning Methods for Networking". Foundations and Trends® in Networking 8, n. 4 (2013): 281–409. http://dx.doi.org/10.1561/1300000050.
Testo completoSalmons, Janet. "Case methods for online learning". eLearn 2003, n. 6 (giugno 2003): 2. http://dx.doi.org/10.1145/863928.863932.
Testo completoPRASETYA, Prita, e Sekar Wulan PRASETYANINGTYAS. "LEARNING STATISTICAL METHODES WITH ONLINE ONLINE COURSE". ICCD 3, n. 1 (27 ottobre 2021): 312–15. http://dx.doi.org/10.33068/iccd.vol3.iss1.368.
Testo completoVilkhovchenko, Nadiia P. "ESP distance learning methods At technical universities". Bulletin of Alfred Nobel University Series "Pedagogy and Psychology» 1, n. 23 (giugno 2022): 116–23. http://dx.doi.org/10.32342/2522-4115-2022-1-23-14.
Testo completoRini, Hesty Prima, e Dewi Khrisna Sawitri. "Effectiveness of Online Learning: The Learning Methods and Media". Ilomata International Journal of Social Science 3, n. 1 (10 febbraio 2022): 330–39. http://dx.doi.org/10.52728/ijss.v3i1.389.
Testo completoTîrziu, Andreea-Maria, e Cătălin I. Vrabie. "NET Generation. Thinking outside the box by using online learning methods". New Trends and Issues Proceedings on Humanities and Social Sciences 2, n. 7 (27 gennaio 2016): 41–47. http://dx.doi.org/10.18844/gjhss.v2i7.1178.
Testo completoSampe, Maria Zefanya, e Syafrudi Syafrudi. "ONLINE MATHEMATICS LEARNING STRATEGY APPROACH: TEACHING METHODS AND LEARNING ASSESSMENT". Jurnal Pendidikan Matematika (JUPITEK) 7, n. 1 (7 luglio 2024): 42–55. http://dx.doi.org/10.30598/jupitekvol7iss1pp42-55.
Testo completoLoi, Chek Kim, Jason Miin Hwa Lim, Norazah Mohd Suki e Hock Ann Lee. "Exploring University Students’ Online Learning Readiness: A Mixed Methods Study of Forced Online Learning". Journal of Language and Education 10, n. 1 (30 marzo 2024): 49–67. http://dx.doi.org/10.17323/jle.2024.16016.
Testo completoNF, Jhoanita, e Siti Khadijah. "PARENTS’ PERCEPTIONS OF ONLINE LEARNING METHODS: A QUANTITATIVE STUDY". Makna: Jurnal Kajian Komunikasi, Bahasa, dan Budaya 10, n. 1 (9 marzo 2022): 21–30. http://dx.doi.org/10.33558/makna.v10i1.3242.
Testo completoTesi sul tema "Online learning methods"
Qin, Lei. "Online machine learning methods for visual tracking". Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0017/document.
Testo completoWe study the challenging problem of tracking an arbitrary object in video sequences with no prior knowledge other than a template annotated in the first frame. To tackle this problem, we build a robust tracking system consisting of the following components. First, for image region representation, we propose some improvements to the region covariance descriptor. Characteristics of a specific object are taken into consideration, before constructing the covariance descriptor. Second, for building the object appearance model, we propose to combine the merits of both generative models and discriminative models by organizing them in a detection cascade. Specifically, generative models are deployed in the early layers for eliminating most easy candidates whereas discriminative models are in the later layers for distinguishing the object from a few similar "distracters". The Partial Least Squares Discriminant Analysis (PLS-DA) is employed for building the discriminative object appearance models. Third, for updating the generative models, we propose a weakly-supervised model updating method, which is based on cluster analysis using the mean-shift gradient density estimation procedure. Fourth, a novel online PLS-DA learning algorithm is developed for incrementally updating the discriminative models. The final tracking system that integrates all these building blocks exhibits good robustness for most challenges in visual tracking. Comparing results conducted in challenging video sequences showed that the proposed tracking system performs favorably with respect to a number of state-of-the-art methods
Kovanovic, Vitomir. "Assessing cognitive presence using automated learning analytics methods". Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28759.
Testo completoJohnson, Alicia Leinaala. "Exploration of Factors Affecting the Self-Efficacy of Asynchronous Online Learners: a Mixed Methods Study". Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/77518.
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Conesa, Gago Agustin. "Methods to combine predictions from ensemble learning in multivariate forecasting". Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-103600.
Testo completoHäglund, Emil. "Estimating Prediction Intervals with Machine Learning and Monte Carlo Methods in Online Advertising". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-282826.
Testo completoReklam på nätet är en komplex miljö. Mängden hemsidor, plattformar och format såväl som trenden med programmatiska reklamköp gör det svårt att utvärdera planerad reklam beträffande förväntad kostnad och värde. Den här rapporten använder maskininlärning för att prediktera kostnaden för tusen visningar (CPM), ett mått på annonseringseffektivitet, för ett planerat reklamköp. Random forest och neurala nätverksmodeller jämfördes med avseende på deras förmåga att producera punktskattningar och prediktionsintervall. För att skatta prediktionsintervall för neurala nätverk användes Monte Carlo dropout och skattning av datamängdens brusnivå. För random forest användes en Monte Carlo metod där ett stort antal modeller parametriseras med bootstrapping. Implementerade algoritmer jämfördes med 5x2cv test. Random forest och neural nätverksmodellerna producerade liknande precision för punktskattningar. För att erhålla giltiga prediktionsintervall avseende täckningssannolikhet för random forest krävdes det att parametrar justerades för att öka de enskilda beslutsträdens varians. Detta påverkade precisionen för punktskattningar negativt och prediktionsintervallen för random forest var mindre optimala än de som skattades av neurala nätverksalgoritmen. Denna skillnad i förmåga att skatta prediktionsintervall bekräftades statistiskt av 5x2cv testet.
Wright, Robert Demmon. "Students' Attitudes Towards Rapport-building Traits and Practices in Online Learning Environments". Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc177265/.
Testo completoLuca, Joseph. "Developing generic skills for tertiary students in an online learning environment". Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2002. https://ro.ecu.edu.au/theses/713.
Testo completoCunningham, E. Ann. "Comparison of Student Success by Course Delivery Methods at an Eastern Tennessee Community College". Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2585.
Testo completoJoshi, Apoorva. "Trajectory-based methods to predict user churn in online health communities". Thesis, University of Iowa, 2018. https://ir.uiowa.edu/etd/6152.
Testo completoTunningley, Joan M. "Self-Regulated Learning and Reflective Journaling in an Online Interprofessional Course: A Mixed Methods Study". University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511799445626182.
Testo completoLibri sul tema "Online learning methods"
plc, Epic Group, a cura di. Methods: A practical guide to the methods used in online learning. Brighton: Epic Group, 1999.
Cerca il testo completoA, Fisher Cheryl, e Rietschel Matthew J, a cura di. Developing online learning environments in nursing education. 3a ed. New York, NY: Springer, 2014.
Cerca il testo completo1966-, Lindberg J. Ola, e Olofsson Anders D. 1973-, a cura di. Online learning communities and teacher professional development: Methods for improved education delivery. Hershey, PA: Information Science Reference, 2010.
Cerca il testo completo1966-, Lambropoulos Niki, e Romero Margarido 1980-, a cura di. Educational social software for context-aware learning: Collaborative methods and human interaction. Hershey, PA: Information Science Reference, 2010.
Cerca il testo completo1966-, Lambropoulos Niki, e Romero Margarido 1980-, a cura di. Educational social software for context-aware learning: Collaborative methods and human interaction. Hershey, PA: Information Science Reference, 2010.
Cerca il testo completo1966-, Lambropoulos Niki, e Romero Margarido 1980-, a cura di. Educational social software for context-aware learning: Collaborative methods and human interaction. Hershey, PA: Information Science Reference, 2010.
Cerca il testo completoLoke, Jennifer C. F. Critical discourse analysis of interprofessional online learning in health care education. Hauppauge, N.Y: Nova Science Publishers, 2011.
Cerca il testo completoConceição, Simone C. O., 1963-, a cura di. Motivating and retaining online students: Research-based strategies that work. San Francisco, CA: Jossey-Bass, a Wiley brand, 2014.
Cerca il testo completoTekin e Mingyan Liu. Online Learning Methods for Networking. Now Publishers, 2015.
Cerca il testo completoLOK, Johnny Ch. Advantages Comparision Between Classroom and Online Learning Methods. Independently Published, 2020.
Cerca il testo completoCapitoli di libri sul tema "Online learning methods"
Bartz-Beielstein, Thomas. "Special Requirements for Online Machine Learning Methods". In Online Machine Learning, 63–69. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-7007-0_6.
Testo completoConceição, Simone C. O., e Susan M. Yelich Biniecki. "Closed and Open Online Discussion Forums". In Methods for Facilitating Adult Learning, 316–32. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003446019-25.
Testo completoMittelman, Rachel J. "Overcoming Resistance to Teaching History Online and Methods of Engagement". In Teaching and Learning History Online, 7–14. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003258414-3.
Testo completoGunawardena, Charlotte Nirmalani, Nick V. Flor e Damien M. Sánchez. "Social Construction of Knowledge (SCK) Platforms, Scraping, and Methods". In Knowledge Co-Construction in Online Learning, 70–77. New York: Routledge, 2025. https://doi.org/10.4324/9781003324461-7.
Testo completoRay, Asmita, Vishal Goyal e Samir Kumar Bandyopadhyay. "Student Stress Detection in Online Learning During Outbreak". In Computational Methods in Psychiatry, 259–81. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6637-0_13.
Testo completoGunawardena, Charlotte Nirmalani, Nick V. Flor e Damien M. Sánchez. "Social Learning Analytic Methods (SLAM) for Examining Online Social Dynamics". In Knowledge Co-Construction in Online Learning, 57–69. New York: Routledge, 2025. https://doi.org/10.4324/9781003324461-6.
Testo completoPark, Sunyoung, Boreum (Jenny) Ju e Shinhee Jeong. "Adopting Massive Open Online Courses (MOOCs) in Adult Learning Contexts". In Methods for Facilitating Adult Learning, 333–49. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003446019-26.
Testo completoSiska, Jumiati, Meydia Afrina, Sudarwan Danim e Agus Susanta. "The Effectiveness of Demonstrative Learning Methods in Improving Students’ Learning Outcomes". In Online Conference of Education Research International (OCERI 2023), 319–25. Paris: Atlantis Press SARL, 2023. http://dx.doi.org/10.2991/978-2-38476-108-1_31.
Testo completoKatiyar, Kalpana, Hera Fatma e Simran Singh. "Student’s Stress Detection in Online Learning During the Outbreak". In Computational Methods in Psychiatry, 335–48. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6637-0_16.
Testo completoOiwa, Hidekazu, Shin Matsushima e Hiroshi Nakagawa. "Frequency-Aware Truncated Methods for Sparse Online Learning". In Machine Learning and Knowledge Discovery in Databases, 533–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23783-6_34.
Testo completoAtti di convegni sul tema "Online learning methods"
Atia, Hend Abdelbakey, Magdy Aboul-Ela, Christina Albert Reyad e Nancy Awadallah Awad. "Online Payments Fraud Detection Using Machine Learning Techniques". In 2024 Intelligent Methods, Systems, and Applications (IMSA), 402–9. IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652834.
Testo completoZhang, Hao, Liang Huang, Kai Zhao e Ryan McDonald. "Online Learning for Inexact Hypergraph Search". In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 908–13. Stroudsburg, PA, USA: Association for Computational Linguistics, 2013. http://dx.doi.org/10.18653/v1/d13-1093.
Testo completoJung, Hoin, e Xiaoqian Wang. "Fairness-Aware Online Positive-Unlabeled Learning". In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track, 170–85. Stroudsburg, PA, USA: Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-industry.14.
Testo completoShdefat, Ahmed Younes, Mennatallah Mohamed, Shahd Khaled, Farrah Hany, Hanaa Fathi e Diaa Salama AbdElminaam. "Comparative Analysis of Machine Learning Models in Online Payment Fraud Prediction". In 2024 Intelligent Methods, Systems, and Applications (IMSA), 243–50. IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652861.
Testo completoDe Silva, D. I., e K. S. N. Athukorala. "Advancing Online Education: An Interactive Framework for Aligning Teaching Methods with Learning Styles". In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 1–7. IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910891.
Testo completoHillier, Michael, Florian Wellmann, Boyan Brodaric, Eric de Kemp e Ernst Schetselaar. "MACHINE LEARNING METHODS FOR 3D GEOLOGICAL MODEL CONSTRUCTION". In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-355922.
Testo completoSaenal, Selfiana, Syakhruni Syakhruni e Muh Kurniawan Adi Kusuma Wiharja. "Online Learning Methods for Learning Dance at School". In 1st World Conference on Social and Humanities Research (W-SHARE 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220402.056.
Testo completoLu, Lyujian, Hua Wang, Hua Wang, Yaoguo Li, Yaoguo Li, Thomas Monecke, Thomas Monecke, Hoon Seo e Hoon Seo. "PREDICTING 3D GEOSPATIAL DATA USING MACHINE LEARNING-BASED IMPUTATION METHODS". In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-356905.
Testo completoLui, Timothy, Daniel Gregory, Sharon A. Cowling e Well-Shen Lee. "APPLYING MACHINE LEARNING METHODS TO PREDICT GEOLOGY USING SOIL SAMPLE GEOCHEMISTRY". In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-359454.
Testo completoLuo, Hongyin, Zhiyuan Liu, Huanbo Luan e Maosong Sun. "Online Learning of Interpretable Word Embeddings". In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/d15-1196.
Testo completoRapporti di organizzazioni sul tema "Online learning methods"
Stanley, April Elisha, e Arienne McCracken. Methods for increasing student learning in an online undergraduate analysis of apparel and production course. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-353.
Testo completoYatsenko, Halyna, e Andriy Yatsenko. Використання креативних методів навчання під час викладання дисциплін «Історія української журналістики» і «Креативний текст». Ivan Franko National University of Lviv, marzo 2023. http://dx.doi.org/10.30970/vjo.2023.52-53.11736.
Testo completoTusiime, Hilary Mukwenda, e Nahom Eyasu Alemu. Embracing E-Learning in Public Universities in Ethiopia and Uganda. Mary Lou Fulton Teachers College, dicembre 2023. http://dx.doi.org/10.14507/mcf-eli.j2.
Testo completoClement, Timothy, e Brett Vaughan. Evaluation of a mobile learning platform for clinical supervision. University of Melbourne, 2021. http://dx.doi.org/10.46580/124369.
Testo completoAkhmedjanova, Diana, e Komiljon Karimov. Covid-19’s Effects on Higher Education in Uzbekistan: The Case of Westminster International University in Tashkent. TOSHKENT SHAHRIDAGI XALQARO VESTMINSTER UNIVERSITETI, novembre 2020. https://doi.org/10.70735/azco9450.
Testo completoNahorniak, Maya. Occupation of profession: Methodology of laboratory classes from practically-oriented courses under distance learning (on an example of discipline «Radioproduction»). Ivan Franko National University of Lviv, febbraio 2022. http://dx.doi.org/10.30970/vjo.2022.51.11412.
Testo completoSchmidt-Sane, Megan, Tabitha Hrynick, Erica Nelson e Tom Barker. Mutual Learning for Policy Impact: Insights from CORE. Adapting research methods in the context of Covid-19. Institute of Development Studies (IDS), dicembre 2021. http://dx.doi.org/10.19088/core.2021.008.
Testo completoFalfushynska, Halina I., Bogdan B. Buyak, Hryhorii V. Tereshchuk, Grygoriy M. Torbin e Mykhailo M. Kasianchuk. Strengthening of e-learning at the leading Ukrainian pedagogical universities in the time of COVID-19 pandemic. [б. в.], giugno 2021. http://dx.doi.org/10.31812/123456789/4442.
Testo completoДирда, Ірина Анатоліївна, Марина Вікторівна Малоіван e Анна Олександрівна Томіліна. Innovative online teaching tools for students who major in english philology: challenges and opportinutuies. Видавнича група «Наукові перспективи», 2023. http://dx.doi.org/10.31812/123456789/7078.
Testo completoDanylchuk, Hanna B., e Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, agosto 2023. http://dx.doi.org/10.31812/123456789/7732.
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