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Статті в журналах з теми "Schools and learning environments not elsewhere classified"
Gee, James Paul. "Affinity spaces: How young people live and learn on line and out of school." Phi Delta Kappan 99, no. 6 (February 26, 2018): 8–13. http://dx.doi.org/10.1177/0031721718762416.
Повний текст джерелаLäänemets, Urve, Katrin Kalamees-Ruubel, Kristi Kiilu, Kadi Kaja, and Anu Sepp. "VALUES CREATED BY MUSIC EDUCATION IN GENERAL COMPREHENSIVE SCHOOLS." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 2 (May 28, 2021): 318–29. http://dx.doi.org/10.17770/sie2021vol2.6297.
Повний текст джерелаFernández-Cézar, Raquel, Natalia Solano-Pinto, and Dunia Garrido. "Can Mathematics Achievement Be Predicted? The Role of Cognitive–Behavioral–Emotional Variables." Mathematics 9, no. 14 (July 7, 2021): 1591. http://dx.doi.org/10.3390/math9141591.
Повний текст джерелаOrava, Taryn, Steve Manske, and Rhona Hanning. "Support for healthy eating at schools according to the comprehensive school health framework: evaluation during the early years of the Ontario School Food and Beverage Policy implementation." Health Promotion and Chronic Disease Prevention in Canada 37, no. 9 (September 2017): 303–12. http://dx.doi.org/10.24095/hpcdp.37.9.05.
Повний текст джерелаPfledderer, Christopher D., Michael W. Beets, Sarah Burkart, Elizabeth L. Adams, Robert Glenn Weaver, Xuanxuan Zhu, and Bridget Armstrong. "Impact of Virtual vs. In-Person School on Children Meeting the 24-h Movement Guidelines during the COVID-19 Pandemic." International Journal of Environmental Research and Public Health 19, no. 18 (September 7, 2022): 11211. http://dx.doi.org/10.3390/ijerph191811211.
Повний текст джерелаLam, Cici Sze-ching, Patcy P. S. Yeung, and Mantak Yuen. "Personal and Environmental Factors Affecting Hong Kong High-Ability Students’ School Satisfaction." Journal of Psychologists and Counsellors in Schools 28, no. 2 (December 6, 2017): 166–84. http://dx.doi.org/10.1017/jgc.2017.18.
Повний текст джерелаKaljee, Linda, Kelvin Munjile, Anitha Menon, Stephen Tembo, Xiaoming Li, Liying Zhang, Jacob Malungo, Bonita Stanton, and Lisa Langhaug. "The ‘Teachers Diploma Program’ in Zambian Government Schools: A Baseline Qualitative Assessment of Teachers’ and Students’ Strengths and Challenges in the Context of a School-Based Psychosocial Support Program." International Education Studies 10, no. 2 (January 30, 2017): 92. http://dx.doi.org/10.5539/ies.v10n2p92.
Повний текст джерелаAttayib Umar, Abdul-Majeed. "The Effect of Classroom Environment on Achievement in English as a Foreign Language (EFL): A Case Study of Secondary School Students in Gezira State: Sudan." World Journal of English Language 7, no. 4 (December 24, 2017): 1. http://dx.doi.org/10.5430/wjel.v7n4p1.
Повний текст джерелаMasoumi-Moghaddam, Saman. "Using Drama and Drama Techniques to Teach English Conversations to English as A Foreign Language Learners." International Journal of Applied Linguistics and English Literature 7, no. 6 (November 1, 2018): 63. http://dx.doi.org/10.7575/aiac.ijalel.v.7n.6p.63.
Повний текст джерелаMoghadam, Saman M., and Reza Ghafarsamar. "Using Drama and Drama Techniques to Teach English Conversations to EFL Learners." Global Journal of Foreign Language Teaching 8, no. 2 (May 29, 2018): 92–101. http://dx.doi.org/10.18844/gjflt.v8i2.3319.
Повний текст джерелаДисертації з теми "Schools and learning environments not elsewhere classified"
(5930588), Michael W. Coots. "LEARNING ENVIRONMENTS FOR STEM INTEGRATION." Thesis, 2021.
Знайти повний текст джерелаSTEM education has been a topic of reform in education for many years and it has recently focused primarily on the education methodology called STEM integration. Universities and state departments of education have defined teacher education programs and STEM initiatives that explore the necessary ingredients for a curriculum using this methodology, but they do not provide explicit instructions for the design of the learning environment. The purpose of this study was to explore the question "What are the characteristics of high school learning environments that support integrated STEM instruction?"
This qualitative study used a postpositive lens and multiple-case study framework to distill the experiences and evidence gathered from four STEM certified high schools in the state of Indiana. This distillation resulted in three universal themes common to each school which were: the allocation of universally accessible free space for STEM integration, the importance for mobility of resources and students, and the need for supportive technological resources.
This study is applicable to both those who are educators working in STEM education and those researchers looking to understand the STEM integration paradigm or learning environment design. Educators can use this study to plan their own learning environments and researchers can use this study as a pilot to many other outlets in the topic of STEM integration.
(8771429), Ashley S. Dale. "3D OBJECT DETECTION USING VIRTUAL ENVIRONMENT ASSISTED DEEP NETWORK TRAINING." Thesis, 2021.
Знайти повний текст джерелаAn RGBZ synthetic dataset consisting of five object classes in a variety of virtual environments and orientations was combined with a small sample of real-world image data and used to train the Mask R-CNN (MR-CNN) architecture in a variety of configurations. When the MR-CNN architecture was initialized with MS COCO weights and the heads were trained with a mix of synthetic data and real world data, F1 scores improved in four of the five classes: The average maximum F1-score of all classes and all epochs for the networks trained with synthetic data is F1∗ = 0.91, compared to F1 = 0.89 for the networks trained exclusively with real data, and the standard deviation of the maximum mean F1-score for synthetically trained networks is σ∗ F1 = 0.015, compared to σF 1 = 0.020 for the networks trained exclusively with real data. Various backgrounds in synthetic data were shown to have negligible impact on F1 scores, opening the door to abstract backgrounds and minimizing the need for intensive synthetic data fabrication. When the MR-CNN architecture was initialized with MS COCO weights and depth data was included in the training data, the net- work was shown to rely heavily on the initial convolutional input to feed features into the network, the image depth channel was shown to influence mask generation, and the image color channels were shown to influence object classification. A set of latent variables for a subset of the synthetic datatset was generated with a Variational Autoencoder then analyzed using Principle Component Analysis and Uniform Manifold Projection and Approximation (UMAP). The UMAP analysis showed no meaningful distinction between real-world and synthetic data, and a small bias towards clustering based on image background.
(8803076), Jordan M. McGraw. "Implementation and Analysis of Co-Located Virtual Reality for Scientific Data Visualization." Thesis, 2020.
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