SYMMETRY PRINCIPLE AS A BASIS FOR INTEGRATION IN SCIENCE AND ITS VALUE FOR EDUCATION by V. L. Gapontsev, V. A. Fedorov, M. G. Gapontseva

“…Students’ thinking and consciousness become fragmented due to the exorbitant, permanently increasing amount of information that is presented for learning, but cannot be fully mastered by students. …”
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概念為本跨領域課程發展之研究—以國際文憑組織中學階段課程為例 Concept-Based Interdisciplinary Curriculum Development in International Baccalaureate Schools in Taiwan– The International Baccalaureate Middle Years... by 洪麗卿 Li-Ching Hung, 劉美慧 Meihui Liu, 王俐蘋 Li-Ping Wang

“…For curriculum integration, the intradisciplinary-cohesion model was first adopted, followed by the interdisciplinary model. (2) Instructional activities were designed using a backward design approach, with inquiry-based tasks, multiple assessments, and rubrics clearly delineating learning objectives. These activities guided students in progressively and actively constructing principles. …”
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Cloud software code generation via knowledge graphs and multi-modal learning by Fanlong Zhang, Huanming Chen, Quan Chen, Jianqi Liu

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Comparing the Effects of Teaching based on the Learning cycle model, Collaborative method and usual method on the level of Academic Engagement and Attitude towards Learning in Expe... by Hassan Gharibi, Saber Tabarsharafi, Shahin Rahmyan, Saba Shafaeirad

“…It seems that in the collaborative method and the learning cycle, students' cognitive constructions become imbalanced through facing the real problems of the class and pondering over them. …”
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Machine Learning Methods of Providing Informational Management Support for Students’ Professional Development by I. G. Zakharova

“…The effectiveness of this interaction resulted from its information support, based on reliable information, promptly provided to all the members of learning process.The aim of this paper was to study the machine learning methods potential for the effective management of learning process by the example of implementing information support component designed to diagnose and predict the professional development of students based on automatic text analysis.Methodology and research methods. …”
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Mapping the tidal marshes of coastal Virginia: a hierarchical transfer learning approach by Zhonghui Lv, Karinna Nunez, Ethan Brewer, Dan Runfola

“…This study leverages the combined capabilities of Sentinel-2 and National Agriculture Imagery Program (NAIP) imagery and a UNet architecture to accurately classify tidal marsh communities. …”
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Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks. by Ramzan Kh Umarov, Victor V Solovyev

“…Thus, the developed CNN models, implemented in CNNProm program, demonstrated the ability of deep learning approach to grasp complex promoter sequence characteristics and achieve significantly higher accuracy compared to the previously developed promoter prediction programs. …”
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The results of using machine learning technology for intraocular lenses optical power calculation by A.A. Arzamastsev, O.L. Fabrikantov, S.V. Belikov, N.A. Zenkova

“…The dataset included 455 depersonalized records of patients (26 columns of input factors and one column – output factor – calculation of IOL (dptr). For convenient construction of ANN models, a simulator program previously developed by the authors and Python language tools in the Google Colaboratory were used. …”
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The use of machine learning methods in the development of nasal dosage forms with cerebroprotective action by B. S. Burlaka, I. F. Bielenichev

“…The methods employed were a set of methods for binary classification of machine learning (pycaret.org) using the programming language Python 3.8 (python.org) in the package management environment Miniconda (conda.io). …”
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From Reductionist Skills to Meaningful Learning: Trust and Humility in Bedside Cardiac Assessment by Meisel JL, Navedo DD, Opole IO, Cohen GM, Bernard SA, Carmona H, Nahas AH, Eiduson CM, Papps N

“…We are studying the curriculum’s effects on BCA-related knowledge, skills, and attitudes and trust-worthiness as a learning construct. Research opportunities include impacts on humility, patient-centeredness, and PIF. …”
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Leveraging historical datasets to quantify the recovery of an impaired stream entering Yellowstone National Park by Andrew M. Ray, Alysa M. Yoder, Brian D. Ertel, Tom H. Henderson, Christopher A. Mebane

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Entry Into Valhalla: Contextualising The Learning of Legal Ethics Through the Use of Second Life Machinima by Des Butler

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Teaching and learning process for mathematization activities: The case of solving maximum and minimum problems by Al Jupri, Dian Usdiyana, Ririn Sispiyati

“…To reach this aim, this qualitative study was conducted through an observation of the learning and teaching process, including the formative written assessment, for the case of maximum and minimum problems, involving 19 students of mathematics education program. …”
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Deep learning quantifies pathologists’ visual patterns for whole slide image diagnosis by Tianhang Nan, Song Zheng, Siyuan Qiao, Hao Quan, Xin Gao, Jun Niu, Bin Zheng, Chunfang Guo, Yue Zhang, Xiaoqin Wang, Liping Zhao, Ze Wu, Yaoxing Guo, Xingyu Li, Mingchen Zou, Shuangdi Ning, Yue Zhao, Wei Qian, Hongduo Chen, Ruiqun Qi, Xinghua Gao, Xiaoyu Cui

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Contrail altitude estimation using GOES-16 ABI data and deep learning by V. R. Meijer, V. R. Meijer, S. D. Eastham, S. D. Eastham, S. D. Eastham, I. A. Waitz, S. R. H. Barrett, S. R. H. Barrett

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Enhancing Feedback Quality at Scale: Leveraging Machine Learning for Learner-Centered Feedback by Ahmad Ari Aldino, Yi-Shan Tsai, Rafael Ferreira Mello, Dragan Gašević, Guanliang Chen

“…Employing a range of machine learning and deep learning techniques, including Random Forest, XGBoost, BERT, and GPT-3.5, we systematically investigated the effectiveness of different approaches for constructing classifiers to accurately categorize feedback into various learner-centered components. …”
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APPROACH TO BUILDING A GLOBAL MOBILE AGENT WAY BASED ON Q-LEARNING by Vitalii Martovytskyi, Oleksandr Ivaniuk

“…The following methods are used: graph theory, queuing theory, Markov decision-making process theory and mathematical programming methods. The research is based on scientific articles and other materials from foreign conferences and archives in the field of machine learning, deep learning and deep reinforcement learning. …”
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Prediction and validation of anoikis-related genes in neuropathic pain using machine learning. by Yufeng He, Ye Wei, Yongxin Wang, Chunyan Ling, Xiang Qi, Siyu Geng, Yingtong Meng, Hao Deng, Qisong Zhang, Xiaoling Qin, Guanghui Chen

“…Anoikis, a special form of programmed cell death, is closely related to the progression of NP. …”
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Deep learning-based detection of indicator species for monitoring biodiversity in semi-natural grasslands by Deepak H. Basavegowda, Inga Schleip, Paul Mosebach, Cornelia Weltzien

“…Deep learning (DL) has huge potential to provide valuable insights into biodiversity changes in species-rich agricultural ecosystems such as semi-natural grasslands, helping to prioritize and plan conservation efforts. …”
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Challenges of projectification in an engineering school: Lessons learned and room for improving the whole performance of the institution by Claudette El Hajj, Germán Martínez Montes

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