Students’ Perceptions of the Literature Circles Method in English Learning at SMKN 1 Toraja Utara by Demma Palulun, Yizrel Nani Sallata, Linerda Tulaktondok

“…Literature Circles are a student-centered approach where learners engage in small group discussions based on selected literary texts. This method aims to promote reading comprehension, encourage communication, foster collaborative learning, and develop critical thinking in a supportive environment. …”
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Relationship between Classroom Management Practice and Student’s Critical Thinking Skills at Higher Education Level by Quratul Ain Hina, Mahek Arshad, Sidra Munir

“…However none of the above mentioned effect was statistically significant. Teachers need to learn how to manage positive learning environment. …”
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The legacy of attending a sustainably friendly school: Ysgol San Sior, a place of possibilities for a sustainable world by Diane Boyd, Naomi McLeod, Ian Jones

“…Our research also indicates how the seamless Welsh curriculum builds on the foundational base of early childhood, through primary and beyond, to inform all areas of lifelong learning and nurtures a strong sense of self and being Welsh. …”
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From boredom to excitement: unleashing motivation with Kahoot in English language learning by Abdullah Noori, Asadullah Azimi

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A case method for Sales and Operations Planning: a learning experience from Germany by Luiz Felipe Scavarda, Bernd Hellingrath, Tobias Kreuter, Antonio Márcio Tavares Thomé, Marcelo Xavier Seeling, Jan-Hendrick Fischer, Raquel Mello

“…This paper presents a case method for S&OP and the learning experience of its application at the University of Münster (Germany). …”
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Student Perceptions of Project-Based Learning When Studying ‘Information Systems’ in an ICT Engineering Program: Taking Advantage of Active Learning by Josep Petchamé, Ignasi Iriondo, Odalys Torné, Francesc Solanellas

“…This article presents a case study on the way of teaching and learning the subject ‘Information Systems’ to ICT (Information and Communication Technology) engineering students, which is based on an active learning strategy implemented through a Project-Based Learning (PjBL) method, a practice that facilitates knowledge acquisition in addition to enhancing diverse learning outcomes such as teamwork, critical thinking, and analysis, or communication skills. …”
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Authoritarian protectionism and the post-neoliberal transition: learning from Stuart Hall’s method of articulation by Luke Cooper

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AutoLDT: a lightweight spatio-temporal decoupling transformer framework with AutoML method for time series classification by Peng Wang, Ke Wang, Yafei Song, Xiaodan Wang

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The Effect of Laboratory-Based Blended-Project Based Learning Model on The Science Process Skills of Students by Ihsan Nurdiansah, Endang Surahman, Yanti Sofi Makiyah, Elis Kurnia

“…The problem that often arises so far in the field is how to teach teachers who still use conventional methods. This learning method has not been able to support the science learning process, which causes low science process skills in students. …”
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Prediction of PD-L1 tumor positive score in lung squamous cell carcinoma with H&E staining images and deep learning by Qiushi Wang, Xixiang Deng, Pan Huang, Qiang Ma, Lianhua Zhao, Yangyang Feng, Yiying Wang, Yuan Zhao, Yan Chen, Peng Zhong, Peng He, Mingrui Ma, Peng Feng, Hualiang Xiao

“…Therefore, the application of deep learning models to segment and quantitatively predict PD-L1 expression in digital sections of Hematoxylin and eosin (H&E) stained lung squamous cell carcinoma is of great significance.MethodsWe constructed a dataset comprising H&E-stained digital sections of lung squamous cell carcinoma and used a Transformer Unet (TransUnet) deep learning network with an encoder-decoder design to segment PD-L1 negative and positive regions and quantitatively predict the tumor cell positive score (TPS).ResultsThe results showed that the dice similarity coefficient (DSC) and intersection overunion (IoU) of deep learning for PD-L1 expression segmentation of H&E-stained digital slides of lung squamous cell carcinoma were 80 and 72%, respectively, which were better than the other seven cutting-edge segmentation models. …”
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The advantages of lexicon-based sentiment analysis in an age of machine learning. by A Maurits van der Veen, Erik Bleich

“…Compared to machine learning and large language model (LLM) approaches, lexicon-based methods may sacrifice some in performance, but in exchange they provide generalizability and domain independence, while crucially offering the possibility of identifying gradations in sentiment. …”
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Realization of medical image data transfer learning based on MATLAB by HUANG Xiaxuan, HUANG Tao, YUAN Shiqi, HE Ningxia, WU Wentao, LYU Jun

“…Objective To discuss how to implement the application of medical image data on transfer learning based on MATLAB.Methods Taking MIMIC-CXR for example, 500 X-ray images of positive and the same number negative pleural effusion were randomly selected as the total data set, and the MATLAB software transfer learning method based on the ResNet network model was used for multiple training, calculating the AUC value to evaluate the accuracy of the model training for pleural effusion image classification.Results The pleural effusion imaging test set and training set used in this study were evenly distributed. …”
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Game-Based Social-Emotional Learning for Youth: School-Based Qualitative Analysis of Brain Agents by Elizabeth Liverman, David Antognoli, Cordelia Elaiho, Madison McGuire, Abbey Stoltenburg, Angel Navarrete, Garrett Bates, Thomas Chelius, Constance Gundacker, Paula Lumelsky, Brandon Currie, John Meurer Sr

“…Game-based learning is a promising, engaging method for delivering SEL content. …”
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FAFIT APPLICATION: SCRATCH WEB-BASED ENGLISH LEARNING INNOVATION by Fatma Yuniarti, Fitri wulandari, Renita Sugesti

“…Validity test results from material and media experts showed a feasibility level of 92%, while positive responses from students reached 88%. Personalization of learning experiences through the FaFit application proved to increase student learning motivation by 42% compared to conventional methods.…”
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Interactive image segmentation algorithm based on adaptive kernel learning by LONG Jianwu, LI Jihao

“…To address the issue that most existing interactive image segmentation methods suffer from limited segmentation performance due to their susceptibility to noise interference and non-convex structure impacts in the original feature space, an adaptive kernel learning-based interactive image segmentation algorithm was proposed. …”
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Deep learning-based lung cancer classification of CT images by Mohammad Khalid Faizi, Yan Qiang, Yangyang Wei, Ying Qiao, Juanjuan Zhao, Rukhma Aftab, Zia Urrehman

“…Traditional radiological methods often struggle with high false-positive rates, underscoring the need for advanced diagnostic tools. …”
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Suicide risk prediction for Korean adolescents based on machine learning by Haitao Wang, Han Yuan, Yunong Zhang, Qixuan Wang, Zeng Gao, Mujuan Zhao

“…Both the Expert Consultation Method (ECM) and Random Forest-Based Filter Feature Selection (RFFS) datasets revealed that the GBM model achieved the best results, with a predictive accuracy (ACC) of 88%, sensitivity (SENS) of 97%, specificity (SPEC) of 26%, positive predictive value (PPV) of 90%, negative predictive value (NPV) of 56%, and an area under the curve (AUC) of 83%. …”
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Dynamic Risk Thresholds for SIEM Alerting Based on Machine Learning by Artur Kapera, Marcin Niemiec

“…In the article, a theoretical concept of a Dynamic Risk-Based Alerting model for SIEM based on machine learning has been presented. …”
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Improving students' performance via case-based e-learning by Sebastian Ertl, Sebastian Ertl, Patricia P. Wadowski, Henriette Löffler-Stastka

“…Consequently, we evaluated the efficacy of a case-based e-learning approach.MethodThe impact of a case-based interdisciplinary e-learning environment with an integrated question/feedback system on medical students' academic performance was examined in a cross-sectional sample of different study years, longitudinally matched per academic year. …”
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Deep Learning-Based Identification of Echocardiographic Abnormalities From Electrocardiograms by Goro Fujiki, MD, Satoshi Kodera, MD, PhD, Naoto Setoguchi, MD, Kengo Tanabe, MD, PhD, Kotaro Miyaji, MD, PhD, Shunichi Kushida, MD, PhD, Mike Saji, MD, PhD, Mamoru Nanasato, MD, PhD, Hisataka Maki, MD, PhD, Hideo Fujita, MD, PhD, Nahoko Kato, MD, PhD, Hiroyuki Watanabe, MD, PhD, Minami Suzuki, MD, Masao Takahashi, MD, PhD, Naoko Sawada, MD, PhD, Jiro Ando, MD, Masataka Sato, MD, Shinnosuke Sawano, MD, PhD, Susumu Katsushika, MD, PhD, Hiroki Shinohara, MD, PhD, Norifumi Takeda, MD, PhD, Katsuhito Fujiu, MD, PhD, Hiroshi Akazawa, MD, PhD, Hiroyuki Morita, MD, PhD, Issei Komuro, MD, PhD

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