Enhancing TOEFL Performance and Student Motivation through Integrated Flipped and Gamified Learning in Online Settings by Safnil Arsyad, Budi Waluyo, Ira Maisarah

“…In the evolving landscape of education, the integration of flipped and gamified learning into online English courses has remained a complex and underexplored terrain. …”
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Exploring psychological dimensions of augmented reality in education: a study on learning motivation and achievement in museums by Anping Cheng, Weiru Zhang, Anran Feng, Yunmengru Wu, Wanjun Li

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THE USE OF E-LEARNING TOOLS IN TRAINING AND THE DEVELOPMENT OF SOCIAL-DIGITAL COMPETENCES IN THE GENERATIONAL Z GROUP by Izabela A. KOŁODZIEJ, Magdalena BOROWSKA

Subjects: “…e-learning tools…”
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Effect of feedback-integrated reflection, on deep learning of undergraduate medical students in a clinical setting by Zainab Maqsood, Madiha Sajjad, Raheela Yasmin

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Deep Learning-based Artificial Intelligence in Audio based Analysis of Swallowing using Cervical Auscultation by Salloum Hazem, Graf Simone, Schilling Berit, Richter Lena, Jeleff-Wölfler Olivia, Feussner Hubertus, Ostler Daniel, Wilhelm Dirk, Fuchtmann Jonas

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On-site quantitative detection of fentanyl in heroin by machine learning-enabled SERS on super absorbing metasurfaces by Yingkun Zhu, Haomin Song, Ruiying Liu, Yunyun Mu, Murali Gedda, Abdullah N. Alodhay, Lei Ying, Qiaoqiang Gan

“…Our study introduces a novel approach for on-site quantitative detection of fentanyl in heroin, employing machine learning-enabled surface-enhanced Raman spectroscopy (SERS) on superabsorbing metasurfaces. …”
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STEM-based mathematics learning module with PBL model in improving higher-order thinking skills by Ayunda Nova Millania, Agus Prasetyo Kurniawan, Ahmad Lubab, Ahmad Choirul Anam

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Predicting turbidity dynamics in small reservoirs in central Kenya using remote sensing and machine learning by Stefanie Steinbach, Anna Bartels, Andreas Rienow, Bartholomew Thiong’o Kuria, Sander Jaap Zwart, Andrew Nelson

“…Here we modelled turbidity in 34 small reservoirs in central Kenya with Sentinel-2 data from 2017 to 2023 and predicted turbidity outcomes using primary and secondary Earth observation data, and machine learning. We found distinct monthly turbidity patterns. …”
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A machine learning interpretation of the correlation between poverty and air pollution in the contiguous United States by Sajeev Magesh, Kevin Geng

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Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach by Sajadul Hassan Kumhar, Prabhakara Rao Kapula, Harveen Kaur, Radeep R. Krishna, Mudasir M Kirmani, Vijay Anant Athavale, Mohd Wazih Ahmad

“…Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. …”
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Retracted: Analysis of Option Butterfly Portfolio Models Based on Nonparametric Estimation Deep Learning Method by Journal of Function Spaces

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20th Anniversary of 9-11: Corporate Disaster Preparedness, Lessons Learned, and Ways Forward by Stefane Kabene, Said Baadel

“…., and Johnson & Johnson with the aim of learning from their experience on how they dealt with their crisis situations in real life post September 11 events. …”
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Strategic learning self-efficacy, strategic decision-making style, and environment as determinants of firm growth by Jeffrey G. Covin, Alessandra Lisanti, Giovanni Latorre, Katrina M. Brownell, Patrick M. Kreiser

“…Strategic learning self-efficacy reflects the confidence of managers in their ability to learn from the outcomes of past strategic decisions and apply that knowledge to new decisions. …”
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Applying the Aajiiqatigiingniq Research Methodology: approaches and lessons learned through collaborative survey development and analysis by Natalie Ann Carter, Shirley Tagalik, Gita Ljubicic

“…We followed the ARM in establishing partnerships, and developing and facilitating a survey, to learn how Nunavut community members use and share available weather, water, ice, and climate information. …”
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Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images by Chhaya Gupta, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

Subjects: “…Federated learning (FedL)…”
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Sten Ingelf, Learn from the Masters: Classical Harmony, Hjärup (Sweden): Sting Music 2010 by Stefan Eckert

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Post-pandemic face-to-face learning environments for undergraduate students: A scoping review protocol. by Karim Garzon Diaz, Angy Villamil Duarte, Sandra Velasco Forero, Sandra Herrera Jacobo

“…<h4>Objective</h4>This scoping review explores the existing literature related to post-pandemic face-to-face learning environments for undergraduate students following their participation in virtual classes during the Covid-19 pandemic. …”
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Data Augmentation and Machine Learning algorithms for multi-class imbalanced morphometrics data of stingless bees by Daisy Salifu, Lorna Chepkemoi, Eric Ali Ibrahim, Kiatoko Nkoba, Henri E.Z. Tonnang

“…These techniques are applied in combination with machine learning (ML) algorithms; specifically Random Forest (RF), and Support Vector Machine (SVM), to assess the models’ predictive performance to infer stingless bee samples identities. …”
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Automatic Segmentation of Ischemic Stroke Lesions in CT Perfusion Maps Using Deep Learning Networks by Lida Zare Lahijan, Saeed Meshgini, Reza Afrouzian

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Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters by C. Braxton Owens, Nithin Mathew, Tyce W. Olaveson, Jacob P. Tavenner, Edward M. Kober, Garritt J. Tucker, Gus L. W. Hart, Eric R. Homer

“…Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. …”
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