EDUCATIVE NETWORK’S ROLE IN REINFORCING THE ACADEMIC DEVELOPMENT IN THE PALESTINIAN UNIVERSITIES (REFLECTIVE MODEL TOWARD AND INNOVATION IN TEACHING AND LEARNING) by Basha Sami

“…This needs a real educative action with engagement and commitment by all role actors and stakeholders.Results and scientific novelty. Based on personal experience I would like to transmit what I have learned and gained in my teaching and learning experiences and present an educative proposal that is based on the connection between the different educative higher institutions in Palestine. …”
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Learning attitude, ethics, and communication: Perspectives from first year medical students - A cross-sectional study by Mrunal R. Shenwai, Priya Mardikar

“…Conclusion: Students responded positively to the AETCOM module. The use of innovative teaching methods enhanced their understanding, with recommendations for continued guidance in reflective writing.…”
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Measurement of Suspended Sediment Concentration at the Outlet of the Yellow River Canyon: Using Sentinel-2 Images and Machine Learning by Genxin Song, Youjing Jiang, Xinyu Lei, Shiyan Zhai

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Multi-camera spatiotemporal deep learning framework for real-time abnormal behavior detection in dense urban environments by Sai Babu Veesam, B. Tarakeswara Rao, Zarina Begum, R. S. M. Lakshmi Patibandla, Arvin Arun Dcosta, Shonak Bansal, Krishna Prakash, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…Multi Scale Graph Attention Networks (MS-GAT) are used to achieve interaction-aware anomaly detection, which has resulted in up to 30% reduction in false positives. RL-DCAT or the Reinforcement Learning Based Dynamic Camera Attention Transformer works very efficiently for optimizing surveillance focus, which helps reduce 40% of the computational overhead and increases recall by 15%. …”
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The relationship between self-directed learning and academic success in nursing students of Ahvaz Jondishapur University of Medical Sciences by Faezeh Larki, shahram Molavynejad, Alireza Momeni, Mojdeh Fathi

“…Background: Learning is the key to entering of a knowledge-based society and is the main topic of any kind of education. …”
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Automated Detection of Micro-Scale Porosity Defects in Reflective Metal Parts via Deep Learning and Polarization Imaging by Haozhe Li, Xing Peng, Bo Wang, Feng Shi, Yu Xia, Shucheng Li, Chong Shan, Shiqing Li

“…Aiming at the key technology of defect detection in precision additive manufacturing of highly reflective metal materials, this study proposes an enhanced SCK-YOLOV5 framework, which combines polarization imaging and deep learning methods to significantly improve the intelligent identification ability of small metal micro and nano defects. …”
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Development and validation of computer-aided detection for colorectal neoplasms using deep learning incorporated with computed tomography colonography by Shungo Endo, Koichi Nagata, Kenichi Utano, Satoshi Nozu, Takaaki Yasuda, Ken Takabayashi, Michiaki Hirayama, Kazutomo Togashi, Hiromasa Ohira

“…Abstract Objectives Computed tomography (CT) colonography is increasingly recognized as a valuable modality for diagnosing colorectal lesions, however, the interpretation workload remains challenging for physicians. Deep learning-based artificial intelligence (AI) algorithms have been employed for imaging diagnoses. …”
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Transgressive pedagogies in a climate-constrained Africa: grounding climate change education and sustainability learning in local communities by Bob Offei Manteaw, Yaw Agyeman Boafo, Erasmus Henaku Owusu, Kirk B. Enu, Antwi Boasiako Amoah

“…This study argues for an urgent shift towards practical and experiential learning in higher education, particularly in sustainability learning and climate change education, by adopting transgressive pedagogies and place-based approaches grounded in local communities.MethodsThis study employed a series of field learning journeys within Ghana to investigate the impact of practical engagements on students’ understanding and appreciation of environmental, social, and climate change challenges. …”
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The role of senescence-related genes in major depressive disorder: insights from machine learning and single cell analysis by Kun Lian, Wei Yang, Jing Ye, Yilan Chen, Lei Zhang, Xiufeng Xu

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The influence of blended learning models and internet self-efficacy on digital citizenship attitudes of elementary school students in Indonesia by M. Mujtahidin, W. Wahjoedi, S. Wiyono, A,R, Atok, M.M. Blažić

“…<strong>Conclusions. </strong>Blended learning improves elementary students' digital citizenship attitudes more effectively than direct instruction, with internet self-efficacy levels significantly influencing these outcomes and interacting with teaching methods, suggesting educators should adopt tailored approaches based on students' technological confidence.…”
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Simulated patient consultations in a second language: the role of open learning tasks in enhancing competence and intrinsic motivation by Hao Yu, Ting Xu, Jeroen J. G. van Merriënboer, Maryam Asoodar

“…We hypothesize that the students learning with open learning tasks will outperform students learning with the closed learning task on both intrinsic motivation and Medical Dutch competence.Methods A mixed-methods pre-post quasi experimental study was conducted with 15 Dutch medical students in two intact groups (open task: n = 7; closed task: n = 8). …”
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A Novel Approach to Boosting Programming Self-Efficacy: Issue-Based Teaching for Non-CS Undergraduates in Interdisciplinary Education by Chih-Yi Tseng, Tsang-Hsiang Cheng, Chih-Hung Chang

“…This study employed a mixed-methods approach, combining the quantitative analysis of student performance and self-efficacy measures with qualitative feedback from learning portfolios and project reports. …”
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A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes by Shuheng Yang, Ralf Weiskirchen, Wenjing Zheng, Xiangxu Hu, Aibiao Zou, Zhiguo Liu, Hualin Wang

“…After screening T2DM patients, feature election was conducted using LASSO regression, and a machine learning model was developed using XGBoost. The model’s performance was evaluated based on accuracy, specificity, positive predictive value, negative predictive value and further analyzed using receiver operating curves, calibration curves, and decision curves.ResultsOut of the 758 T2DM patients included, 477 had their glycated hemoglobin (HbA1c) levels reduced to less than 6.5% after inulin intervention, resulting in an incidence rate of 62.93%. …”
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Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients by Tagayasu Anzai, Kenji Hirata, Ken Kato, Kohsuke Kudo

“…Sixteen ML models were constructed including various boosting and tree-based methods. We assessed the models by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, Positive predictive value (PPV), Negative predictive value (NPV), and F1 score. …”
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Perceptions on Oral Corrective Feedback: The Case of Iranian EFL Teachers and Students in Face-to-Face and Virtual Learning Contexts by Narges Sardabi, Amir Ghajarieh, Navid Atar Sharghi, Leyla Rahmani

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Multiple attachment perspectives: the relationship between interpersonal attachment from family and school environments and children’s learning engagement by Qi Li, Die Wang, Guihua Qin

“…Abstract Objectives Abundant evidence has demonstrated that positive interpersonal relationships promote children’s learning engagement. …”
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What are we learning with Yoga? Mapping the scientific literature on Yoga using a vector-text-mining approach. by Rosangela Ieger-Raittz, Camilla Reginatto De Pierri, Camila Pereira Perico, Flavia de Fatima Costa, Elisa Garbin Bana, Leonardo Vicenzi, Diogo de Jesus Soares Machado, Jeroniza Nunes Marchaukoski, Roberto Tadeu Raittz

“…However, there is a lack of research exploring the mechanisms behind this learning and its potential for further enhancement. …”
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Automatic segmentation and quantitative analysis of brain CT volume in 2-year-olds using deep learning model by Fengjun Xi, Liyun Tu, Feng Zhou, Yanjie Zhou, Jun Ma, Yun Peng

“…ObjectiveOur research aims to develop an automated method for segmenting brain CT images in healthy 2-year-old children using the ResU-Net deep learning model. …”
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A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach by Paola Argiento, Anna D'Agostino, Rossana Castaldo, Monica Franzese, Matteo Mazzola, Ekkehard Grünig, Lavinia Saldamarco, Valeria Valente, Alessandra Schiavo, Erica Maffei, Davide Lepre, Antonio Cittadini, Eduardo Bossone, Michele D'Alto, Luna Gargani, Alberto Maria Marra

“…Aim of the current study was to develop a Machine Learning (ML) algorithm based on the analysis of anamnestic data to predict the presence of an invasively measured PH. …”
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Efectividad de una metodología para contribuir a la habilidad de solucionar problemas en la asignatura Embriología Médica by Elena Vicenta Hernández Navarro, Jorge Luis Losada Guerra, Lizette Elena Leiva Suero, Marcelo Mantilla-Falcón

“…Abstract: Introduction: Based on the publication of methodology design and validation focused on visualization and problematization to improve the problem-solving skill in Embryology subject, the present study was carried out with the objective of evaluating the effectiveness of the aforementioned methodology in the teaching-learning process. …”
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