Understanding the Second Victim Phenomenon Among Healthcare Workers in an Italian Hospital by Raffaella Sedile, Antonella Zizza, Luca Bastiani, Eugenia Carluccio, Marinella Marrazzi, Tommaso Bellandi, Giorgio O. Spagnolo

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THE VIDEO ASSISTANT REFEREE (VAR) IN SOCCER: WHERE IS THE BIOMECHANICS? by Felipe Arruda Moura

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Strategic Sampling of Eurasian Otter Spraints for Genetic Research in South Korea: Enhancing PCR Success and Data Accuracy by Jee Hyun Kim, Jangmi Lee, Dong Youn Kim, Yoon-Do Yang, Sujoo Cho, Han-Chan Park, Sung Yong Han, Mi-Sook Min, Hang Lee, Je-Yoel Cho, Puneet Pandey

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The effects of corrective feedback on Iranian EFL students' writing by Amir Rezaei, Siros Izadpanah, Ali Shahnavaz

“…It is concluded that most of the feedback given by teachers were concentrated on grammatical errors and that the teachers’ view of feedback is based on the context, which might origin from absence of sufficient teacher training. …”
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A comparative study of kinetic balance and static balance among football, volleyball, basketball, and handball team game players using the Balance Error Scoring System test by Nihad Ayyub Qadir, Nawazad Hussien Darwesh, Awara Sabr Hamad, Marian Cretu

“…BESS, or the Balance Error Scoring System, was used to measure balance. …”
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Prevalence of oculomotor, binocular vision anomalies and refractive error among children with cerebral palsy in WHO South-East Asia: A protocol of systematic review and meta-analys... by Radhika R P, Bhamini Krishna Rao, Shonraj Ballae Ganesh Rao, Nachiket Gudi, Shradha Parsekar, Revathy Mani

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Nurses’ assessment of artificial ıntelligence chatbots for health literacy education by Gulsum Asiksoy

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PROJECT-BASED TRAINING AS A MODERN TREND IN ENGINEERING EDUCATION by Raisa M. Petruneva, Olga V. Toporkova, Valentina D. Vasilyeva

“…In the present state of things the in-depth examination of the accumulated experience and errors and a forecast of the future of engineering education are needed in order to address current and upcoming industry employment requirements.…”
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Secure Software Engineering Education: Knowledge Area, Curriculum and Resources by Xiaohong Yuan, Li Yang, Bilan Jones, Huiming Yu, Bei-Tseng Chu

“…This paper reviews current efforts and resources in secure software engineering education, with the goal of providing guidance for educators to make use of these resources in developing secure software engineering curriculum. …”
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Semantic intrusion errors differentiate between amnestic MCI who are plasma p-tau217+ from p-tau217- after adjusting for initial learning strength by Rosie E. Curiel Cid, Rosie E. Curiel Cid, David Vaillancourt, David Vaillancourt, Alexandra Ortega, Alexandra Ortega, Elizabeth A. Crocco, Elizabeth A. Crocco, Kirsten Crenshaw, Kirsten Crenshaw, Stephanie M. Remedios, Breton M. Asken, Breton M. Asken, Melissa J. Armstrong, Melissa J. Armstrong, Idaly Velez Uribe, Idaly Velez Uribe, Wei-en Wang, Wei-en Wang, Monica Rosselli, Monica Rosselli, Malek Adjouadi, Malek Adjouadi, Michael Marsiske, Michael Marsiske, Warren W. Barker, Warren W. Barker, Steven DeKosky, Steven DeKosky, Glenn Smith, Glenn Smith, Ranjan Duara, Ranjan Duara, David A. Loewenstein, David A. Loewenstein

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Architecture of an Efficient Environment Management Platform for Experiential Cybersecurity Education by David Arnold, John Ford, Jafar Saniie

“…This platform is applicable to many educational domains that rely on virtual machines for experiential learning.…”
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How to educate English language students in the age of artificial intelligence? by Anna Włodarczyk-Czubak

“…And here it is still the necessity to educate translators, without whom the translated text may contain many errors in both grammatical and stylistic structures. …”
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Challenges and solutions for integrating artificial intelligence into transportation engineering education by NANTOI, Vadim, NANTOI, Daria, CEBAN, Dumitru

“…The research aims to explore the complexities of student learning by acknowledging variations in reasoning processes, errors, and cognitive dilemmas influenced by known and unknown variables in their educational journey. …”
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Towards Computer-Supported Functional Modelling in Engineering Design Education by Tomislav Martinec, Filip Valjak, Nikola Horvat, Nenad Bojčetić

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Improving data processing in medical education through machine learning by N. Shyndaliyev, A. Orynbayeva, K. Shadinova, A. Barakova, N. Nurmukhanbetova

“…The ML model achieved a coefficient of determination (R2) of 0,85 with low prediction errors (MAE=0,45, MSE=0,30, RMSE=0,55). Statistical tests supported the hypothesis that structured ML education enhances medical students’ competencies, suggesting that future healthcare professionals trained in ML can better leverage data-driven decision-­making for improved patient care. …”
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The Use of Neural Networks in Distance Education Technologies for the Identification of Students by O. A. Kozlova, A. A. Protasova

“…With an insufficient number of training sets (datasets), neural networks begin to perceive errors as reliable information, which, as a result, will lead to the need to retrain neural networks. …”
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Experimental Comparison of Interference and Autocollimating Null Indicators by B. Nyamweru, E. V. Shishalova

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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…IntroductionPhysical education (PE) plays a vital role in promoting long-term health and wellness among students. …”
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Machine Learning Techniques and Recommender Systems for Large Educational Data by Ammar Mohammed, Murtadha Hamad

“…This study utilized the educational dataset from Coursera’s online courses. …”
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Cluster analysis of digital competencies among professors in higher education by Karime Chahuán-Jiménez, Eduardo Lara-Yergues, Dominique Garrido-Araya, Elena Salum-Alvarado, Paulina Hurtado-Arenas, Rolando Rubilar-Torrealba

“…Regarding the clustering analysis, specifically using the K-means clustering algorithm, four distinct clusters are identified based on the questionnaire scores, aligning with findings from Silhouette score and Quadratic error by number of clusters.DiscussionThis research reveals that professors in higher education span all four levels of competency as defined by the DigComEdu model, primarily falling within the intermediate levels of digital competencies. …”
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