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  1. 2701

    Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters by Ishan R. Perera, Taylor Daniels, Janella Looney, Kimberly Gittings, Frederic A. Rawlins

    Published 2025-07-01
    “…This study aims to determine the prediction accuracy of a random forest model to derive NYHA Classification from medical students’ free-text history of present illness (HPI). …”
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  2. 2702
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    The effectiveness of a psychological-sports program to reduce aggression, anger and stubbornness among primary school students by عاصم امير فاضل أ.د عكلة سليمان علي

    Published 2021-03-01
    “…The research sample reached (30) students who were divided into two control and experimental groups. …”
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  4. 2704

    Addressing Digital Addiction Among University Students: A Study of Digital Detox Techniques in Smartphone and Social Media Addiction by Deniz Yaramış, Recep Ünal

    Published 2024-12-01
    “…The interviews revealed that a majority of the students experienced withdrawal symptoms, indicative of digital addiction, and manifested this in their behavior.…”
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  5. 2705
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    Verbal Learning Style as the Least Preferred Learning Style of Students in an Asian Country by Samuel S. Poliden

    Published 2016-06-01
    “…Hence, the study aimed to determine the learning styles of freshmen students in the language class at Benguet State University, Philippines. …”
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  7. 2707
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    Interactive Mitigation of Biases in Machine Learning Models for Undergraduate Student Admissions by Kelly Van Busum, Shiaofen Fang

    Published 2025-07-01
    “…Because these issues are intrinsically subjective and context-dependent, creating trustworthy software requires human input and feedback. (1) Introduction: This work introduces an interactive method for mitigating the bias introduced by machine learning models by allowing the user to adjust bias and fairness metrics iteratively to make the model more fair in the context of undergraduate student admissions. (2) Related Work: The social implications of bias in AI systems used in education are nuanced and can affect university reputation and student retention rates motivating a need for the development of fair AI systems. (3) Methods and Dataset: Admissions data over six years from a large urban research university was used to create AI models to predict admissions decisions. …”
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  10. 2710

    Development of a Student Depression Prediction Model Based on Machine Learning with Algorithm Performance Evaluation by Penni Wintasari Simarmata, Putri Taqwa Prasetyaningrum

    Published 2025-06-01
    “…This research explores the implementation of machine learning to predict depression among university students using a dataset of 2.028 responses containing PHQ-9 scores and academic-demographic attributes. …”
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  11. 2711

    Formation of Professional Language Competence of Foreign Students in the Process of Teaching Architectural and Urban Terminology in the Lessons of Russian Language by M. A. Grigorieva, R. S. Satretdinova

    Published 2018-08-01
    “…Methods of teaching foreign students of architectural direction of special vocabulary of the studied disciplines is proposed. …”
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  12. 2712

    EFL students’ perceptions of interactive slides (Pear Deck) in blended and online flipped classrooms by Kiki Juli Anggoro, Damar Isti Pratiwi

    Published 2025-01-01
    “…A total of 490 students from a public university in Thailand participated, with 258 enrolled in online English lessons and 232 in face-to-face courses. …”
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