AIMC Topic: Universities

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Detecting Perceived Unfair Treatment Among US College Students Using Mobile Sensing: Pilot Machine Learning Study.

JMIR formative research
BACKGROUND: Experiences of unfair treatment on college campuses are linked to adverse mental and physical health outcomes, highlighting the need for interventions. However, detecting such experiences relies mainly on self-reports. No prior research h...

Application of AI and deep learning technology for IPE education under dual track cultivation model.

Scientific reports
This work intends to explore the effectiveness of a dual-track cultivation model for ideological and political literacy in vocational colleges driven by artificial intelligence deep learning models. This work compares the performance of different mod...

Artificial intelligence (AI)-Enabled behavioral health application for college students: Pilot study protocol.

PloS one
Given the prevalence of depression among young adults, particularly those aged 18-25, this study aims to address a critical need in higher education institutions for proactive, private, automated mental health self-awareness. This study protocol outl...

Utilizing multi-level convolutional neural networks to achieve refined modeling and visual analysis of college students' mental health data.

PloS one
Early identification of students' mental health issues has become an urgent priority in education and public health. However, existing studies often rely on questionnaire-based assessments or traditional machine learning models, which are limited by ...

Randomised controlled trial of VR-based observation meditation with AI coaching ('Otti') for stress reduction in university students in the United States: study protocol.

BMJ open
INTRODUCTION: Stress is a major health issue in contemporary society, and mindfulness-based approaches reduce stress and anxiety but face practical barriers to consistent practice; this protocol evaluates a Virtual Reality (VR)-based observation medi...

Predicting visual aesthetic preferences in Tehran city universities campuses using machine learning techniques.

Scientific reports
Visual aesthetic preferences fundamentally shape the restorative potential of university landscapes and have a significant impact on student well-being and engagement. This study developed Ensemble Learning Models to predict students' aesthetic prefe...

Prevalence, associated factors, and machine learning-based prediction of depression, anxiety, and stress among university students: a cross-sectional study from Bangladesh.

Journal of health, population, and nutrition
BACKGROUND: Mental health challenges are a growing global public health concern, with university students at elevated risk due to academic and social pressures. Although several studies have exmanined mental health among Bangladeshi students, few hav...

Determinants of student adoption of artificial intelligence applications in higher education.

Scientific reports
The integration of artificial intelligence (AI) into educational settings has the potential to transform learning experiences; however, its adoption among students remains impacted by various factors. The current study assesses the determinant factor...

Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis.

Scientific reports
The landscape of academic publishing has evolved dramatically, leading to a surge in publications and journals. The 'publish or perish' culture has resulted in undesirable practices, such as many researchers publishing in predatory journals due to in...

Students' perceptions of AI mental health chatbots: an exploratory qualitative study at Sultan Qaboos University.

BMJ open
OBJECTIVES: The aim of this study is to explore the perceptions, attitudes and previous experiences of Sultan Qaboos University (SQU) students towards artificial intelligence (AI) mental health chatbots.