AIMC Topic: Students

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Leveraging Generative Artificial Intelligence to Improve Motivation and Retrieval in Higher Education Learners.

JMIR medical education
Generative artificial intelligence (GenAI) presents novel approaches to enhance motivation, curriculum structure and development, and learning and retrieval processes for both learners and instructors. Though a focus for this emerging technology is a...

Analysing how AI-powered chatbots influence destination decisions.

PloS one
This study aims to explore the role of destination chatbots as innovative tools in travel planning, focusing on their ability to enhance user experiences and influence decision-making processes. Based on the Technology Acceptance Model, Enterprise Co...

Artificial Intelligence Algorithms, Bias, and Innovation: Implications for Social Work.

Journal of evidence-based social work (2019)
PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As the reach of AI continues to grow, there is a need to examine student perspectives on the increasing prevalence of AI and AI-based practice approache...

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

BMC public health
BACKGROUND: In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementation of strict lockdown management measures in colleges. While existing research has indicated that the pandemic has had a significant impact on sleep...

Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.

Frontiers in public health
INTRODUCTION: The increasing prevalence of mental health challenges among college students necessitates innovative approaches to early identification and intervention. This study investigates the application of artificial intelligence (AI) techniques...

Predictors of depression among Chinese college students: a machine learning approach.

BMC public health
BACKGROUND: Depression is highly prevalent among college students, posing a significant public health challenge. Identifying key predictors of depression is essential for developing effective interventions. This study aimed to analyze potential depre...

Exploring AI-Driven Feedback as a Cultural Tool: A Cultural-Historical Perspective on Design of AI Environments to Support Students' Writing Process.

Integrative psychological & behavioral science
This study draws on the cultural-historical perspectives of Vygotsky and Galperin to examine the role of AI-generated feedback within the Assessment for Learning (AfL) process in fostering students' development as learners. By leveraging Galperin's c...

On the relationship between music students' negative emotions, artificial intelligence readiness, and their engagement.

Acta psychologica
This study explored the relationship between negative emotions, engagement, and artificial intelligence (AI) readiness among 323 music students. The researchers employed SPSS (version 27) and AMOS (version 24) for analysis using the Emotion Beliefs Q...

Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach.

BMC public health
BACKGROUND: Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understandin...

Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework.

PloS one
As education increasingly relies on data-driven methodologies, accurately predicting student performance is essential for implementing timely and effective interventions. The California Student Performance Dataset offers a distinctive basis for analy...