AIMC Topic: Students

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The ChatGPT Fact-Check: exploiting the limitations of generative AI to develop evidence-based reasoning skills in college science courses.

Advances in physiology education
Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenge...

Machine learning approach to student performance prediction of online learning.

PloS one
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educati...

Generative AI in Higher Education: Balancing Innovation and Integrity.

British journal of biomedical science
Generative Artificial Intelligence (GenAI) is rapidly transforming the landscape of higher education, offering novel opportunities for personalised learning and innovative assessment methods. This paper explores the dual-edged nature of GenAI's integ...

Research on the self-efficacy and resilience of female graduate students in the era of artificial intelligence: analysis of the mechanism of mobile phone dependence, anxiety and mentoring relationship.

Archives of women's mental health
PURPOSE: The purpose of this study is to investigate the impact of the employment situation on the anxiety levels and research self-efficacy of graduate students, with a particular focus on female graduate students. The study aims to understand how t...

What is the influence of psychosocial factors on artificial intelligence appropriation in college students?

BMC psychology
BACKGROUND: In recent years, the adoption of artificial intelligence (AI) has become increasingly relevant in various sectors, including higher education. This study investigates the psychosocial factors influencing AI adoption among Peruvian univers...

AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model.

Acta psychologica
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated ...

Predicting learning achievement using ensemble learning with result explanation.

PloS one
Predicting learning achievement is a crucial strategy to address high dropout rates. However, existing prediction models often exhibit biases, limiting their accuracy. Moreover, the lack of interpretability in current machine learning methods restric...

Utilising AI technique to identify depression risk among doctoral students.

Scientific reports
The phenomenon that the depression risk among doctoral students is higher than that of other groups should not be ignored. Despite this, studies specifically addressing depression risk in doctoral students are relatively scarce, and existing findings...

Conceptual understanding and cognitive patterns construction for physical education teaching based on deep learning algorithms.

Scientific reports
To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using de...

How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Cadernos de saude publica
Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following research question: "How do machine learning models perform in the detection o...