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Using Machine Learning to Train a Wearable Device for Measuring Students' Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use.

Sensors (Basel, Switzerland)
Automated tracking of physical fitness has sparked a health revolution by allowing individuals to track their own physical activity and health in real time. This concept is beginning to be applied to tracking of cognitive load. It is well known that ...

Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.

International journal of medical informatics
INTRODUCTION: School violence has a far-reaching effect, impacting the entire school population including staff, students and their families. Among youth attending the most violent schools, studies have reported higher dropout rates, poor school atte...

Developing an Interactive Environment Through the Teaching of Mathematics with Small Robots.

Sensors (Basel, Switzerland)
The article is the product of the study "Development of innovative resources to improve logical-mathematical skills in primary school, through educational robotics", developed during the 2019 school year in three public schools in the province of Chi...

Teaching cross-cultural design thinking for healthcare.

Breast (Edinburgh, Scotland)
OBJECTIVES: Artificial intelligence (AI) is poised to transform breast cancer care. However, most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. In this paper, we describe our experiences teac...

Using machine learning to model problematic smartphone use severity: The significant role of fear of missing out.

Addictive behaviors
We examined a model of psychopathology variables, age and sex as correlates of problematic smartphone use (PSU) severity using supervised machine learning in a sample of Chinese undergraduate students. A sample of 1097 participants completed measures...

Robust Student Network Learning.

IEEE transactions on neural networks and learning systems
Deep neural networks bring in impressive accuracy in various applications, but the success often relies on heavy network architectures. Taking well-trained heavy networks as teachers, classical teacher-student learning paradigm aims to learn a studen...

Using machine learning to examine the relationship between asthma and absenteeism.

Environmental monitoring and assessment
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating ...

Harnessing robotic automation and web-based technologies to modernize scientific outreach.

PLoS biology
Technological breakthroughs in the past two decades have ushered in a new era of biomedical research, turning it into an information-rich and technology-driven science. This scientific revolution, though evident to the research community, remains opa...

An Empirical Study on the Artificial Intelligence Writing Evaluation System in China CET.

Big data
The Artificial Intelligence Writing Evaluation system is widely used in China College English writing. It provides for both teachers and the English learners services of automated composition evaluation on the net in order that teacher's working load...