Student’s Executive Function Assessment Tool using Convolutional Neural Network

Sanchez, Maria Trinidad Ursula R.; Singson, Lowell Nathaniel B.; Villaverde, Jocelyn F.

doi:10.1109/tencon50793.2020.9293886

Cited by 4 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ECG is a simple test that uses a sensor attached to one’ s skin for detecting the electrical signals generated when the heart beats, which is the data used in less than 10% of the researches. In addition to the monitoring of ECG data, heart rate and other characteristics can also be calculated from the ECG for further study (Ahonen et al, 2018; Kanna et al, 2018; Pourmohammadi & Maleki, 2020; Sanchez et al, 2020). Blood volume pulse (BVP) is another method of measuring heart rate, based on the amount of blood passing through the local area tissue with each beat (pulse) of the heart (Gao et al, 2020; Pijeira-Díaz et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Learning Analytics Based on Wearable Devices: A Systematic Literature Review From 2011 to 2021

Liu

Ren

Kong

et al. 2022

Journal of Educational Computing Research

View full text Add to dashboard Cite

Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published between 2011 and 2021, exploring current research on learning analytics based on wearable devices in detail from both descriptive and content analysis. The descriptive analysis reviewed the included literature in five dimensions: publication times of the reviewed literature, wearable devices and data types used in studies, stakeholders, objectives, and methods involved in the analysis procedure. The content analysis aims to examine the literature covered in terms of three categorical domains of educational objectives: cognitive, affective, and behavioral, to investigate the practical applications and potential issues of learning analytics based on wearable devices. After that, based on the overall research content of the reviewed literature, a framework for learning analytics based on wearable devices is present, and its application process is summarized and analyzed for the reference of related researchers. At last, we summarize the limitations of existing studies and present several recommendations to further promote research and development in this field.

show abstract