System for Detecting Student Attention Pertaining and Alerting

Vettivel, N.; Jeyaratnam, N.; Ravindran, Vyshnavi; Sumathipala, Sagara; Amarakecrthi, Senaka

doi:10.1109/icitr.2018.8736145

Cited by 9 publications

(5 citation statements)

References 13 publications

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“…In fact, the EBR has been demonstrated to be inversely correlated with attention and vigilance: i.e., an increased EBR is a biomarker of decreased attention, the loss of situation awareness and even drowsiness [39,47,48]. Such findings have also been demonstrated in the scientific literature related to education and learning [49,50]. In the present work, for convenience, the inverse of the EBR was considered in order to have a direct correlation with attention.…”

Section: Discussionsupporting

confidence: 52%

Neurophysiological Evaluation of Students’ Experience during Remote and Face-to-Face Lessons: A Case Study at Driving School

Simonetti

Tamborra²,

Giorgi³

et al. 2023

Brain Sciences

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Nowadays, fostered by technological progress and contextual circumstances such as the economic crisis and pandemic restrictions, remote education is experiencing growing deployment. However, this growth has generated widespread doubts about the actual effectiveness of remote/online learning compared to face-to-face education. The present study was aimed at comparing face-to-face and remote education through a multimodal neurophysiological approach. It involved forty students at a driving school, in a real classroom, experiencing both modalities. Wearable devices to measure brain, ocular, heart and sweating activities were employed in order to analyse the students’ neurophysiological signals to obtain insights into the cognitive dimension. In particular, four parameters were considered: the Eye Blink Rate, the Heart Rate and its Variability and the Skin Conductance Level. In addition, the students filled out a questionnaire at the end to obtain an explicit measure of their learning performance. Data analysis showed higher cognitive activity, in terms of attention and mental engagement, in the in-presence setting compared to the remote modality. On the other hand, students in the remote class felt more stressed, particularly during the first part of the lesson. The analysis of questionnaires demonstrated worse performance for the remote group, thus suggesting a common “disengaging” behaviour when attending remote courses, thus undermining their effectiveness. In conclusion, neuroscientific tools could help to obtain insights into mental concerns, often “blind”, such as decreasing attention and increasing stress, as well as their dynamics during the lesson itself, thus allowing the definition of proper countermeasures to emerging issues when introducing new practices into daily life.

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Section: Discussionsupporting

confidence: 52%

Neurophysiological Evaluation of Students’ Experience during Remote and Face-to-Face Lessons: A Case Study at Driving School

Simonetti

Tamborra²,

Giorgi³

et al. 2023

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…increasing EBR is a biomarker of attention decreasing, loss of situation awareness and even drowsiness [36], [43], [44]. Such findings have been demonstrated also in scientific literature related to education and learning [45], [46]. In the present work, for convenience, the inverse of the EBR was considered in order to have a direct correlation with attention.…”

Section: Discussionmentioning

confidence: 59%

Neurophysiological Evaluation of Students’ Experience during Remote and Face-To-Face Lessons. A Case Study at Driving School

Simonetti¹,

Tamborra²,

Giorgi³

et al. 2022

Preprint

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Nowadays, fostered by technological progress and contextual circumstances such as economic crisis and pandemic restrictions, remote education is living a growing deployment. However, this growth generated widespread doubts about the actual effectiveness of remote/online compared to face-to-face education. The present study aimed at comparing face-to-face and remote education through a multimodal neurophysiological approach. It involved forty students at a driving school, during a real classroom, experiencing both the modalities. Wearable devices to measure brain, ocular, heart and sweating activities were employed in order to analyse the students’ neurophysiological signals to obtain insights about their cognitive dimension. In particular, four parameters were considered, the Eye Blink Rate, the Heart Rate and its Variability and the Skin Conductance Level. Also, the students filled a questionnaire at the end to obtain an explicit measure of their learning performance. Data analysis showed a higher cognitive activity, in terms of attention and mental engagement, in presence with respect to remote modality. On the other hand, students by remote felt more stressed, in particular during the first part of the lesson. Analysis of questionnaires demonstrated worst performance by remote, thus suggesting a common “disengaging” behaviour when attending remote courses, thus undermining their effectiveness. In conclusion, neuroscientific tools could help to obtain insights about mental concerns, often «blind», such as attentional decreasing and stress increasing, as well as their dynamics during the lesson itself, so allowing to define proper countermeasures to emerging issues when introducing new practices into daily life.

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“…Vettivel et al [4] tried to establish the relationship between attention and human parameters such as heart rate variation, facial expressions, and brain waves. They used appropriate sensors to collect information on the three student parameters during the course.…”

Section: A Existing Systemsmentioning

confidence: 99%

A New Big Data Architecture for Real-Time Student Attention Detection and Analysis

Hachad¹,

Sadiq²,

Ghanimi³

2020

IJACSA

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Big Data technologies and their analytical methods can help improve the quality of education. They can be used to process and analyze classroom video streams to predict student attention, this would greatly improve the learning-teaching experience. With the increasing number of students and the expansion of educational institutions, processing and analyzing video streams in real-time become a complicated issue. In this paper, we have reviewed the existing systems of student attention detection, open-source real-time data stream processing technologies, and the two major data stream processing architectures. We also proposed a new Big Data architecture for real-time student attention detection.

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System for Detecting Student Attention Pertaining and Alerting

Cited by 9 publications

References 13 publications

Neurophysiological Evaluation of Students’ Experience during Remote and Face-to-Face Lessons: A Case Study at Driving School

Neurophysiological Evaluation of Students’ Experience during Remote and Face-to-Face Lessons: A Case Study at Driving School

Neurophysiological Evaluation of Students’ Experience during Remote and Face-To-Face Lessons. A Case Study at Driving School

A New Big Data Architecture for Real-Time Student Attention Detection and Analysis

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