A Review on Different Approaches for Assessing Student Attentiveness in Classroom using Behavioural Elements

Kainat, .; Ali, Sara; Iqbal, Khawaja Fahad; Avaz, Yasar; Saiid, Muhammad

doi:10.1109/icai55435.2022.9773418

Cited by 4 publications

(2 citation statements)

References 46 publications

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“…Assessing the attention of students is the main point to improve both instructing and learning [12]. Kainat et al [13] declared that attention is core for effective learning, but analyzing attention is a complex task.…”

Section: Online Educationmentioning

confidence: 99%

The Attention of Students in Online Education

Barba-Guamán

Valdiviezo-Díaz

2022

Int. J. Emerg. Technol. Learn.

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The level of attention of students who receive classes through videoconferencing platforms is troubling. Different throughout an entire lecture, the instructor can perceive the participants' behavior, while in an online class, it is difficult to determine if they are attentive to the instructions given. An innovative method that helps solve this problem is the use of computer vision algorithms, with methods such as face detection, facial landmarks, face recognition, and head pose detection based on deep learning networks. In this paper, a neural network was trained using facial landmarks to estimate head position and thus attention levels. The model was applied in five classes using different videoconferencing platforms in the Intelligent Systems subject of a private university in Ecuador. Some limitations, such as lighting and video quality, affected the level of accuracy. The number of registered participants was 12, of which between 30% and 80% attended. The maximum level of attention detected was 91.9%, while the minimum level was 86.6%. This case study proves that the head position detection function employed by many videoconferencing platforms is a useful parameter that aids the instructor in this type of context.

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Section: Online Educationmentioning

confidence: 99%

The Attention of Students in Online Education

Barba-Guamán

Valdiviezo-Díaz

2022

Int. J. Emerg. Technol. Learn.

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“…However, a lack of student attentiveness and active engagement with learning activities has become a significant challenge that negatively influences learning outcome (Creelman, 2021;Derakhshandeh et al, 2021). Many studies have been performed to determine the attentiveness of students in a learning setting (Adam et al, 2009;Kainat et al, 2022;, however all these studies focus more on determining the attention states rather than studying the effective relationship of attentiveness on learning performance. Only few (Creelman, 2021;Fredricks & McColskey, 2012) studies such relationship.…”

Section: Introductionmentioning

confidence: 99%

A study of children emotion and their performance while handwriting Arabic characters using a haptic device

et al. 2022

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Emotion and focus of children during handwriting are essential for language learning. Handwriting for young children is challenging because it needs deep motivation and willingness to complete the task regardless of its difficulty. Recently, emerged haptic guidance systems have a good potential to offer children a better sense of engagement to keep their interests awake. Yet, handwriting in 3D is more challenging for children due to many reasons including demotivation, out of focus, and visuomotor coordination difficulties. In this paper, we study the effectiveness of a haptic device in analyzing schoolchildren emotion, attentiveness and handwriting performance of Arabic letters. We conducted the experiments for a period of four weeks with an immersive environment where the subjects practiced writing in VR environment using a haptic device-controlled stylus. We assessed the childrens’ emotions to get insights into their engagement during such hard learning environment. We found that our approach improved the participants’ fine-motor skills and handwriting quality. However, our analysis revealed that such task was effective on detecting emotions (angry/neutral) only as a negative/positive contributor of performance. Overall, the obtained findings can well contribute to the understanding of the relationship between students’ emotions and other variables in an attempt to support the development of adaptive learning technologies.

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