Technological tools for virtual teaching and their effect on the satisfaction of online learning

Chamorro-Atalaya, Omar; Alvarado-Bravo, Nestor; Aldana-Trejo, Florcita; Huarcaya-Godoy, Madison; Santos, Marco Anton-De los; Santos, Juan Anton-De los; Fierro-Bravo, Maritte

doi:10.11591/ijeecs.v25.i3.pp1634-1643

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…The paradigm shift from offline to online mode of teaching was the need of the hour during the COVID-19 pandemic. Looking at the advantages of the online classroom, many educational institutions are imparting instruction in either fully online or blended mode even after the subsiding of the pandemic [20], [21]. Hence in online teaching, the major challenge for a teacher to detect student attentiveness still remains.…”

Section: Methodsmentioning

confidence: 99%

An adaptive system for predicting student attentiveness in online classrooms

Bansal

2023

IJEECS

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The effectiveness of teaching methods is determined by whether a student is attentive in a lecture or not. In face-to-face classroom teaching, a teacher is able to judge whether students are understanding the subject, based on their facial expressions. However, since the uprise of COVID-19 pandemic, virtual classrooms have found a holding in the field of education and detecting attentiveness of students is a challenge in the same. This paper proposes a student attentiveness model that would detect and monitor a student’s eye state to determine their level of attentiveness and provide a real-time feedback mechanism to the teacher. The proposed model employs a histogram of oriented gradient (HOG) method in conjunction with support vector machine (SVM) algorithm for face recognition. It then computes an adaptive eye aspect ratio (AEAR) for each individual student to determine their level of attentiveness. The model is tested on a real-time dataset and validated using classifiers (SVM, decision tree, and random forest). The results of the classifiers verify that the model produces an accuracy of more than 92%.

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Section: Methodsmentioning

confidence: 99%

An adaptive system for predicting student attentiveness in online classrooms

Bansal

2023

IJEECS

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“…The problem of satisfaction with the online learning process is now relevant and is being actively considered by researchers [3,4,[8][9][10][11][12]. Satisfaction with distance learning is understood as an integrated concept reflecting the degree of realization of a student's social expectations from educational activities at the university, formed in the process of their socialization [13]; the subjective, emotionally colored assessment of the quality of certain objects and the conditions of educational activity, including interpersonal relationships [14]; emotional and personal attitude, which consist of motivation and subjective experiences associated with the process and result of achieving the goal [15].…”

Section: Introductionmentioning

confidence: 99%

Students Satisfaction with Online Higher Education during the COVID-19 Pandemic

Arsenijević¹,

Belousova

Tushnova

2023

Education Sciences

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The digital educational environment is not new in the modern world, but in the context of the COVID-19 pandemic, the transition to online learning has become necessary and fast. This offered the possibility to study various characteristics of objects and subjects in the digital educational environment. During the pandemic, universities worldwide were forced to switch to online learning, creating a global educational experiment with results to be comprehended and theoretically reflected upon. The significance of this scientific reflection is important for understanding the characteristics and factors that influence student satisfaction with online learning, as well as for anticipating possible ways to improve its effectiveness. This research aimed to study the characteristics of satisfaction with online learning during the COVID-19 pandemic in connection with the elements of the Community of Inquiry (CoI) online learning model. The study involved 808 students (M = 22.5, SD = 2.4 (53.3% men)) from 6 countries (Serbia—30.8%, Bosnia and Herzegovina—8.5%, Croatia—8.9%, Romania—21.8%, Russia—25.2%, Slovenija—4.7%). A total of 808 students responded to a questionnaire measuring the levels of cognitive, social, and teaching presence in distance learning. Satisfaction with online learning has been shown to positively correlate with cognitive, social and teaching presence, and overall CoI presence. The results of the Kruskal-Wallis test showed that satisfaction with online learning does not differ among students with different levels of academic performance; however, the subjective assessment of the element of social presence “Tools and platforms for online learning allow students to work with each other” is significantly higher among students with low academic performance. Satisfaction with online learning and the elements of the CoI model is different in study groups with varying degrees of online learning presence, as well as different in students whose training included different elements of online learning. The conclusions obtained in this study will make it possible to organize the digital educational environment more effectively by managing the elements of the CoI model.

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Empowering Faculty Vitality and Mitigating Burnout Through Generative AI in Higher Education

Ybarra

2024

Transforming Education With Generative AI

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In today's dynamic landscape of higher education, the pervasive issue of faculty burnout has emerged as a pressing concern, casting a shadow over the well-being of educators and the overall quality of instruction. This chapter proposal embarks on an exploration of how generative artificial intelligence (AI) can act as a transformative force within higher education, specifically focusing on its potential to empower faculty members, enhance pedagogical practices, and mitigate the alarming prevalence of burnout. The chapter's central objectives are multifaceted, commencing with a comprehensive examination of the multifaceted phenomenon of faculty burnout. This includes an analysis of the contributing factors such as the escalating workloads, the shift towards online and blended learning modalities, and the overwhelming administrative duties that educators must shoulder. The aim here is to illuminate the multifaceted nature of burnout, thereby fostering an enhanced understanding of its urgency and the critical need for sustainable solutions.

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Technological tools for virtual teaching and their effect on the satisfaction of online learning

Cited by 3 publications

References 12 publications

An adaptive system for predicting student attentiveness in online classrooms

An adaptive system for predicting student attentiveness in online classrooms

Students Satisfaction with Online Higher Education during the COVID-19 Pandemic

Empowering Faculty Vitality and Mitigating Burnout Through Generative AI in Higher Education

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