Student satisfaction with videoconferencing teaching quality during the COVID-19 pandemic

Fatani, Tarah

doi:10.1186/s12909-020-02310-2

Cited by 190 publications

(171 citation statements)

References 29 publications

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“…Therefore, instructors play an important role in enhancing the concentration, motivation, and level of understanding of learners, and facilitating quality online learning, in particular when the class is conducted through video conferencing tools. This was in line with the study conducted by Fatani (2020) and Alqurashi (2018) which showed the importance of instructor presence and instructor-learner interaction based on the community of inquiry (COI) framework [20,43].…”

Section: Important Predictorssupporting

confidence: 90%

“…Therefore, the technical barrier or underdeveloped infrastructure was not likely the key factor contributing to the low satisfaction score on ERL. This supported the finding observed from another recent study conducted by Fatani (2020) that technical issues (audio/visual) were not the significant determinants of student satisfaction using ERL during the pandemic [20]. Both studies somewhat echoed and associated with the idea raised by Alqurashi et al (2018) that computer and internet self-efficacies were not important in determining student satisfaction in online learning [43].…”

Section: Important Predictorssupporting

confidence: 85%

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Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques

2021

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Despite the wide adoption of emergency remote learning (ERL) in higher education during the COVID-19 pandemic, there is insufficient understanding of influencing factors predicting student satisfaction for this novel learning environment in crisis. The present study investigated important predictors in determining the satisfaction of undergraduate students (N = 425) from multiple departments in using ERL at a self-funded university in Hong Kong while Moodle and Microsoft Team are the key learning tools. By comparing the predictive accuracy between multiple regression and machine learning models before and after the use of random forest recursive feature elimination, all multiple regression, and machine learning models showed improved accuracy while the most accurate model was the elastic net regression with 65.2% explained variance. The results show only neutral (4.11 on a 7-point Likert scale) regarding the overall satisfaction score on ERL. Even majority of students are competent in technology and have no obvious issue in accessing learning devices or Wi-Fi, face-to-face learning is more preferable compared to ERL and this is found to be the most important predictor. Besides, the level of efforts made by instructors, the agreement on the appropriateness of the adjusted assessment methods, and the perception of online learning being well delivered are shown to be highly important in determining the satisfaction scores. The results suggest that the need of reviewing the quality and quantity of modified assessment accommodated for ERL and structured class delivery with the suitable amount of interactive learning according to the learning culture and program nature.

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Section: Important Predictorssupporting

confidence: 90%

Section: Important Predictorssupporting

confidence: 85%

Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques

2021

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“…Universities stopped face-to-face education and have been advised to rapidly offer online learning tools [ 7 ]. University staff and educators had to meet new online education challenges: demonstrating pedagogical skills in an online classroom, addressing their managerial role, establishing relationships with students, and providing technical support [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Facing COVID-19 Challenges: 1st-Year Students’ Experience with the Romanian Hybrid Higher Educational System

Potra

Pugna

Pop

et al. 2021

IJERPH

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First-year students undergo several transformations like the transition from high school to university schedules, teaching methods, and discipline specificities to social changes that come with meeting new colleagues or moving to other locations far from family and friends. The COVID-19 outbreak brought additional concerns and uncertainties once educational systems implemented distance learning schemes for public health management. Nevertheless, higher educational organizations preferred to implement hybrid approaches for student engagement motivation and high dropout rate avoidance. In Romania, such an educational system has been applied with caution. Since the pandemic needs to be understood as an opportunity for adaptation and education improvements, the purpose of the present paper is to uncover lessons learned and to develop a systematized model based on students’ perception regarding face-to-face, online and hybrid systems. For this reason, a grounded theory approach has been preferred. Thus, 149 Romanian students enrolled in the first year in engineering specialities with ages between 18–26 years both male (50.3%) and female (49.7%) have answered the research questions in an online environment due to pandemic restrictions. Based on the online asynchronous student interviews, 220 codes and a further 13 categories have been developed. After a pertinent analysis of the relationships between categories and relevant literature sorting, a theoretical model for the Romanian higher educational current pandemic situation has been proposed. The main face-to-face and online education characteristics are outlined, the hybrid approach becoming a bridge between the two systems. Management implications are outlined together with further research directions.

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“…COVID-19 disease has popularized video conferencing tools for synchronous teaching sessions, meeting, or tutoring. Students feel highly satisfied with the videoconferences teaching quality [47]. However, different difficulties with this system might be underlined, such as class rhythm, problems for interacting with the teachers and peers, attention and procrastination issues, etc.…”

Section: Infrastructure Layermentioning

confidence: 99%

Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education

García-Peñalvo

2021

Sustainability

105

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The purpose of this paper is to define a reference framework for introducing eLearning practices in mainly face-to-face higher education institutions. We suggest a suitable adoption and management of associated infrastructures and processes, in order to guarantee the ethical use of data in the related academic and learning analytics. A theoretical framework is proposed after years of practice and experience in the institutional government of IT processes related to learning technology. The digital transformation of teaching should imply the right technological decisions made by people and for people, in order to achieve a more inclusive, participative, and human university supported by technology. digital transformation is a social requirement of governments, companies, and institutions, and it should take into account the associated risks of the unethical use of technology, which leads to the dark side of transformation processes. eLearning approaches, especially with the influence of the COVID-19 outbreaks, are increasing the need for digital mechanisms in universities. Further, there is a need for strategical support and reference models if we are to avoid these undesired effects.

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Student satisfaction with videoconferencing teaching quality during the COVID-19 pandemic

Cited by 190 publications

References 29 publications

Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques

Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques

Facing COVID-19 Challenges: 1st-Year Students’ Experience with the Romanian Hybrid Higher Educational System

Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education

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