Houston, we Have a Pandemic: Technical Difficulties, Distractions and Online Student Engagement

Kostaki, Dimitra; Karayianni, Irene

doi:10.31219/osf.io/6mrhc

Cited by 14 publications

(13 citation statements)

References 30 publications

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“…Low levels of technical difficulties perception, respectively, of diversity of techniques are associated with high levels of online learning engagement, while high levels of online self-efficacy are associated negatively with technical difficulties perception, respectively, with diversity of techniques, which confirms the fact that there is variability in the modality of students' answers. The more recent literature on this topic (Kostaki and Karayianni, 2021) points out that self-efficacy moderates the relation between technical difficulties and learning engagement, therefore students who were not confident in their computer skills and encountered technical difficulties had lower engagement scores than those with higher online self-efficacy facing a similar situation, which opens new directions in research.…”

Section: Sources Of Stress and Learning Engagementmentioning

confidence: 99%

Predictors of Learning Engagement in the Context of Online Learning During the COVID-19 Pandemic

et al. 2022

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The main aim of the present research is to analyze the predictive value of individual characteristics such as online self-efficacy, adaptability to uncertainty, and sources of stress during online learning on learning engagement. We also aimed to highlight if these relationships could be mediated by the online self-regulated learning strategies, during the COVID-19 pandemic. The participants were 529 university students and the design was cross-sectional. The results showed significant associations of the sources of stress in online learning with self-efficacy, leaning engagement and self-regulated learning strategies. Self-regulated strategies—task strategies and goal setting represent mediators of stressors perceived by the students under the conditions of the sudden shift to online activity and online learning engagement. The most relevant self-regulation strategies seemed to be goal setting and task strategies, which confirm the need for a clear structure of learning in the context of online activities. The implications of this study reside in the increased awareness regarding how learning engagement in online learning can be predicted by individual characteristics.

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Section: Sources Of Stress and Learning Engagementmentioning

confidence: 99%

Predictors of Learning Engagement in the Context of Online Learning During the COVID-19 Pandemic

et al. 2022

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“…Some early studies exploring online learning as part of the response to the global pandemic have been published, showing a mixed picture. Kostaki and Karayianni ( 2021 ) explored student engagement in online courses during the pandemic to find an unsurprising negative correlation with technical difficulties. Garris and Fleck ( 2020 ) surveyed students across the US to ask them to provide an evaluation of one of their online courses.…”

Section: Introductionmentioning

confidence: 99%

Identifying factors influencing study skills engagement and participation for online learners in higher education during COVID‐19

Fabian

Smith

Taylor‐Smith

et al. 2022

Brit J Educational Tech

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The COVID‐19 pandemic disrupted education across the world as campuses closed to restrict the spread of the virus. UK universities swiftly migrated to online delivery. The experiences of students and staff during this transition can inform our return to campus and our ability to deal with future disruption. This study draws on Moore's theory of transactional distance to understand factors influencing student study skills engagement and participation in online learning during this period. We surveyed students ( n = 178) in a computing school at a UK university. A partial least squares (PLS) analysis was used to explore the influence of transactional distance (between students/teachers and between students/students), access to e‐learning capital, and perceived usefulness on two measures: study skills engagement and participation in online collaborative activity. Results show that transactional distance influences participation, and e‐learning capital influences study skills engagement. Our findings suggest that if universities continue with aspects of online learning for previously on‐campus students they should provide access to infrastructure and training on utilising the online ecosystem to avoid disadvantaging students. Further investment in students' e‐learning capital, such as signposting and adapting existing resources, is also necessary to support this key influence in study skills engagement. Practitioner notes What is already known about this topic Moore's transactional distance theory recognises that the significant distance of distance learning is not of time or place, but rather a communication and psychological distance between the learner and teacher that is affected by the structure of the course, the dialogue between the learner and teacher, and the autonomy of the learners. Transactional distance affects student engagement. Studies using Davis' technology acceptance model have found perceived usefulness of the virtual learning environment to be an important factor in student engagement with online learning. Computer self‐efficacy is a factor related to engagement with digital learning technologies. What this paper adds This study identifies the relationship between factors of transactional distance (transactional distance between student and teacher TDST and transactional distance between students TDSS) with study skills engagement and participation, as mediated by perceived usefulness. We introduce the term e‐learning capital as a measure of self‐expressed ability (skills and resources) to utilise the online learning environment. This e‐learning capital influences students study skills engagement but not participation. Transactional distance between students and teacher did not directly affect study s...

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“…Additional factors potentially contributing to the overall dissatisfaction with the course include the lack of clinical experiences in the redesigned ophthalmology curriculum, reduced digital efficacy and technical issues. Kostaki et al found that student engagement negatively correlated with technical difficulties and home distractions [ 47 ]. Furthermore, they reported that computer self-efficacy positively contributed towards engagement as students could remedy technical difficulties [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

“…Kostaki et al found that student engagement negatively correlated with technical difficulties and home distractions [ 47 ]. Furthermore, they reported that computer self-efficacy positively contributed towards engagement as students could remedy technical difficulties [ 47 ]. Brockman et al compared student perceptions of an online or in-person microbiology laboratory and found that while students have positive perceptions of digital online activities there was still a significant preference for a blend of online and in-person practical activities [ 48 ].…”

Section: Discussionmentioning

confidence: 99%

How has medical student learning changed with the pivot to online delivery of ophthalmology in the pandemic?

Gabhann-Dromgoole

Murphy

Boland³

et al. 2023

PLoS ONE

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Purpose This study aimed to measure stakeholder satisfaction with our usual delivery format, which previously relied on a blend of didactic lectures and clinical skills sessions compared to a revised format, which had more emphasis on online learning. We hypothesised that the online flipped classroom (OFC) would facilitate delivery of content in the wake of the pandemic, and result in improved levels of student satisfaction and knowledge gain. Design Non randomised intervention study. Group 1 = Traditional delivery (TD) and Group 2 = OFC group. Methods A validated course evaluation questionnaire (CEQ) compared perspectives of teaching faculty (n = 5) and students with the traditional delivery (TD) of the 4th year ophthalmology clinical attachment and an OFC approach (TD n = 129 v OFC n = 114). Results The OFC group (n = 114; response rate = 24.6%) reported significantly reduced satisfaction with staff motivation of students and provision of feedback, compared to TD (n = 129; response rate = 17.8%). OFC students also felt it was harder to determine what standard of work was expected and found the course less beneficial at helping develop problem-solving skills. Students were dissatisfied with the level of choice afforded by the OFC, specifically how they would learn and assessment options. No significant difference in exam score was observed between the TD and OFC groups. For faculty (n = 5), there was no evidence of a difference between OFC and TD. Conclusions Students indicated a preference for the TD compared to the OFC approach. However, both delivery approaches led to comparable student performances as determined by MCQ examination.

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Houston, we Have a Pandemic: Technical Difficulties, Distractions and Online Student Engagement

Cited by 14 publications

References 30 publications

Predictors of Learning Engagement in the Context of Online Learning During the COVID-19 Pandemic

Predictors of Learning Engagement in the Context of Online Learning During the COVID-19 Pandemic

Identifying factors influencing study skills engagement and participation for online learners in higher education during COVID‐19

How has medical student learning changed with the pivot to online delivery of ophthalmology in the pandemic?

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