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dc.contributor.authorMalinovski, Tonien_US
dc.contributor.authorVasileva-Stojanovska, Tatjanaen_US
dc.contributor.authorJovevski, Dobrien_US
dc.contributor.authorVasileva, Marinaen_US
dc.contributor.authorTrajkovik, Vladimiren_US
dc.date.accessioned2023-03-09T08:15:58Z-
dc.date.available2023-03-09T08:15:58Z-
dc.date.issued2015-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/26057-
dc.description.abstractDistance education learning environments provide tremendous convenience and flexibility, allowing busy, mobile adult learners to engage in education while coping with their limited resources in terms of time, energy and finances. Following a student-centered approach this study investigates adult students’ subjective perceptions while using distance education systems based on a videoconferencing platform as Quality of Experience (QoE). Based on a literature review, sociological behavior and expectations, we have constructed a structural equation model (SEM) illustrating relations among different variables that can predict positive levels of adult students’ QoE, thus providing guidelines for proper development. We have tested the model using a survey of 198 primary education school teachers involved in a videoconferencing-based learning program for teacher enhancement. Results show a good fit to the model developed. The analysis showed that adult students’ QoE is directly influenced by appropriateness of teacher-student interaction and ease of participation, as well predicted by students’ motivation to attend similar trainings. Additionally, we found that variances in technical quality did not directly influence their QoE from the learning sessions.en_US
dc.publisherInforming Science Instituteen_US
dc.relation.ispartofJournal of Information Technology Education. Researchen_US
dc.subjectQuality of Experience, adult students, distance education, lifelong learning, videoconferencing, structural equation modelingen_US
dc.titleAdult Students' Perceptions in Distance Education Learning Environments Based on a Videoconferencing Platform–QoE Analysisen_US
dc.typeJournal Articleen_US
item.grantfulltextopen-
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Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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