Literaturnachweis - Detailanzeige
Autor/inn/en | Pozón-López, I.; Kalinic, Zoran; Higueras-Castillo, Elena; Liébana-Cabanillas, Francisco |
---|---|
Titel | A Multi-Analytical Approach to Modeling of Customer Satisfaction and Intention to Use in Massive Open Online Courses (MOOC) |
Quelle | In: Interactive Learning Environments, 28 (2020) 8, S.1003-1021 (19 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Liébana-Cabanillas, Francisco) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1049-4820 |
DOI | 10.1080/10494820.2019.1636074 |
Schlagwörter | Online Courses; Large Group Instruction; Predictor Variables; Student Satisfaction; Intention; Educational Technology; Technology Uses in Education; Distance Education; Artificial Intelligence; Foreign Countries; Higher Education; Student Attitudes; Program Effectiveness; College Students; Interaction; Spain Online course; Online-Kurs; Prädiktor; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Distance study; Distance learning; Fernunterricht; Künstliche Intelligenz; Ausland; Hochschulbildung; Hochschulsystem; Hochschulwesen; Schülerverhalten; Collegestudent; Interaktion; Spanien |
Abstract | The purpose of this study is to classify the predictors of satisfaction and intention to use in Massive Open Online Courses (MOOC). Informed by a scientific literature review, this work poses a behavioral model to explain intention to use via various constructs. To this end, the authors have carried out a study through an online survey of Spanish Internet users. Two techniques were used: first, structural equation modeling (SEM) was approached to determine which variables had significant influence on MOOC adoption; in a second phase, the neural network model was used to rank the relative influence of significant predictors obtained by SEM. The analysis also shows that perceived satisfaction is affected by the quality of the course, its entertainment value and its usefulness. The latter variable also plays a major role when addressing user emotions. On the other hand, results from the neural network analysis confirmed many SEM findings and also provided a slightly different order of influence of significant predictors. The study provides an original focus in the study of perceived satisfaction and intention to use for MOOCs by extending the models proposed in previous research with regard to this emerging field. (As Provided). |
Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |