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Exploring non-linear relationships between perceived interactivity or interface design and acceptance of collaborative web-based learning.
Al-Sayid, Fareed; Kirkil, Gokhan.
Afiliação
  • Al-Sayid F; Industrial Engineering Department, Faculty of Graduate Students, Kadir Has University, Istanbul, Turkey.
  • Kirkil G; Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey.
Educ Inf Technol (Dordr) ; : 1-48, 2023 Feb 27.
Article em En | MEDLINE | ID: mdl-37361814
The novelty of this study is in developing a conceptual model for predicting the non-linear relationships between human-computer interaction factors and ease of use and usefulness of collaborative web-based learning or e-learning. Ten models (logarithmic, inverse, quadratic, cubic, compound, power, s-curve, growth, exponential, and logistic) were examined as functions of effects compared to linear relationships to see which was the most appropriate, based on R2, adjusted R2 and SEE values. To answer the addressed questions, the researcher surveyed 103 students from Kadir Has University about the perceived interface and interactivity of e-learning. The results show that most of the hypotheses formulated for this purpose have been proven. Our analysis shows that cubic models (the relationship between ease of use and usefulness, visual design, course environment, learner-interface interactivity, and course evaluation system and ease of use), quadratic models (the relationship between visual design, and system quality and usefulness, course structure and content, course environment, and system quality and ease of use), logarithmic model (the relationship between course evaluation system and usefulness), and s-curve models (learner-interface interactivity, navigation, and course structure and content and usefulness) performed better in the description for the correlations. Supplementary Information: The online version contains supplementary material available at 10.1007/s10639-023-11635-6.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article