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Due to the COVID‐19 epidemic crisis, students from higher education institutions around the world are forced to participate in comprehensive online curriculums. In such a scenario, it is worth investigating how students perceived their learning outcomes and satisfaction based on this method of teaching and learning online. This study aims to explore the role of six factors, namely, system quality, course design, learner‐learner interaction, learner‐instructor interaction, learner‐content interaction, and self‐discipline, on university students' perceived learning outcomes and their effect on student satisfaction with online curricula during the COVID‐19 epidemic. A structural equation modelling technique was used to assess survey questionnaires obtained from 457 validated students at a Public University in China. The results demonstrated that these determinants had a positive effect on satisfaction and learning outcomes, whereas learner‐instructor interaction had no significant effect. Furthermore, the strongest determinant that affected not only students' satisfaction but also their learning outcomes was the learner‐content interaction. Lay Description: What is already known about this topic?: Online teaching can support students' learning in COVID‐19 epidemic.Various determining factors affect students' learning outcomes and satisfaction towards online learning. What this paper adds?: This study investigates six determinants on students' learning outcomes and satisfaction towards online learning.Learner‐content interaction yielded a stronger effect on university students' learning outcomes and satisfaction.Learner‐instructor interaction has no significant effect. Implications for practice and/or policy: System quality, course design, learner‐learner interaction, learner‐content interaction, and self‐discipline, had a positive impact on university students' perceived learning outcomes and satisfaction in COVID‐19. [ABSTRACT FROM AUTHOR]

Digital competence is critical for university students to adapt to and benefit from digitally enhanced learning. Prior studies on its measurement mostly focus on educators and relied on factor analyses. However, there is a lack of valid and convenient tools to measure university students' digital competence. This study aimed to develop a digital competence scale for university students (DC‐US) in digitally enhanced learning with robust psychometric properties. An initial DC‐US with 23 items was proposed to measure the single latent trait of digital competence. It was validated and refined continuously through a pilot study, a main study and a predictive validity study in three datasets involving 825 participants altogether, using factor analyses, Rasch analyses and the partial least squares modelling. The final DC‐US turned out to comprise two subscales: technical literacy and digital skills, with 10 items retained, and manifested high internal consistency, unidimensionality and measurement invariance. The scale also demonstrated strong predictive validity, with technical literacy greatly predicting digital skills, which negatively predicted technostress. The DC‐US enables instructors and school administrators to conveniently obtain preliminary information of university students' digital competence, informing their digital class preparation and development of timely interventions for addressing digital deficiencies. Lay Description: What is already known about this topic?: Digital competence is critical for university students to adapt to and benefit from digitally enhanced learning (DEL).There is a lack of valid and convenient tools to measure university students' digital competence.Prior studies on its measurement mostly focus on educators and relied on factor analyses. What this paper adds?: A unidimensional, valid and unbiased digital competence scale was developed for university students.Rasch analyses and classical test theory were employed jointly for the scale development.The digital competence scale comprised two subscales: Technical literacy and digital skills. Implications for practice: University students can use the scale for a quick self‐assessment of their digital competence before joining DEL.Instructors can use the scale to gain an initial knowledge of their students' digital competence to inform digital class preparation.University administrators can rely on the scale to quickly evaluate the implementation effectiveness of DEL schemes. [ABSTRACT FROM AUTHOR]