Exploring the intention to use a clinical imaging portal for enhancing healthcare education

Exploring the use of standardized patients for simulation-based learning in preparing advanced practice nurses

“…However, we did not measure the relationship between perceived usefulness and learning outcomes in the study. Most research studies examined the relationship of perceived usefulness and behavior intention to use new technology in healthcare education (Chow et al, 2012(Chow et al, , 2013, but did not investigate using SPs. Further investigation on this aspect in using SPs for simulation-based learning is highly recommended.…”

Discovering online learning barriers: survey of health educational stakeholders in dentistry

“…The stakeholders involved in online dental learning from nine countries were invited to complete the online Survey of Barriers in Online Learning Education in Health Professional Schools (SBOLEHPS). This survey was developed by the authors to cover aspects of known barriers in the literature (6): support (including financial) and resources (12,13,18,23), developmental issues and concerning the online learning tool itself (14,15,18), concerning the end-users (11,16,18,19), faculty attitudes and barriers (23-25), and cognitive abilities (i.e. computer self-efficacy) (13).…”

Learner control, user characteristics, platform difference, and their role in adoption intention for MOOC learning in China

“…In the field of elearning, TAM could not only be used for predicting adoption behavior, but also for measuring the learning satisfaction, continuous intention to use e-learning (Pereira, Ramos, Gouvêa, & Costa, 2015), loyalty to elearning (Sánchez-Franco, Peral-Peral, & Villarejo-Ramos, 2014), course outcomes, and academic performance using e-learning (Arbaugh, 2014). The features of technology: interactivity, personalisation, accessibility, mobility, and the choice of media to present the contents (Agudo-Peregrina, Hernández-García, & Pascual-Miguel, 2014); individual characteristics such as personal innovativeness in information technology, computer self-efficacy, and demographic variables (Chow et al, 2013;Thatcher & Perrewe, 2002);the course characteristics of learning resources, course content, tutor quality, and course quality (Persico, Manca, & Pozzi, 2014;Teo, 2014); and other variables such as social influence (or social norm) and flow (Wu & Zhang, 2014), are incorporated into TAM to enhance the understanding of adopting. In summary, TAM has been widely used in predicting e-learning adoption and proved to be robust.…”