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Objective: The complementary medicine (CM) education sector is maturing as evidenced by rising professionalization and improved educational standards. However, despite the substantial size of the CM industry the education of existing and future CM practitioners has received little research attention. The aim of the study reported here is to explore the perceptions of CM teaching academics (working across the university and nonuniversity CM education sector) to the use of learning technologies in their work. Methods: An online survey was administered to academic staff (n = 80) at two key CM education provider institutions, one in Australia and one in the United States. Academics were questioned regarding four specific domains: their demographics; their perceptions and experiences of technologies in general; their perceptions of the changing face of CM education and the role of the CM teacher in general; and their perceptions of their institution's infrastructure, progress, and support regarding learning technologies. Results: Respondents reported having taught for a mean of 9.6 years overall and a mean of 5.3 years at their current institution. More respondents identified as female, and most participants were employed on duration-specific contracts (n = 57, 72.2%). A majority of permanent employees (71%) reported not currently being in clinical practice, while most contract employees (82%) were in clinical practice. Participants reported that teaching practice was changing due to the availability of learning technologies (mean 4.2: standard deviation [SD] 0.79) and that confidence and capability with digital technologies were essential to being a successful academic (mean 4.2: SD 0.74). Contracted academics were significantly more in agreement than the tenured academics with regards to their institution being more advanced with regards to the effective use of digital technologies (p = 0.025). Tenured academics were significantly more likely than the contracted academics to perceive themselves as having a positive influence upon recommendations for new technologies to be adopted by their institution (p = 0.001), as well as input to decision-making about which technologies are implemented in their area of work (p |
