Modelling Digital Knowledge Transfer: Nurse Supervisors Transforming Learning at Point of Care to Advance Nursing Practice
Journal Title: Informatics - Year 2017, Vol 4, Issue 2
Abstract
Limited adoption of mobile technology for informal learning and continuing professional development within Australian healthcare environments has been explained primarily as an issue of insufficient digital and ehealth literacy of healthcare professionals. This study explores nurse supervisors’ use of mobile technology for informal learning and continuing professional development both for their own professional practice, and in their role in modelling digital knowledge transfer, by facilitating the learning and teaching of nursing students in the workplace. A convenience sample of 27 nurse supervisors involved with guiding and supporting undergraduate nurses participated in one of six focus groups held in two states of Australia. Expanding knowledge emerged as the key theme of importance to this group of clinicians. Although nurse supervisors regularly browsed Internet sources for learning and teaching purposes, a mixed understanding of the mobile learning activities that could be included as informal learning or part of formal continuing professional development was detected. Participants need educational preparation and access to mobile learning opportunities to improve and maintain their digital and ehealth literacy to appropriately model digital professionalism with students. Implementation of mobile learning at point of care to enable digital knowledge transfer, augment informal learning for students and patients, and support continuing professional development opportunities is necessary. Embedding digital and ehealth literacy within nursing curricula will promote mobile learning as a legitimate nursing function and advance nursing practice.
Authors and Affiliations
Carey Mather and Elizabeth Cummings
Keywords
Related Articles
- EP ID EP44079
- DOI https://doi.org/10.3390/informatics4020012
- Views 267
- Downloads 0
Improving the Classification Efficiency of an ANN Utilizing a New Training Methodology
In this work, a new approach for training artificial neural networks is presented which utilises techniques for solving the constraint optimisation problem. More specifically, this study converts the training of a neur...
Data Provenance for Agent-Based Models in a Distributed Memory
Agent-Based Models (ABMs) assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual...
The Effects of Motion Artifacts on Self-Avatar Agency
One way of achieving self-agency in virtual environments is by using a motion capture system and retargeting user’s motion to the virtual avatar. In this study, we investigated whether the self-agency is affected when mo...
Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions
Making sense of complex objects is difficult, and typically requires the use of external representations to support cognitive demands while reasoning about the objects. Visualizations are one type of external representat...
Multidimensional Data Exploration by Explicitly Controlled Animation
Understanding large multidimensional datasets is one of the most challenging problems in visual data exploration. One key challenge that increases the size of the exploration space is the number of views that one can gen...