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Developing a multi-method approach to data collection and analysis for explaining the learning during simulation in
Andrew J Bland1, Jane Tobbell2
1Department of Nursing & Health Sciences, University of Huddersfield, UK.
Nurse Education in Practice
|August 26, 2015
Summary
This study introduces a new method for analyzing learning in nursing simulation. Dynamic data collection and analysis reveal how student nurses interact with context during simulations.
Area of Science:
- Nursing Education
- Learning Sciences
Background:
- Simulation is a key component of undergraduate nurse education.
- Current research methods may limit understanding of learning mechanisms in simulation.
- Distributed learning theories emphasize the interaction of individual identity and context.
Purpose of the Study:
- To detail a novel data collection and analysis method for simulation-based education.
- To capture the interaction of individuals within simulation experiences.
- To enable analysis through multiple lenses, including context and participant/researcher perspectives.
Main Methods:
- Grounded theory approach with 31 third-year undergraduate student nurses.
- Data collection via non-participant observation and digital recordings.
- Analysis through focus group deconstruction of recorded simulations by participants and researchers.
Main Results:
- The method captured dynamic, multi-level data on the simulation experience.
- It allowed for analysis of learning through the interaction of individual identity and context.
- Focus group interviews provided further clarification and depth.
Conclusions:
- Understanding student learning in simulation requires dynamic data.
- This method facilitates unpacking learning as it unfolds in action.
- It supports analysis of social and active learning strategies in simulation.
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