Introducing Scientific Approaches in Health Professions Education Research
Charlotte E. Rees
The University of Newcastle, Callaghan, New South Wales, Australia
Monash University, Clayton, Victoria, Australia
Search for more papers by this authorJeffrey J.H. Cheung,
University of Illinois at Chicago, Chicago, Illinois, USA
Search for more papers by this authorJonathan Fooand
Monash University, Clayton, Victoria, Australia
Search for more papers by this authorCharlotte E. Rees
The University of Newcastle, Callaghan, New South Wales, Australia
Monash University, Clayton, Victoria, Australia
Search for more papers by this authorJeffrey J.H. Cheung,
University of Illinois at Chicago, Chicago, Illinois, USA
Search for more papers by this authorJonathan Fooand
Monash University, Clayton, Victoria, Australia
Search for more papers by this authorCharlotte Rees
The University of Newcastle, Callaghan, New South Wales, Australia
Search for more papers by this authorLynn Monrouxe
The University of Sydney, Camperdown, New South Wales, Australia
Search for more papers by this authorBridget O'Brien
University of California San Francisco, San Francisco, California, USA
Search for more papers by this authorSummary
This chapter summarises common scientific methodologies in health professions education research (HPER). Scientific approaches aim to explain or predict regularities in the natural world based on relationships between variables and cause-effect inferences: hypothesis testing, randomisation, control, replicability, impartiality, predictive validity, and other features are therefore common in these approaches. The chapter explains the main indicators of quality employed in scientific approaches. Non-experimental scientific approaches in HPER are widespread, and include observational investigations such as correlational questionnaire studies, and exploratory work including descriptive questionnaires and measurement psychometrics. Minimisation of bias can be seen as attempts to minimise researcher practices or actions that could influence sampling, data collection, or interpretation, thereby threatening objectivity and neutrality. The chapter discusses the strengths and challenges of scientific approaches for HPER. It also discusses the philosophical underpinnings of scientific approaches to HPER — realist ontology, objectivist epistemology, and the values of empiricism, facts, objectivity, and dualism.
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