Abstract
BACKGROUND
Undergraduates’ workplace learning is an important part of health sciences education. Educational psychology research considers many different aspects of self-regulated learning at the workplace, including cognition, motivation, emotions, and context. Multivariate longitudinal and diary studies in this field require fewer items than alternatives or even a single item per construct and can reveal the sub-processes of workplace learning and contribute to a better understanding of students’ learning. Short instruments are necessary for application in workplace settings, especially stressful ones, to mitigate survey fatigue. The present study aimed to assess the psychometric properties of single items measuring various aspects of workplace learning.
METHODS
Twenty-nine single items selected from the Workplace Learning Inventory in Health Sciences Education were analyzed for reliability, information reproduction, and relationships within the nomological network. The authors additionally analyzed four generally formulated single items’ relationships with the full Workplace Learning Inventory scales and external criteria within the nomological network. Participants were 214 ninth- or tenth-semester veterinary medicine students in Austria and Germany who were learning at varied workplaces during the winter semester of 2021/2022.
RESULTS
Of the 29 single items selected from existing scales, 27 showed sufficient reliability, but mixed results were obtained regarding validity. Although the items’ relationships within the nomological network were similar to those of the full scales, information reproduction was insufficient for most items. The four general single items showed acceptable validity, but the reliability of these measures of states could not be assessed.
CONCLUSIONS
This paper reported findings on the psychometric properties of single items for undergraduates’ workplace learning in health science education. The findings are crucial for deciding whether to use scales versus single-item measures in future studies. By applying the findings, researchers can be more economical in their workplace learning data collection and can include more constructs.
