The measurement of unobservable variables is what we focus on in this primer. Other variables that researchers may want to measure are not directly observable, such as students’ attitudes, feelings, and knowledge. For example, the percent of international students in a class or the amount of time students spend on a specific task can both be directly observed by the researcher. Some variables measured in education studies are directly observable. Measuring Variables That Are Not Directly Observable In this primer, we walk the reader through important validity aspects to consider and report when using surveys in their specific context. This will allow education researchers to produce more rigorous and replicable science. As a community, biology education researchers need to move beyond simply adopting a “validated” instrument to establishing the validity of the scores produced by the instrument for a researcher’s intended interpretation and use. As biology education researchers who use surveys, we need to understand both the theoretical and statistical underpinnings of validity to appropriately employ instruments within our contexts. While this shift is a methodological advancement, as a community of researchers we still have room to grow. Andrews et al., 2017 Wachsmuth et al., 2017 Wiggins et al., 2017). This shift may be due to researchers’ increased recognition of the amount of work that is necessary to create and validate survey instruments (cf. In recent years, researchers have begun adopting existing measurement instruments. Generally, each question on these instruments asked about something different and did not involve extensive use of measures of validity to ensure that researchers were, in fact, measuring what they intended to measure ( Armbruster et al., 2009 Rissing and Cogan, 2009 Eddy and Hogan, 2014).
In the early days of biology education research, researchers designed their own surveys (also referred to as “measurement instruments” 1) to obtain information about students. Surveys and achievement tests are common tools used in biology education research to measure students’ attitudes, feelings, and knowledge.
THE USE OF SURVEYS IN BIOLOGY EDUCATION RESEARCH For education researchers using surveys, understanding the theoretical and statistical underpinnings of survey validity is fundamental for implementing rigorous education research.
#Concept of validity and reliability in research software
We provide example data, annotated code, and output for analyses in R, an open-source programming language and software environment for statistical computing. This use of factor analysis is illustrated throughout by a validation of Diekman and colleagues’ goal endorsement instrument for use with first-year undergraduate science, technology, engineering, and mathematics students. The essential steps to conduct and interpret a factor analysis are described. Factor analysis helps researchers explore or confirm the relationships between survey items and identify the total number of dimensions represented on the survey. It then focuses on factor analysis, a statistical method that can be used to collect an important type of validity evidence. This article briefly reviews the aspects of validity that researchers should consider when using surveys. Yet, this step is frequently skipped or is not reported in educational research.
Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Across all sciences, the quality of measurements is important.
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