Educators' inaccurate use of causal language to describe non-causal data

Abstract

Previous research has documented that causal language is used inaccurately in a variety of areas including the general public, students, media articles, press releases, and scientific journal articles. The following study investigated the rate at which educators used inaccurate causal language to describe non-causal research descriptions. In order to accurately use causal language in their work, researchers need to conduct experiments that (1) manipulate the causal variable while measuring the other variable (Morling, 2018) and (2) meet the three causality criteria: covariance, temporal precedence, and internal validity (Morling, 2018). In this study, 223 educators read two non-causal research descriptions about parenting topics and then generated and selected headlines that would accurately describe the research that they read. Educators generated and selected more inaccurate causal headlines and less accurate non-causal headlines than expected. Moreover, the rate at which educators generated and selected inaccurate causal language was higher than the average of other reported rates in the literature. With these findings in mind, future research should investigate the rate of inaccurate causal language use in individuals who get specific training in correlation and causation as well as other teaching methodologies that may improve individuals' language accuracy.