Thinking Critically About Data Displays by Luke Duesberry, Jenelle Braun-Monegan, Kimy Liu, and Jan McCoy
The quality of a data display can have an impact on the interpretation of those data. A survey of the literature indicates that data displays can vary in quality of accuracy, clarity, and efficacy. In this study we develop and apply an evaluative rubric to graphs in a sample of six education journals: three research and three practitioner. Results indicate that graph quality is typically high in educational journals, however, in practitioner oriented journals issues around graph clarity and efficacy should be addressed. Common error patterns are pinpointed, and four recommendations are made to authors and editors: focus on meaningful labels, increase amount of data displayed, portray multiple relationships, and elaborate with supporting text.