Combining multiple external representations and refutational text: An intervention on learning to interpret box plots

Box plots are frequently misinterpreted and educational attempts to correct these misinterpretations have not been successful. In this study, we used two instructional techniques that seemed powerful to change the misinterpretation of the area of the box in box plots, both separately and in combination, leading to three experimental conditions, next to a control condition. First, we used multiple external representations: Histograms were used as an overlay on box plots in order to give students a better insight in the way box plots represent data distributions. Second, we used refutational text to explicitly name and invalidate the area misinterpretation of box plots. Third, we combined multiple external representations and refutational text. A box plot test showed that students in the refutation and combination condition scored statistically significant better than students in the control condition with respect to the misinterpretation of interest. The condition with multiple external representations scored in between. The implications of these results for theory and educational practice are discussed.status: publishe