Visual portrayals of data and results at ITICSE

We present an analysis of the visual portrayals of data (including results) in the full papers and working group reports of ITiCSE from 2013 to 2018. We find that tables are the most common visual portrayal of data in these publications, but that a number of graphical forms are also widely used. We examine the quality of the data portrayals for tables, graphs, and images using visual quality indicators derived from the literature. Overall, our findings are not positive. We find that many papers present data in such a way that it cannot be readily interpreted. The most common problem is captions that do not adequately describe the table, figure, or image. In tables, the main issues affecting readability of numeric data are poor alignment of numbers within a column, unnecessary notations, and unwarranted precision. In graphs and images, the prevalent problem is text that is too small to be read. We conclude with guidelines for future authors to ITiCSE and other computing education venues, in the hope that we can contribute to an improvement in the quality of computing education publications.