From 2012From until 2016, the number of US students enrolled in an online course increased 14.68%, resulting in more work for online teachers, who are responsible for planning and making pedagogical decisions to guide students. Interactions in such courses can generate data (quantity and variety), where relevant information in the educational context can be extracted, assisting teachers managing their classes. However, to present these data in spreadsheets, tables and graphics, is not enough. In this context, some authors suggest using data visualization to communicate information clearly and efficiently from the point of view of users, helping them analyze and reason about the data. However, people react differently to different types of visualization, which we categorized in two broad groups: traditional or non-traditional. We evaluated how users reacted to these types of visualizations and what users' features are associated with their preferences for one category or the other. In this paper, we surveyed 235 teachers to evaluate how these two categories of visualizations affect the way participants evaluate data from an online course. They had to check the visualizations and identify which item contributed the most, and which item contributed the least to the performance of the students. The answers (correct or incorrect) were evaluated regarding the teachers': age, gender, experience, education and perception on the usefulness of each visualization. Our ultimate purpose was to create a model to recommend visualizations according to the teachers' profile.

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