Complexity classification framework for infographics
DOI:
https://doi.org/10.5753/rbie.2019.27.01.196Keywords:
Infographics, Classification, Complexity, Learning, FrameworkAbstract
Infographics have been used as learning materials due to their informative nature. Empirical evidence shows that this kind of visualization affects students’ learning and interest. However, providing further details on which parameters ensure positive results is still required. An example of such parameter is the complexity of the infographics. Therefore, there is a need to obtain information on the impact of infographics of different levels of complexity in learning. Observing the lack of guidelines to classify the complexity of infographics, we propose a framework that considers three dimensions (i.e., visual, verbal and conceptual) to score infographics and, generate a complexity measure. We carried out a controlled experiment to evaluate the framework and verify if our complexity measure reflects the real perception of the users. Our results showed that users learned more from infographics classified as low and medium complexity. We conclude that the complexity of an infographic is a factor that affects learning and should be considered by teachers and content creators when deciding to use infographics as learning materials.
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Copyright (c) 2019 Kamila Takayama Lyra, Rachel Reis, Wilmax Marreiro Cruz, Seiji Isotani
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