Abstract
User preferences for indicating uncertainty using specific visual variables have been explored outside of educational reporting. Exploring students’ preferred method to indicate uncertainty in open learner models can provide hints about which approaches students will use, so further design approaches can be considered. Participants were 67 students exploring 6 visual variables applied to a learner model visualisation (skill meter). Student preferences were ordered along a scale, which showed the size, numerosity, orientation and added marks visual variables were near one another in the learner’s preference space. Results of statistical analyses revealed differences in student preferences for some variables with opacity being the most preferred and arrangement the least preferred. This result provides initial guidelines for open learner model and learning dashboard designers to represent uncertainty information using students’ preferred method of visualisation.
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Al-Shanfari, L., Baber, C., Demmans Epp, C. (2017). Student Preferences for Visualising Uncertainty in Open Learner Models. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_37
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DOI: https://doi.org/10.1007/978-3-319-61425-0_37
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