Abstract
Many STEM problems involve visuals. To benefit from these problems, students need representational competencies: the ability to understand and appropriately use visuals. Support for representational competencies enhances students’ learning outcomes. However, it is infeasible to design representational-competency supports for entire curricula. This raises the question of whether these supports enhance future learning from novel problems. We addressed this question with an experiment with 120 undergraduates in an engineering class. All students worked with an intelligent tutoring system (ITS) that provided problems with interactive visual representations. The experiment varied which types of representational-competency supports the problems provided. We assessed future learning from a subsequent set of novel problems that involved a novel visual representation. Results show that representational-competency support can enhance future learning from the novel problems. We discuss implications for the integration of these supports in educational technologies.
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Acknowledgements
This work was supported by NSF DUE 1933078. We also thank Bernie Lesieutre and his teaching assistants for their help with our study.
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Rho, J., Rau, M.A., Van Veen, B.D. (2022). Preparing Future Learning with Novel Visuals by Supporting Representational Competencies. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2022. Lecture Notes in Computer Science, vol 13355. Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_6
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