iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data

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Abstract

Creativity can be defined as the process of having original ideas that have value. The use of educational technology to promote creativity has attracted a great deal of attention. However, mining creative thinking patterns from educational data remains challenging. In this paper, we introduce a pipeline to contextualize the raw educational data, such as assessments and class activities. We also evaluate our approach with a real-world dataset and highlight how the proposed pipeline can help instructors understand creative thinking patterns from students’ activities and assessment tasks.

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APA

Shabani, N., Beheshti, A., Farhood, H., Bower, M., Garrett, M., & Rokny, H. A. (2022). iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13356 LNCS, pp. 352–356). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-11647-6_68

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