iCreate: Mining creative thinking patterns from contextualized educational data
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.
RAS ID
52053
Document Type
Conference Proceeding
Date of Publication
1-1-2022
Volume
13356 LNCS
School
School of Arts and Humanities
Copyright
subscription content
Publisher
Springer
Comments
Shabani, N., Beheshti, A., Farhood, H., Bower, M., Garrett, M., & Rokny, H. A. (2022). iCreate: Mining creative thinking patterns from contextualized educational data. In International Conference on Artificial Intelligence in Education (pp. 352-356). Springer. https://doi.org/10.1007/978-3-031-11647-6_68