iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data

Nasrin Shabani, Amin Beheshti, Helia Farhood, Matt Bower, Michael Garrett, Hamid Alinejad-Rokny

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.