  Creativity, i.e., the process of generating and developing fresh and original
ideas or products that are useful or effective, is a valuable skill in a
variety of domains. Creativity is called an essential 21st-century skill that
should be taught in schools. The use of educational technology to promote
creativity is an active study field, as evidenced by several studies linking
creativity in the classroom to beneficial learning outcomes. Despite the
burgeoning body of research on adaptive technology for education, mining
creative thinking patterns from educational data remains a challenging task. In
this paper, to address this challenge, we put the first step towards
formalizing educational knowledge by constructing a domain-specific Knowledge
Base to identify essential concepts, facts, and assumptions in identifying
creative patterns. We then introduce a pipeline to contextualize the raw
educational data, such as assessments and class activities. Finally, we present
a rule-based approach to learning from the Knowledge Base, and facilitate
mining creative thinking patterns from contextualized data and knowledge. We
evaluate our approach with real-world datasets and highlight how the proposed
pipeline can help instructors understand creative thinking patterns from
students' activities and assessment tasks.
