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Towards Mining Creative Thinking Patterns from Educational Data

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posted on 2022-11-04, 00:00 authored by Nasrin ShabaniNasrin Shabani

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 thesis, to address this challenge, we put the first step towards formalizing the 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 learn 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.

History

Table of Contents

1. Introduction -- 2. Background and State-of-the-Art -- 3. Methodology -- 4. Experiments and Evaluation -- 5. Conclusion and Future Work -- Bibliography

Notes

A thesis submitted to Macquarie University for the degree of Master of Research, School of Computing, February 2022

Awarding Institution

Macquarie University

Degree Type

Thesis MRes

Degree

Thesis (MRes), Macquarie University, Faculty of Science and Engineering, School of Computing, 2022

Department, Centre or School

School of Computing

Year of Award

2022

Principal Supervisor

Amin Beheshti

Rights

Copyright: The Author Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer

Language

English

Extent

79 pages

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