Using data mining to investigate cognitive processes by a creativity test-a preliminary study

Lu, Yu-Ling; Wu, Yuan-Chang; Chen, Wei-Ming; Lien, Yu-Cheng Norm; Lien, Chi-Jui

doi:10.1109/coginf.2010.5599698

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Although much have been investigated regarding EDM and LA in education and student assessment, there is little study on creativity assessment using EDM or LA. However, there are some researches around cognitive processes such as creative thinking and problem-solving skills 23,70,114,163,191 . For example, Yu 191 performed rule extraction using rough set as a data mining tool to find the rules between scientific creativity and creativity affective.…”

Section: Creativity Assessment Using Edm/lamentioning

confidence: 99%

Towards Mining Creative Thinking Patterns from Educational Data

Shabani¹

2022

Preprint

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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.

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Section: Creativity Assessment Using Edm/lamentioning

confidence: 99%

Towards Mining Creative Thinking Patterns from Educational Data

Shabani¹

2022

Preprint

View full text Add to dashboard Cite

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A Rule-Based Approach for Mining Creative Thinking Patterns from Big Educational Data

et al. 2023

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Numerous studies have established a correlation between creativity and intrinsic motivation to learn, with creativity defined as the process of generating original and valuable ideas, often by integrating perspectives from different fields. The field of educational technology has shown a growing interest in leveraging technology to promote creativity in the classroom, with several studies demonstrating the positive impact of creativity on learning outcomes. However, mining creative thinking patterns from educational data remains a challenging task, even with the proliferation of research on adaptive technology for education. This paper presents an initial effort towards formalizing educational knowledge by developing a domain-specific Knowledge Base that identifies key concepts, facts, and assumptions essential for identifying creativity patterns. Our proposed pipeline involves modeling raw educational data, such as assessments and class activities, as a graph to facilitate the contextualization of knowledge. We then leverage a rule-based approach to enable the mining of creative thinking patterns from the contextualized data and knowledge graph. To validate our approach, we evaluate it on real-world datasets and demonstrate how the proposed pipeline can enable instructors to gain insights into students’ creative thinking patterns from their activities and assessment tasks.

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Using data mining to investigate cognitive processes by a creativity test-a preliminary study

Cited by 2 publications

References 3 publications

Towards Mining Creative Thinking Patterns from Educational Data

Towards Mining Creative Thinking Patterns from Educational Data

A Rule-Based Approach for Mining Creative Thinking Patterns from Big Educational Data

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