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Automatic Assessment of Mathematical Creativity Using Natural Language Processing
- Source :
-
Creativity Research Journal . 2023 35(4):661-676. - Publication Year :
- 2023
-
Abstract
- Creativity is now accepted as a core 21st-century competency and is increasingly an explicit part of school curricula around the world. Therefore, the ability to assess creativity for both formative and summative purposes is vital. However, the "fitness-for-purpose" of creativity tests has recently come under scrutiny. Current creativity assessments have up to five key weaknesses that create a barrier to their widespread use in educational settings. These are: (a) A lack of domain/subject specificity; (b) Inconsistency, leading to a lack of trust; (c) A lack of authenticity in classroom settings; (d) Slowness (in providing useful results); (e) High cost to administer. The aim of the present study is to explore the feasibility of the automated assessment of mathematical creativity, drawing on tools and techniques from the field of natural language processing, as a means to address these weaknesses. This paper describes the performance of a machine learning algorithm, relative to human judges, demonstrating the practicality of automated creativity assessment for large-scale, school-based assessments.
Details
- Language :
- English
- ISSN :
- 1040-0419 and 1532-6934
- Volume :
- 35
- Issue :
- 4
- Database :
- ERIC
- Journal :
- Creativity Research Journal
- Publication Type :
- Academic Journal
- Accession number :
- EJ1404125
- Document Type :
- Journal Articles<br />Reports - Research
- Full Text :
- https://doi.org/10.1080/10400419.2022.2131209