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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.10300 |
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| _version_ | 1866916569848741888 |
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| author | Kollapally, Navya Martin Geller, James Morreale, Patricia Kwak, Daehan |
| author_facet | Kollapally, Navya Martin Geller, James Morreale, Patricia Kwak, Daehan |
| contents | The use of computational ontologies is well-established in the field of Medical Informatics. The topic of Social Determinants of Health (SDoH) has also received extensive attention. Work at the intersection of ontologies and SDoH has been published. However, a standardized framework for Social Determinants of Education (SDoEd) is lacking. In this paper, we are closing the gap by introducing an SDoEd ontology for creating a precise conceptualization of the interplay between life circumstances of students and their possible educational achievements. The ontology was developed utilizing suggestions from ChatGPT-3.5-010422 and validated using peer-reviewed research articles. The first version of developed ontology was evaluated by human experts in the field of education and validated using standard ontology evaluation software. This version of the SDoEd ontology contains 231 domain concepts, 10 object properties, and 24 data properties |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_10300 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Ontology for Social Determinants of Education (SDoEd) based on Human-AI Collaborative Approach Kollapally, Navya Martin Geller, James Morreale, Patricia Kwak, Daehan Artificial Intelligence The use of computational ontologies is well-established in the field of Medical Informatics. The topic of Social Determinants of Health (SDoH) has also received extensive attention. Work at the intersection of ontologies and SDoH has been published. However, a standardized framework for Social Determinants of Education (SDoEd) is lacking. In this paper, we are closing the gap by introducing an SDoEd ontology for creating a precise conceptualization of the interplay between life circumstances of students and their possible educational achievements. The ontology was developed utilizing suggestions from ChatGPT-3.5-010422 and validated using peer-reviewed research articles. The first version of developed ontology was evaluated by human experts in the field of education and validated using standard ontology evaluation software. This version of the SDoEd ontology contains 231 domain concepts, 10 object properties, and 24 data properties |
| title | An Ontology for Social Determinants of Education (SDoEd) based on Human-AI Collaborative Approach |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2501.10300 |