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| Turnitin 및 iThenticate 유사성 탐지× | 유사성과 표절: 차이점 이해하기× | |
|---|---|---|
| 분야 | 연구윤리 | 연구윤리 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1997 | 2000s |
| 창시자≠ | Turnitin (1997), iThenticate (commercial variant) | Academic integrity frameworks and plagiarism detection software companies |
| 유형≠ | Tool | Concept |
| 원전≠ | Turnitin. (2023). Turnitin similarity detection and plagiarism detection technology. Retrieved from https://www.turnitin.com/products/similarity link ↗ | Hirsch, L. R. (2013). Recognizing plagiarism: A guide for academic professionals. Teaching Professor Blog. link ↗ |
| 별칭≠ | text-matching software, plagiarism detection software, similarity detection, originality reports | similarity index, turnitin score, similarity percentage |
| 관련≠ | 2 | 4 |
| 요약≠ | Turnitin and iThenticate are commercial text-matching software tools used by educational institutions and academic journals to screen submissions for potential plagiarism. Turnitin is designed for student assignments; iThenticate is designed for researcher manuscripts. Both tools compare submitted text against billions of sources (web pages, academic databases, previously submitted documents) and generate a Similarity Index showing what percentage of the submission matches existing sources. These tools are screening instruments, not plagiarism detectors—they flag suspicious content for human review. | A critical distinction exists between similarity percentages generated by plagiarism detection software (Turnitin, iThenticate) and an actual plagiarism verdict. A similarity index is a red flag requiring review; it is not a plagiarism determination. High similarity can result from legitimate quotations, references, shared technical language, or common knowledge. Conversely, low similarity does not guarantee absence of plagiarism. Human expert judgment is essential—similarity detection software provides data, not judgment. |
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