Papers with computer-adaptive testing
Machine Learning–Driven Language Assessment (2020.tacl-1)
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| Challenge: | Language proficiency tests are cumbersome to create and maintain, and items may be copied and leaked or simply used too often. |
| Approach: | They propose a method that uses machine learning and natural language processing to induce proficiency scales and linguistic models to estimate item difficulty directly for computer-adaptive testing. |
| Outcome: | The proposed method produces scores that are reliable and reliable while generating item banks large enough to satisfy security requirements. |