Pensieve Grader: An AI-Powered, Ready-to-Use Platform for Effortless Handwritten STEM Grading
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866918084799889408 |
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| author | Yang, Yoonseok Kim, Minjune Rondinelli, Marlon Shao, Keren |
| author_facet | Yang, Yoonseok Kim, Minjune Rondinelli, Marlon Shao, Keren |
| contents | Grading handwritten, open-ended responses remains a major bottleneck in large university STEM courses. We introduce Pensieve (https://www.pensieve.co), an AI-assisted grading platform that leverages large language models (LLMs) to transcribe and evaluate student work, providing instructors with rubric-aligned scores, transcriptions, and confidence ratings. Unlike prior tools that focus narrowly on specific tasks like transcription or rubric generation, Pensieve supports the entire grading pipeline-from scanned student submissions to final feedback-within a human-in-the-loop interface.
Pensieve has been deployed in real-world courses at over 20 institutions and has graded more than 300,000 student responses. We present system details and empirical results across four core STEM disciplines: Computer Science, Mathematics, Physics, and Chemistry. Our findings show that Pensieve reduces grading time by an average of 65%, while maintaining a 95.4% agreement rate with instructor-assigned grades for high-confidence predictions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01431 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Pensieve Grader: An AI-Powered, Ready-to-Use Platform for Effortless Handwritten STEM Grading Yang, Yoonseok Kim, Minjune Rondinelli, Marlon Shao, Keren Artificial Intelligence Computation and Language Human-Computer Interaction Machine Learning Grading handwritten, open-ended responses remains a major bottleneck in large university STEM courses. We introduce Pensieve (https://www.pensieve.co), an AI-assisted grading platform that leverages large language models (LLMs) to transcribe and evaluate student work, providing instructors with rubric-aligned scores, transcriptions, and confidence ratings. Unlike prior tools that focus narrowly on specific tasks like transcription or rubric generation, Pensieve supports the entire grading pipeline-from scanned student submissions to final feedback-within a human-in-the-loop interface. Pensieve has been deployed in real-world courses at over 20 institutions and has graded more than 300,000 student responses. We present system details and empirical results across four core STEM disciplines: Computer Science, Mathematics, Physics, and Chemistry. Our findings show that Pensieve reduces grading time by an average of 65%, while maintaining a 95.4% agreement rate with instructor-assigned grades for high-confidence predictions. |
| title | Pensieve Grader: An AI-Powered, Ready-to-Use Platform for Effortless Handwritten STEM Grading |
| topic | Artificial Intelligence Computation and Language Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2507.01431 |