Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence

[2509.10591] Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence Skip to main content Search Submit Donate Log in Computer Science > Computers and Society arXiv:2509.10591 (cs) [Submitted on 12 Sep 2025 ( v1 ), last revised 10 Nov 2025 (this version, v2)] Title: Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence Authors: Jan Cvengros , Gerd Kortemeyer View PDF HTML (experimental) Abstract: We explore the effectiveness and reliability of an artificial intelligence (AI)-based grading system for a handwritten general chemistry exam, comparing AI-assigned scores to human grading across various types of questions. Exam pages and grading rubrics were uploaded as images to account for chemical reaction equations, short and long open-ended answers, numerical and symbolic answer derivations, drawing, and sketching in pencil-and-paper format. Using linear regression analyses and psychometric evaluations, the investigation reveals high agreement between AI and human graders for textual and chemical reaction questions, while highlighting lower reliability for numerical and graphical tasks. The findings emphasize the necessity for human oversight to ensure grading accuracy, based on selective filtering. The results indicate promising applications for AI in routine assessment tasks, though careful consideration must be given to student perceptions of fairness and trust in integrating AI-based grading into educational practice. Subjects: Computers and Society (cs.CY) ; Artificial Intelligence (cs.AI) Cite as: arXiv:2509.10591 [cs.CY] (or arXiv:2509.10591v2 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2509.10591 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1007/s44163-026-01606-4 Focus to learn more DOI(s) linking to related resources Submission history From: Gerd Kortemeyer [ view email ] [v1] Fri, 12 Sep 2025 13:08:27 UTC (12,994 KB) [v2] Mon, 10 Nov 2025 12:37:31 UTC (13,128 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: cs.CY < prev | next > new | recent | 2025-09 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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