{"title":"Semi-automated rubrics for evidence-based medicine assessment: a case report on grading time reduction.","authors":"Juliana Magro","doi":"10.5195/jmla.2026.2343","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Librarians providing feedback on Evidence-Based Medicine (EBM) assignments face time constraints. This case report describes implementing a semi-automated rubric - defined here as a tool that automatically calculates scores from grader-selected ratings while narrative feedback is still written by the instructor - to reduce grading time for an EBM capstone assignment for first-year medical students.</p><p><strong>Case presentation: </strong>Two cohorts of approximately 100 students completed the same EBM assignment. The 2023 cohort received manual feedback, while the 2024 cohort received feedback using the semi-automated rubric. Grading time was logged for both cohorts. The rubric, adapted from a template, automatically calculates scores based on selected criteria, streamlining the feedback process.</p><p><strong>Conclusions: </strong>The semi-automated rubric reduced grading time by 30%, from an average of seven minutes per assignment to five minutes. This simple, adaptable intervention can help reduce educator workload, improve feedback timeliness, and enhance assessment consistency. While limited by its single-grader and single institution design, this case report offers practical insights for educators seeking to improve feedback efficiency in EBM and other disciplines.</p>","PeriodicalId":47690,"journal":{"name":"Journal of the Medical Library Association","volume":"114 3","pages":"290-296"},"PeriodicalIF":1.7000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13367300/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Medical Library Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.5195/jmla.2026.2343","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/14 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Librarians providing feedback on Evidence-Based Medicine (EBM) assignments face time constraints. This case report describes implementing a semi-automated rubric - defined here as a tool that automatically calculates scores from grader-selected ratings while narrative feedback is still written by the instructor - to reduce grading time for an EBM capstone assignment for first-year medical students.
Case presentation: Two cohorts of approximately 100 students completed the same EBM assignment. The 2023 cohort received manual feedback, while the 2024 cohort received feedback using the semi-automated rubric. Grading time was logged for both cohorts. The rubric, adapted from a template, automatically calculates scores based on selected criteria, streamlining the feedback process.
Conclusions: The semi-automated rubric reduced grading time by 30%, from an average of seven minutes per assignment to five minutes. This simple, adaptable intervention can help reduce educator workload, improve feedback timeliness, and enhance assessment consistency. While limited by its single-grader and single institution design, this case report offers practical insights for educators seeking to improve feedback efficiency in EBM and other disciplines.
期刊介绍：
The Journal of the Medical Library Association (JMLA) is an international, peer-reviewed journal published quarterly that aims to advance the practice and research knowledgebase of health sciences librarianship. The most current impact factor for the JMLA (from the 2007 edition of Journal Citation Reports) is 1.392.
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