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Bringing Nuance to Automated Exam and Classroom Response System Grading: A Tool for Rapid, Flexible, and Scalable Partial-Credit Scoring

التفاصيل البيبلوغرافية
العنوان: Bringing Nuance to Automated Exam and Classroom Response System Grading: A Tool for Rapid, Flexible, and Scalable Partial-Credit Scoring
المؤلفون: Dustin J. Covell, Philip S. Lukeman, Tom P. Carberry
المصدر: Journal of Chemical Education. 96:1767-1772
بيانات النشر: American Chemical Society (ACS), 2019.
سنة النشر: 2019
مصطلحات موضوعية: Multimedia, business.industry, Computer science, Workload, General Chemistry, computer.software_genre, Partial credit, Automation, Education, Software, Scalability, ComputingMilieux_COMPUTERSANDEDUCATION, Statistical analysis, Grading (education), business, computer, Response system
الوصف: We present here an extension of Morrison’s and Ruder’s “Sequence-Response Questions” (SRQs) that allows for more nuance in the assessment of student responses to these questions. We have implemented grading software (which we call ANGST, “Automated Nuanced Grading & Statistics Tool”) in a Microsoft Excel sheet that can take SRQ answer data from any source and flexibly and automatically grade these responses with partial credit. This allows for instructors to assess a range of understanding of material from student-generated answers as in a traditional written exam, while still reducing grading workload for large classes. It also allows instructors to do automated statistical analysis on the most popular answers, and subanswers, either from sources like exams or classroom response systems (CRSs), to determine common misunderstandings and facilitate adjustments to instruction.
تدمد: 1938-1328
0021-9584
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::5ea0852885fe0e0ce003d9db3044a289
https://doi.org/10.1021/acs.jchemed.8b01004
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........5ea0852885fe0e0ce003d9db3044a289
قاعدة البيانات: OpenAIRE
الوصف
تدمد:19381328
00219584