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Smart grading: A generative AI-based tool for knowledge-grounded answer evaluation in educational assessments.
Tobler, Samuel.
Affiliation
  • Tobler S; ETH Zurich, Switzerland.
MethodsX ; 12: 102531, 2024 Jun.
Article in En | MEDLINE | ID: mdl-38204981
ABSTRACT
Evaluating text-based answers obtained in educational settings or behavioral studies is time-consuming and resource-intensive. Applying novel artificial intelligence tools such as ChatGPT might support the process. Still, currently available implementations do not allow for automated and case-specific evaluations of large numbers of student answers. To counter this limitation, we developed a flexible software and user-friendly web application that enables researchers and educators to use cutting-edge artificial intelligence technologies by providing an interface that combines large language models with options to specify questions of interest, sample solutions, and evaluation instructions for automated answer scoring. We validated the method in an empirical study and found the software with expert ratings to have high reliability. Hence, the present software constitutes a valuable tool to facilitate and enhance text-based answer evaluation.•Generative AI-enhanced software for customizable, case-specific, and automized grading of large amounts of text-based answers.•Open-source software and web application for direct implementation and adaptation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: MethodsX Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: MethodsX Year: 2024 Document type: Article Affiliation country: Country of publication: