Utilizing Artificial Intelligence for Exam Grading

dc.contributor.authorBosankic, Antonio
dc.contributor.mentorGiovanoli, Claudio
dc.date.accessioned2025-12-15T13:39:08Z
dc.date.issued2025
dc.description.abstractThis study explores the application of AI models in grading bachelor’s and master’s level assessments, comparing their performance with traditional human grading methods. The research aims to evaluate the strengths and limitations of AI-driven grading systems, focusing on key metrics such as accuracy, efficiency, reliability, and fairness.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/54836
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialOlten
dc.subject.ddc330 - Wirtschaft
dc.titleUtilizing Artificial Intelligence for Exam Grading
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeMaster
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutMaster of Sciencede_CH
relation.isMentorOfPublicationac88a4d1-8c8f-4c07-a064-c18658c0f009
relation.isMentorOfPublication.latestForDiscoveryac88a4d1-8c8f-4c07-a064-c18658c0f009
Dateien