Utilizing Artificial Intelligence for Exam Grading
| dc.contributor.author | Bosankic, Antonio | |
| dc.contributor.mentor | Giovanoli, Claudio | |
| dc.date.accessioned | 2025-12-15T13:39:08Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This 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.uri | https://irf.fhnw.ch/handle/11654/54836 | |
| dc.language.iso | en | |
| dc.publisher | Hochschule für Wirtschaft FHNW | |
| dc.spatial | Olten | |
| dc.subject.ddc | 330 - Wirtschaft | |
| dc.title | Utilizing Artificial Intelligence for Exam Grading | |
| dc.type | 11 - Studentische Arbeit | |
| dspace.entity.type | Publication | |
| fhnw.InventedHere | Yes | |
| fhnw.StudentsWorkType | Master | |
| fhnw.affiliation.hochschule | Hochschule für Wirtschaft FHNW | de_CH |
| fhnw.affiliation.institut | Master of Science | de_CH |
| relation.isMentorOfPublication | ac88a4d1-8c8f-4c07-a064-c18658c0f009 | |
| relation.isMentorOfPublication.latestForDiscovery | ac88a4d1-8c8f-4c07-a064-c18658c0f009 |