Balancing innovation and integrity: Faculty perceptions of AI and generative AI in assessment

dc.contributor.authorSantos-Pereira, Carla
dc.contributor.authorMoreira, Fernando
dc.contributor.authorLobo, Carla Azevedo
dc.contributor.authorAzevedo, Mónica
dc.date.accessioned2026-01-07T14:59:50Z
dc.date.available2026-01-07T14:59:50Z
dc.date.issued2025-12-10
dc.description.abstractThe integration of Artificial Intelligence (AI) and Generative AI (GAI) into higher education assessment is reshaping debates, especially in business education, in teaching and learning. While AI supports data analysis, pattern recognition, and predictive modelling, GAI extends these capabilities to the automated generation of texts and assessment materials. Yet their role remains contested, raising questions of efficiency, ethics, and academic integrity. This study investigates faculty perceptions and practices regarding AI/GAI in assessment, with a focus on business disciplines. A national survey yielded 111 responses across institutions; 46.8% were social sciences faculty. The questionnaire examined current uses, perceived benefits and risks, and expectations for future adoption. Overall, 53.2% report using AI/GAI for assessment. Among adopters, applications include plagiarism detection (63.3%) and content generation (37.6%). Benefits include time efficiency (66.1%), greater objectivity (48.6%), and improved feedback quality (42.2%). However, concerns persist about reliability (62.4%), ethical implications (52.3%), loss of the human element (51.4%), and insufficient training (50.5%). Faculty remains divided on permissibility: 44.0% support conditional integration, 43.1% favor selective use, and 5.6% advocate complete prohibition. These patterns indicate cautious optimism. While faculty recognize AI/GAI’s transformative potential, training deficits, technical limitations, and unresolved ethical challenges impede widespread adoption. Business educators emphasize the tension between efficiency gains and safeguarding critical thinking, creativity, and fairness. This article offers one of the first empirical portraits of Portuguese assessment practices involving AI/GAI. It underscores the need for targeted training, ethical frameworks, and institutional policies that balance innovation and integrity, enabling responsible and effective assessment in higher education.
dc.identifier.citationSantos-Pereira, C., Moreira, F., Lobo, C. A., & Azevedo, M. (versão aceite: dezembro 2025). Balancing innovation and integrity: Faculty perceptions of AI and generative AI in assessment. In International Conference on Applied Management: Advances in the 21st Century (AMA21) 2025, [online]. IADIS - International Association for Development pf the Information Society. Repositório Institucional UPT. https://hdl.handle.net/11328/6874
dc.identifier.urihttps://hdl.handle.net/11328/6874
dc.language.isoeng
dc.publisherIADIS - International Association for Development pf the Information Society
dc.rightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAcademic Integrity
dc.subjectArtificial Intelligence in Higher Education
dc.subjectBusiness Education
dc.subjectFaculty Perceptions
dc.subjectGenerative AI in Assessment
dc.subject.fosCiências Sociais - Economia e Gestão
dc.titleBalancing innovation and integrity: Faculty perceptions of AI and generative AI in assessment
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2025-12-10
oaire.citation.conferencePlaceOnline
oaire.citation.endPage6
oaire.citation.startPage1
oaire.citation.titleInternational Conference on Applied Management: Advances in the 21st Century (AMA21) 2025
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.affiliation.nameREMIT
person.affiliation.nameUniversidade Portucalense
person.affiliation.nameREMIT – Research on Economics, Management and Information Technologies
person.familyNameSantos-Pereira
person.familyNameMoreira
person.familyNameLobo
person.familyNameAzevedo
person.givenNameCarla
person.givenNameFernando
person.givenNameCarla Azevedo
person.givenNameMónica
person.identifier.ciencia-idDD11-7CE2-337F
person.identifier.ciencia-id7B1C-3A29-9861
person.identifier.ciencia-id2E1D-CA98-5832
person.identifier.ciencia-id3216-1D29-22AB
person.identifier.orcid0000-0002-3545-6265
person.identifier.orcid0000-0002-0816-1445
person.identifier.orcid0000-0002-6721-376X
person.identifier.orcid0000-0003-2118-0138
person.identifier.ridG-9695-2016
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person.identifier.ridG-9840-2016
person.identifier.ridV-1275-2019
person.identifier.scopus-author-id12794047600
person.identifier.scopus-author-id8649758400
person.identifier.scopus-author-id57210261298
person.identifier.scopus-author-id56012866500
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