Assessment Practices with Generative Artificial Intelligence: Pedagogical Innovation and Faculty Development in Higher Education

dc.contributor.authorFernandes, Sandra
dc.contributor.authorMartins, Mário
dc.date.accessioned2026-08-03T08:44:55Z
dc.date.issued2026-06-06
dc.description.abstractGenerative artificial intelligence (AI) is challenging established approaches to student assessment in higher education, creating both pedagogical opportunities and ethical concerns. This study explores teachers’ perceptions of assessment, feedback, and the role of generative AI, with the aim of informing professional development and the integration of generative AI in assessment design and practices. The research was conducted at Portuguese higher education institution, within a six-hour training programme organised by the Pedagogic Innovation Office. The study was guided by three research questions: how do teachers conceptualise student assessment; how do they value feedback within assessment practices; and how do they perceive the potential and risks of generative AI in assessment. Data were collected through a questionnaire composed of 12 closed questions addressing: Conceptions of student assessment; Feedback practices; Attitudes towards generative AI in assessment. The instrument functioned as a diagnostic tool to inform the training design and research analysis. A total of 46 valid responses were obtained from participants enrolled in the programme, corresponding to a response rate of 83.6%. Descriptive analysis was conducted to identify dominant patterns in participants’ responses. The results indicate a strong orientation towards formative assessment, with teachers primarily viewing assessment as a means to support learning and guide teaching decisions rather than as a solely summative process. Feedback is consistently perceived as a core component of meaningful assessment, although its implementation is often constrained by workload and time limitations. Participants demonstrate a cautious yet open attitude towards generative AI, recognising its potential to support assessment and feedback practices, while simultaneously expressing concerns related to ethical use, student dependency, and reduced critical thinking. These findings highlight the importance of ethically grounded approaches to assessment supported by targeted professional development in higher education.
dc.identifier.citationFernandes, S., & Martins, M. (2026). Assessment Practices with Generative Artificial Intelligence: Pedagogical Innovation and Faculty Development in Higher Education. In M. Inoue, H. Hasegawa, R. M. Lima, K. H. Murakami, A. K. Yamazaki, A. Alves, & D. Mesquita (Eds.), International Symposium on Project Approaches in Engineering Education: Proceedings of the PAEE/ALE’2026, International Conference on Active Learning in Engineering Education, 18 th International Symposium on Project Approaches in Engineering Education (PAEE), 23rd Active Learning in Engineering Education Workshop (ALE), Taisho University, Tokyo, Japan, 4-6 June 2026, (pp. 1034-1042). Universidade do Minho. Repositório Institucional UPT. https://hdl.handle.net/11328/7368
dc.identifier.issn2183-1378
dc.identifier.urihttps://hdl.handle.net/11328/7368
dc.language.isoeng
dc.publisherDepartment of Production and Systems – PAEE association School of Engineering of the University of Minho
dc.relation.hasversionhttps://paeeale.conferenceservice.jp/doc/PAEE_ALE_2026_PROCEEDINGS_draft_version.pdf
dc.rightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHigher Education
dc.subjectGenerative Artificial Intelligence
dc.subjectTeacher Professional Development
dc.subjectStudent Assessment
dc.subjectFeedback Practices
dc.subject.fosCiências Sociais - Ciências da Educação
dc.subject.ods04 - quality education
dc.titleAssessment Practices with Generative Artificial Intelligence: Pedagogical Innovation and Faculty Development in Higher Education
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2026-06-06
oaire.citation.conferencePlaceTokyo, Japan
oaire.citation.endPage1042
oaire.citation.startPage1034
oaire.citation.titleInternational Symposium on Project Approaches in Engineering Education: Proceedings of the PAEE/ALE’2026, International Conference on Active Learning in Engineering Education, 18 th International Symposium on Project Approaches in Engineering Education (PAEE), 23 rd Active Learning in Engineering Education Workshop (ALE)
oaire.citation.volume16
oaire.versionhttp://purl.org/coar/version/c_fa2ee174bc00049f
person.affiliation.nameI2P - Instituto Portucalense de Psicologia
person.familyNameFernandes
person.givenNameSandra
person.identifier.ciencia-idD617-2C98-5011
person.identifier.orcid0000-0003-4712-4249
person.identifier.ridQ-2679-2019
person.identifier.scopus-author-id16315361800
relation.isAuthorOfPublication31cac8f7-2343-4567-9a41-454606455b42
relation.isAuthorOfPublication.latestForDiscovery31cac8f7-2343-4567-9a41-454606455b42

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