Assessing for Integrity in the Age of AI

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dc.contributor.authorEaton, Sarah Elaine
dc.date.accessioned2024-12-06T19:16:13Z
dc.date.available2024-12-06T19:16:13Z
dc.date.issued2024-12-04
dc.description.abstractIn this webinar, Dr. Sarah Elaine Eaton, explores the potential benefits and drawbacks of using AI in educational assessment. Although AI offers opportunities for efficiency and personalization, ethical considerations, including potential biases, privacy concerns and the risk of undermining academic integrity, need to be addressed. AI can enhance assessment practices by automating grading and feedback, enabling frequent assessments and providing personalized learning paths. However, AI algorithms can perpetuate biases, struggle to evaluate nuanced responses and raise privacy concerns about student data. Maintaining academic integrity in a technology-driven classroom is crucial, particularly avoiding unreliable and potentially biased AI-text detection tools. To ensure equity, diversity, inclusion, and accessibility in AI-powered assessments, it is important to incorporate accessibility and inclusion features for students with disabilities and use diverse and representative training data to minimize bias. This approach aligns with the principles of fairness and equity in AI assessment highlighted in the abstract, promoting a more inclusive learning environment. Ensuring fair and equitable AI-powered assessments requires diverse training data, regular audits for bias and transparency in assessment criteria. Strategies for ethical AI implementation include clear communication with students, data privacy protection, human oversight and ongoing system improvement. Keywords: artificial intelligence, GenAI, education, higher education, assessment, academic integrity, ethics, bias, equity, ed tech, disability, neurodiversity, inclusion, inclusive education How to cite this work: Eaton, S. E. (2024, December 4). Assessing for Integrity in the Age of AI [Online]. DOCEO AI. Calgary, Canada.
dc.identifier.urihttps://hdl.handle.net/1880/120156
dc.identifier.urihttps://dx.doi.org/10.11575/PRISM/47767
dc.language.isoenen
dc.publisher.facultyWerklund School of Educationen
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Canadaen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/ca/
dc.subjectacademic integrity
dc.subjectartificial intelligence
dc.subjectGenAI
dc.subjectassessment
dc.subjectacademic misconduct
dc.subjecteducation
dc.subjecthigher education
dc.subjectethics
dc.subjectbias
dc.subjectequity
dc.subjectinclusion
dc.subjectdiversity
dc.subjectneurodiversity
dc.subjectinclusive education
dc.titleAssessing for Integrity in the Age of AI
dc.typePresentation
ucalgary.scholar.levelFaculty
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