Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

• DOI: 10.55016/ojs/cpai.v7i3.78123
• Publication Date: 2024-04-19T20:24:16Z
• Authors: Beatriz Moya; Sarah Eaton; Helen Pethrick; Alix Hayden; Robert Brennan; Jason Wiens; Brenda McDermott
• Keywords: Academic Integrity

Artificial Intelligence (AI) developments challenge higher education institutions’ teaching, learning, assessment, and research practices. To contribute timely evidence-based recommendations for upholding academic integrity, we conducted a rapid scoping review focusing on what is known about integrity AI in education. We followed the Updated Reviewer Manual Scoping Reviews from Joanna Briggs Institute (JBI) Preferred Reporting Items Systematic reviews Meta-Analysis (PRISMA-ScR) reporting standards. Five databases were searched, eligibility criteria included stakeholders of any age gender engaged with context 2007 through November 2022 available English. The search retrieved 2223 records, which 14 publications mixed methods, qualitative, quantitative, randomized controlled trials, text opinion studies met inclusion criteria. results showed bounded unbounded ethical implications AI. Perspectives included: cheating; as legitimate support; an equity, diversity, lens into AI; emerging to tackle evidence sources provides guidance that can inform educational decision-making processes integration, analysis misconduct cases involving AI, exploration assistance. Likewise, this signals key questions future research, explore our discussion.