Academic integrity (AI) is a complex problem that challenges how we view action, intentions, research, and knowledge production as human agents working with computers. This paper proposes that a productive approach to support AI is found at the nexus of behavioural ethics and a view of hybrid app-human agency. The proposal brings together AI research in behavioural ethics and Rest’s (1979) four stages of ethical decision-making which tracks the development of moral sensitivity, moral judgement, moral motivation and finally moral action combined with insights taken from Actor-Network Theory (ANT). This framework, bluntly named the Academic Integrity Model (AIM), positions AI as an effect of an entangled hybrid of human-technology actors moving through distinct but related steps towards ultimately mobilising (un)ethical learning behaviours. This model highlights the importance of developing socio-techno responsibility in students and suggests that approaches to address academic integrity performances such as contract cheating, collusion and plagiarism should include considerations of the complex nature of app-centric students.

学术诚信（AI）是一个复杂的问题，对我们如何将行为，意图，研究和知识生产视为人类与计算机一起工作的人提出了挑战。本文提出，在行为伦理学的关系和混合应用程序-人代理的观点中，发现了一种支持AI的有效方法。该提案将AI在行为伦理学方面的研究与Rest（1979）的道德决策的四个阶段结合在一起，该阶段跟踪道德敏感性，道德判断，道德动机以及最终的道德行为的发展，并结合Actor-Network Theory（ANT）的见解。这个框架直称为学术诚信模型（AIM），将AI定位为人类技术参与者纠缠不清的混合体的影响，它们通过不同但相关的步骤最终调动（非）道德学习行为。