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.