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Generative artificial intelligence in forensic science education: Student perspectives on AI-supported crime scene
Paula Tarttelin Hernández1, Alicia Haines1, Vincent Mousseau2
1Centre for Forensic Science, MAPS School, University of Technology Sydney, Australia.
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Students in Higher Education (HE) are increasingly engaging with Generative Artificial Intelligence (GenAI), raising concerns regarding learning, academic integrity, and equitable access to technology. In forensic science, these concerns are particularly significant, as professional practice relies on critical judgement, evidentiary reliability and ethical accountability. This study examined how undergraduate forensic science students engaged with a university-approved GenAI tool (Copilot) within crime scene simulations, with a focus on decision-making, ethical and responsible use, and trust. Copilot was embedded into a second-year subject (Major Scene Investigation) of a three-year undergraduate forensic science degree, as a structured decision-support tool. Students critically evaluated AI-generated outputs during simulated crime scene investigations and documented their use through reflective entries, including interaction records and reflections that could be presented in various formats (e.g. written, audio, video). These data were analysed thematically to explore student perceptions, patterns of engagement, and the development of critical AI literacy. Findings indicate that students did not adopt GenAI uncritically or as a substitute for professional judgement. Instead, they demonstrated a cautious selective approach, positioning GenAI as a conditional support tool. Engagement evolved over time, with initial scepticism giving way to more informed strategic use. Importantly, students differentiated between low- and high-stakes decisions, demonstrating reduced reliance on GenAI where accountability and evidentiary consequences were greater. Embedding GenAI within assessments supported the development of critical and ethical GenAI literacy, enabling students to articulate appropriate, cautious, and limited uses of the technology. While GenAI offered efficiencies in tasks such as hazard identification and documentation, its role remained bounded by the need for human oversight and justification. This study demonstrates the value of integrating GenAI into discipline specific learning environments to support critical engagement and understanding rather than passive use. It highlights the importance of explicitly teaching the ethical and professional boundaries of GenAI in forensic science decision-making to prepare students for responsible use of this technology in future practice.