Universities are redefining their approach to generative AI (GenAI) by prioritizing teaching AI as a collaborative tool rather than viewing it as a threat. The AI Collaboration Toolkit emphasizes a student-first methodology, framing AI use with clear ethical guidelines and limits, while also addressing equality in education. Key components include a Typology of Student AI Use, categorizing tasks to differentiate between acceptable and questionable AI involvement. This framework promotes inclusivity, aiding students with language barriers and those with less access to resources. Additionally, reflective practices like the AI Reflection Journal encourage accountability. Misconduct definitions clarify acceptable use, shifting the conversation from fear to productive engagement. The goal is to foster active collaboration between students and AI, enhancing learning outcomes while maintaining integrity. By promoting transparency and purpose in AI practices, universities can empower students, encouraging them to ask meaningful questions about their learning process.
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