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AGGA (Academic Guidelines for Generative AIs) is a dataset of 80 academic guidelines for the usage of generative AIs and large language models in academia, selected systematically and collected from official university websites across six continents. Comprising 181,225 words, the dataset supports natural language processing tasks such as language modeling, sentiment and semantic analysis, model synthesis, classification, and topic labeling. It can also serve as a benchmark for ambiguity detection and requirements categorization. This resource aims to facilitate research on AI governance in educational contexts, promoting a deeper understanding of the integration of AI technologies in academia.more » « less
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Afroogh, Saleh; Esmalian, Amir; Donaldson, Jonan; Mostafavi, Ali (, Sustainability)In this paper, we argue that an inclusive and effective community resilience approach requires empathy as a missing component in the current engineering education and practice. An inclusive and effective community resilience approach needs to be human-centric, individual- and communal-sensitive, justice-oriented, and values-based consistent. In this paper, we argue that three kinds of empathy, namely cognitive, affective, and conative, play a central role in creating and sustaining an inclusive and effective approach to community resilience. Finally, we discuss empathetic education through learning theories and analytics skills to cultivate empathy in engineering education. Cultivating empathy in engineering education could help advance the impact and contribution of engineering to well-being.more » « less
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