NEXUS

Testing in general produces anxiety in students. The watchful eye of a proctor can potentially add more. However, some pressure is actually good for learning. Other kinds of pressure, like sorting out problems with unfamiliar tech, can have a negative impact. For exams, proctoring is certainly in large part about ensuring fairness and adherence to ​​NYU academic integrity policy but it’s also about setting up a clear, structured environment where students can demonstrate thei

In this sample Global Sport assignment, students read different articles about the same topic, then listen to a Gemini Notebook generated podcast about the articles. Students meet in groups to deepen their understanding by discussing their articles and critiquing what the AI generated podcast got right and wrong. AI Tool Gemini Notebook - Audio Overview Summary The purpose of this exercise is to do a deep reading of an article, then analyze and critique the output of an AI to

In this sample assignment, students practice creating Google Gem to act as a financial planner and then analyze its output. Through this process, students practice building gems, developing procedures and documents for good financial planning and critically analyzing AI outputs. AI Tool Google Gemini / Gems Summary Students will create a Gem to act as a financial planner, then upload data and documents to test its capability and utility and analyze the Gem’s output using thei

What kinds of learning experiences become more important when students can generate explanations, summaries, and examples in seconds? AI can make learning feel efficient, but efficiency is not the same as understanding. When students work mostly through prompts and generated responses, they may miss the nuance and energy that comes from learning with other people. For me, the solution lies in creating intentional space for analog interaction, where students can explain ideas

A common problem with AI as a drafting tool is its generic output. For instance, ask it to draft a lesson plan, and you often receive a bland, uninspired outline; ask for a complex case study, and the output frequently lacks the specific nuance or local context needed for your students. It's a common frustration that leaves many of us wondering if these tools are actually worth the hype. But as I've discovered while starting the NYU Google AI for Education Accelerator program

Faculty receive training about how AI tools fit into teaching and learning. Students, however, have varying levels of experience and little structure or guidance for how to use AI to support their learning. Faculty at SPS share that students tend to arrive with uneven experience and little structure for using AI to support their learning. Some students rely on generative AI without clear judgment, while others avoid it because expectations are unclear. What Students Are Missi