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Imagine planning a trip to a new city. A quick online search highlights the usual downtown tourist spots, but as you explore more, you uncover unique neighborhoods—a financial district bustling with experts, a hidden restaurant scene, and a college area alive with bookstores and cafés. Yet, none of these appeared in your initial search for “best places to visit.”

Late submissions can raise thorny questions for online instructors. While studies show that students who submit assessments before the due date receive higher-than-average grades, as many as 70% of college students identify as procrastinators (You, 2015). Despite instructor attempts to create a manageable workload and motivate students to submit assignments on time, it is inevitable that procrastination, combined with the competing obligations of online students, will result in occasional late submissions. When preparing for an upcoming term, it is a good idea to share a late policy that clearly communicates your expectations for student submissions (Santelli et al., 2020).

This piece builds on a previous piece where we explored the importance of keeping your desired outcome in mind when working with generative AI (genAI). We also highlighted the value of including specific data and contextual details in your prompt to align with your goals. If you haven’t read that piece, we recommend starting there: