My students’ weekly reading reflections now seem entirely AI-generated. Unlike in-person classes where handwritten work is used, I require methods to ensure genuine submissions for my online asynchronous course this spring. Any ideas?
i reckon ask them to do quick, spontaneous reflections during the week. this might force more unique input and make it difficlt for ai to spit out generic response. trying out random prompts could also help catch copied work.
Hey everyone, I’m really intrigued by this topic! I was thinking that maybe we could shake things up by having students engage in a sort of role-play dialogue. Imagine asking them to write a conversation between themselves and a character deeply immersed in the course material – it almost becomes like storytelling. It’s not just an essay anymore, but a unique interaction that reflects their personal insights. I also wonder if incorporating a bit of multimedia, like a short video or even a voice note, might push them to bring in more of their genuine self. It might be a bit more work to evaluate, but could also open the door to deeper understanding and authenticity. What are your thoughts on this approach? Ever tried something similar before? 
Based on my experience managing online courses, I have found that developing assignments that require personalized context can help deter AI-generated submissions. For instance, by asking students to relate the course material to a specific scenario they have encountered or to compare it with something uniquely personal from their lives, the responses tend to be more nuanced and reflective. Incorporating follow-up prompts that require explanations or justifications for their viewpoints also encourages original work. This approach not only deters generic AI responses but also deepens their engagement with the subject.
i wonder if combining quick, live response tasks with a reflective element might help. having students record brief video/audio logs could force more spontaneous, genuine reflections that ai finds harder to mimic.