For each student-led discussion day in the course schedule, select a paper of your choice from the related readings column for that day. Read the paper and prepare a 200-300 word paper summary/reflection (do not go over 300 words). Post your summary to EdSTEM so that other students can read it. Reflections are due by 11:59 PM two days before the relevant Discussion class. They will be graded on a pass/fail basis.
Note that you do not need to read every paper listed for the Discussion class, since we’ve often listed many more than we will have time for in class. Our goal is to cover a broad range of ideas related to the topic. We hope that students will cover the different papers, and that even if you don’t have the chance to read a particular paper, you can learn a bit about it by reading other students’ summaries. To help incentivize coverage of the papers, you will get a bonus of 0.25% that can be applied to improve your overall grade in the course if you submit a reflection on a paper that no one else does. Even more bonus points if you can prove this is not a dominant-strategy incentive-compatible mechanism (just kidding!).
Do not generate paper summaries with AI. We want to see evidence that you've actually read the paper, and would prefer sloppy jot notes to an AI-generated summary. If we think your summary sounds AI-generated, we will run it through an AI detector. If the detector indicates that more than 50% of your summary was AI-generated, then we will dock you points proportional to the detected AI-generated percentage. E.g. if the detector says it's 90% AI, you will receive 10% on the summary reflection grade.
Your reflection on the paper should concisely present the technical details needed for others to understand the paper, as well as why it is worth reading and where it fits in the literature. Try to answer:-
Keep your response short and sweet. Ideally, your summary is clear, crisp, and concise, and lets other students grasp the central ideas of the paper from reading your reflection.