Unclear how the paper builds off of previous work. Works discussed are not state of the art. 5-10 pts – Failed to identify major categories of related work.Discussed works that are state of the art but missed a few major papers. 11-15 pts – Identified and discussed most major categories of related work.Made clear how the paper advances the state of the art compared to the papers cited. Within each category, identified works that are truly state of the art. 16-20 pts – Identified and discussed all categories of related work.10-20pts – The writing interferes with the reader’s ability to learn from work.21-26 pts – The writing does not add too nor detract from the research itself.27-30 pts – The writing makes the work more interesting and accessible.This includes linguistic clarity, exposition of technical concepts, logical structure, justification of claims, explanation of background concepts, and discussion of results. 5-10 pts – Left gaping holes in the investigation / incorrect data analysis etc.11-15 pts – Covered a few bases but left some obvious holes.16-20 pts – Thorough investigation with no obvious holes.
5-10 pts – Used techniques learned in class in a straightforward way.Ĭorrectness and thoroughness of Investigation (20 points).11-15 pts – Used designs and techniques learned in class but showed some originality in their application and/or dataset choices.Taught the reader something new and surprising. 16-20 pts – Research design and techniques went beyond what was shown in class.5 pts – Problem statement or importance is unclear.10 pts – Interesting, important, and clearly defined problem.If you have a reason to be exempted from this policy, please talk to us. blog or tweet about it) unless you tell us that’s ok. Except for potentially citing your paper, we won’t publicize it (e.g. we won’t be able to cite your paper for the insight nor, of course, claim credit for it as our own. The reason for this requirement is that your work may contain new research insights unless it is public, it will be difficult for others (including us) to build on those insights - i.e. We are happy to do this for you by default. It is completely up to you.Įither way, we ask that you make your class project submission public in a way that can be cited by others. You are welcome to work with us to produce a publishable paper, or do so on your own, or choose to leave it as a class project. After the course is over, we (Arvind and/or Matt) may, at our discretion, offer to help you develop your project into a paper to submit for peer review. Recall that in addition to learning goals, this course also has the goal of enabling publishable student-led research. Making your final project submission public
#Thoroughness as element of rubric code#
This is what happens in peer review (at least in the ideal case in practice, unfortunately, often authors don’t make code available and reviewers are overburdened and don’t have time to look at it). Other than that, you won’t be graded based on your code, but we’ll consult it if we can’t understand something in your paper or if we want to get a deeper understanding of how your system works. Learning to carry out reproducible research is an important learning goal of the class. You should submit reproducible code along with your paper we need to be able to run your code and verify your results. See “Grading Rubric” below for more details. It’s basically like a research paper, except that you’re probably tackling a more modest problem, and we won’t penalize you if you accidentally missed prior work. We’ll evaluate your project based on the creativity of your ideas, the thoroughness of your investigation, the quality of your writing, as well as connecting your project to related work.
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