Editing Human Centered Data Science (Fall 2019) (section)

=== Grading ===

Active participation in class activities is one of the requirements of the course. You are expected to engage in group activities, class discussions, interactions with your peers, and constructive critiques as part of the course work. This will help you hone your communication and other professional skills. Correspondingly, working in groups or on teams is an essential part of all data science disciplines. As part of this course, you will be asked to provide feedback of your peers' work.

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The following grading scheme will be used to evaluate each of the 6 individual assignments (not reading reflections or graded in-class activities). 

;81-100% - Exceptional: The student demonstrated novelty or insight beyond the specific requirements of the assignment.

;61-80% - Competent: The student competently and confidently addressed requirements to a good standard.

;41-60% - Acceptable: The student met the absolute minimum requirements for the assignment.

;21-40% - Partial: The student submitted something, but only addressed some of the assignment requirements or they submitted work that was poor quality overall.

;1-20% - Submitted: The student submitted something.
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Individual assignments will have specific requirements listed on the assignment sheet, which the instructor will make available on the day the homework is assigned. If you have questions about how your assignment was graded, please see the TA or instructor.