Grading

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Grade
Basic Info
  1. Grading is based on the 10 workbooks (50%), two projects (20%), and the exams (20%), and in-class quizzes (10%, lowest four dropped).
  2. We will consider dropped in-class quizzes to adjust your grade at the end.

Canvas cannot compute your grade for you. It does not correctly deal with the way we handle dropping scores.

Your grade in this class will be determined by:

  1. (50%) Your total score on the 10 workbooks. You will get a number of points for each workbook. Note that workbook scores are points not percentages. 86 points is an 4.5/5, whether there are 120 points possible or 90 points possible. More details are given in the information about workbooks.

  2. (20%) Your grade on the projects (which are bigger workbooks).

  3. (20%) Your exam grades. There will be 2 exams.

  4. (10%) Your in-class quiz grades. They must be completed on TopHat during the lectures.

All class assignments will be graded on a point scale and converted to letter grades at the end. The class will use the following point scale:

  • 91 and above A - the University does not award A+, but you can earn that on assignments and exams. You may score more than 100 on individual assignments.
  • 86-90 AB
  • 81-85 B
  • 76-80 BC
  • 71-75 C
  • 61-70 D (the university does not give a “DC” grade)
  • below 60 F

Workbooks, project, exams, and in-class quizzes will provide points on this scale. Note: individual assignments may have different numbers of points possible. For example, an 86 is an 4.5 whether the assignment has 120 or 90 points possible. There is no notion of “percentage of possible.”

Canvas cannot compute your grade for you.

Stochastic Grading

We have limited resources for assessing student work. We can’t check everything. Therefore, we won’t. For some things (exam questions, items in workbooks), we might not actually check your work - but will just give you the points you reported in the Canvas hand-in assignment. We call this “stochastic” grading because we will check only some of the assignments chosen at random.

A few things to note about this:

  • Just because you got points for something, doesn’t mean you got it correct. We will generally release the answers to things so you can check yourself.
  • If you request a regrade, we may check something that wasn’t graded and find out that you didn’t deserve points.

Code Similarity

If you find code or ideas from other students, on the Internet, or generated using large language models (for example GPT),

  • You must give proper attribution (comments in the .js file), including name and ID of the student, or link to the web page, or prompt used for the large language model, and
  • You should rewrite the code yourself, but if you are unable to rewrite the code, you must add documentation (comments in the .js file) demonstrating that you understand what each line of the code is doing.

If your code is flagged during our code similarity check and you do not have sufficient documentation demonstrating your understanding of the code (or if your documentation is also identical to the ones written by the other student),

  • Your code will be submitted to the Office of Student Conduct OSC and we will suggest a grade of 0 for the whole workbook for the first offense, and a grade of F for the whole course for the second offense.

Note: allowing another student to copy your code and not making sure the student is giving proper attribution is also considered an academic offense (except if your code is stolen by another student without permission).