Computer Science 121 Grading - Fall 2009

General Weighting

While a weight is shown for each project, there will not be a "single grade" for each project. Each of the projects will involve a great many activities and deliverables, each of which will be individually graded (and many of which will each be the subject of an entire lecture). In Project 1, for example the individually graded processes and submissions will be:

Activity	Graded Item	Area Weight	Item Weight
Concept Proposal	report	15%	15%
Customer Requirements	Requirements Elicitation	15%	10%
	report		5%
User Assessment	prototype	25%	15%
	process		5%
	report		5%
Techology Assessment	report	10%	10%
Final Proposal	report	25%	25%
Management	planning & tracking	10%	3%
	Post Mortem		4%
	process & presentation		3%

For each graded submission most (e.g. 60-75%) of the grade will be a group-score (based on the overall quality of the submission). A smaller portion of the grade will be personal, based on and divided (more or less equally) between the share and quality of each person's individual contributions to the overall effort.

Rationale

I have two goals in grading:

1. to assess your mastery of the material.
2. to encourage you go get as much as possible out of this class.

The greatest portion of the grade is evenly divided between exams (your mastery of concepts) and projects (your ability to apply skills and techniques). On the projects, I am weighting the overall result more than the individual components because:

1. in the real world you will be judged, not on the basis of your individual efforts, but on the overall quality of your results.
2. teams are not merely a technique for allowing individuals to do less work. A well functioning team can do work that none of the individuals would have been able to do.
3. work division and cooperation are skills that are taught in this class. I expect to see the results of the applications of those skills.

I am using the remaining 10% as a coercive tool, to encourage you to get the maximum benefit out of the course:

• Years of experience have consistently taught me that the greatest single predictor of how much a student will get from a lecture is how well they understood the material before the start of the lecture.

  I have found (and student surveys regularly confirm) that giving daily quizzes on the assigned reading gets students to do the reading before the lecture, and greatly enhances learning.

  I attempt to choose quiz questions, based on key concepts, that should be trivial to answer based on a single reading. Even though the questions are simple, you can earn double credit for an answer that impresses me as particularly insightful.

• Non-trivial concepts cannot be usefully mastered merely by reading about them. Their implications and applications must be explored. In class discussions are the only place where I have the opportunity to observe this process.