Author: Sanjay Goel, http://in.linkedin.com/in/sgoel
___________________________________________
Student evaluation (grading) policies are a very important element of any course. Mostly Indian universities show a tendency to overemphasize the importance of written exams at the cost of several other potential forms of student engagements that require (and hence promote) critical/creative thinking, information gathering, problem formulation, complex problem solving, experimentation/construction/documentation skills, reflective improvisation, independence of thought, group work, etc. This practice significantly differs from the practice at CS departments of a few top Universities, e.g., MIT, UC Berkeley, Stanford, etc.
I have tabulated the grading policy of some CS courses at MIT, UC Berkeley, and Stanford University. It can be seen that in 65% of 43 courses, the written exams (including quizzes) do not form the major component of student’s task. Instead more than 50% weightage is given to student performance in assignments, projects, homework, participation, peer review. Interestingly, in 40% courses, there is no midterm/final exam or quiz. Many midterm and final exams are held as Open book exams. Some faculty members administer their exams as take home or open book- open laptop exams. The faculty members at these universities have the flexibility of designing their own evaluation scheme in their courses. They do not have to follow a rigid universal scheme in their courses. Such an academic flexibility is not yet seen on the agenda of academic reforms in India.
In my view, if any institute wants to excel in computing education, it will have to reform its grading policies as well and give higher freedom to its faculty in terms of designing the evaluation scheme in their courses. The examples listed below can be used as benchmarks in this regard. No doubt, the proposed higher flexibility will require a higher sense of commitment for excellence by the faculty members.
A. Stanford University
| SNo | Course | Evaluation/Grading Policy |
| 1. | CS103: Mathematical Foundations of Computing | Homeworks (60%), Midterm (15%), and Final (25%). Students may use the course texts and all handouts (including lecture notes, course notes, and solutions) and their own notes and homework solutons during exams, but no other materials. |
| 2. | CS 106A: Programming Methodology | Programming Assignments: 55%, Midterm: 15%, Final Exam: 25%, Section Participation: 5% |
| 3. | CS 106A: Programming Abstractions | Programming assignments: 60% minus 5% for each Honor Code case reported, Final examination: 15% plus 5% for each Honor Code case reported, Midterm examination: 15%, Section participation: 10% |
| 4. | CS 108 : Object Oriented System Design | Homework Assignments 66.6% , Class Project 33.3% |
| 5. | CS110: Principles of Computer Systems | Homework 50%, Midterm Exam 15%, Final Exam 35% |
| 6. | CS144: Introduction to Computer Networking | E = max (final; avg (final; midterm));
HW= avg (hw1; hw2); HW’s are writing assignments; W = (3E+HW)/4; P = avg (p1; p2; p3; p4; p5); P’s are programming assignments; Grade = max{ (2W+P)/3 ; (W+2P)/3} |
| 7. | CS157: Computational Logic | CS157 is offered for 3-4 units. The requirements (same for both number of units) include four problem sets and a very easy final exam. Each will be worth 20% of the total grade. |
| 8. | CS 181: Computers, Ethics and Public Policy | 20% Paper #1, 20% Paper #220% Section participation and reaction papers, 40% Final project |
| 9. | CS221: Introduction to Artificial Intelligence | Homework assignments : 20%, Programming assignments: 30%, Midterm: 20%, Final: 30% |
| 10. | CS 224: Natural Language Processing | Programming assignments and final project : 92%; Quizzes: 8%. |
| 11. | CS224W: Social and Information Network Analysis | 30% on problem sets10% on reaction paper60% on the final project |
| 12. | CS 231A: Introduction to Computer Vision | Problem Sets: 40%, Midterm exam: 20%, Final project: 40% |
| 13. | CS 245: Database System Principles | Homeworks: 20%, Midterm: 30%, Final: 50%. |
| 14. | CS 249a: Object-Oriented Programming from a Modeling and Simulation Perspective | 40% assignments, 15% midterm, 45% final exam. |
| 15. | CS 255: Introduction to Cryptography | Homework: 35%; Programming project: 35%; Final exam: 30% |
| 16. | CS 259C: Elliptic Curves in Cryptography | Homework assignments: 60%, Final project: 40% |
| 17. | CS 309A: Cloud Computing | Class attendanceAsking one question in advance of each lecture/guest lecturer. There is a site where you register your questionA final paper of between 4 and 8 pages. |
| 18. | CS 347: Transaction Processing and Distributed Databases | Assignment: 20%, Mid term: 30% Final: 50%;exams are open-book open laptop |
| 19. | CS 378: Phenomenolgical foundations of Cognition, language and Computation | Forum Participation (including pairs)- 30%Term Paper Draft and comment on other person’s draft – 30%Term Paper Final Version- 30%In-Class Participation – 10% |
| 20. | CS 448B: Data Visualization | Class Participation: 10%, Assignments : 50%, Final Project: 40% |
B. UC Berkeley
| SNo | Course | Evaluation/Grading Policy |
| 1. | CS 3L: Introduction to Symbolc Programming | Total marks = 400
45 Labs 11.25% 40 Quizzes 10% 50 Homework 12.5% 5 Free points 1.25% 20 Final project 5% 60 Exam 1 15% 80 Exam 2 20% 100 Final Exam 25% |
| 2. | CS4: Introduction to Computing for Engineers | Lab quizzes: 10%, Project: 10%, Homework: 20%Midterm: 25%, Final: 35% |
| 3. | CS 61B: Data Structures | Labs 5%, Homework 10%, Projects 35%Midterm I 12.5%Midterm II 12.5%Final Exam 25% |
| 4. | EE123: Digital Signal Processing | Homework: (Weekly) 20%,
Midterm 1: 20%, Midterm 2: 20%, Project: 10%, Final: 30% |
| 5. | CS152: Computer Architecture and Engineering | Quizzes: 50%, Labs: 35%, Problem sets: 15% |
| 6. | CS252 – Graduate Computer Architecture | Homework: 50%, Midterm: 20%, Final: 30% |
| 7. | CS 261N: Internet/Network Security | Class project: 50%, Homework: 35% Topic briefing: 10% Lecture participation: 5% |
| 8. | CS 274: Computational Geometry | Homework 80%, Projects 20% |
| 9. | CS 276: Cryptography | Homework: 10%, Scribe notes: 20%,
Take-home midterm: 30%, Final project: 40% |
| 10. | CS 281A: Statistical Learning Theory | Homework 60%, Projects 40% |
| 11. | CS 287: Advanced Robotics | Open-ended final project: 45%, Assignments: 55% |
| 12. | CS 289: Knowledge Representation and Reasoning | Assignments. 60% (written work + implementations) Term Project 40% (substantial project or analytical paper) |
| 13. | CS302 : Designing Computer Science Education | Weekly Homework: 50%, Participation in class discussions: 25%, Reviewing each other’s work: 25% |
C. MIT
| SNo | Course | Evaluation/Grading Policy | ||||||||||||||||
| 1. | 6.00: Introduction to Computer Science and Programming | Problem sets: 55%, Open book Quizzes: 45% | ||||||||||||||||
| 2. | 6.001: Structure and Interpretation of Computer Programs | Two Mid-term Quizzes 25%
Final Exam 25% Projects 30% Problem Sets 10% Course Participation in Recitations and Tutorials 10% |
||||||||||||||||
| 3. | 6.005: Elements of Software Construction | Explorations 20%,
Problem sets 30%, Projects 40%. Participation and lab assignments 10% |
||||||||||||||||
| 4. | 6.006: Introduction to Algorithms | Problem sets 40%
Two quizzes 30% Final exam 25% Recitation participation 5% |
||||||||||||||||
| 5. | 6.01: Introduction to EECS I |
|
||||||||||||||||
| 6. | 6.034 Artificial Intelligence | Final 30%
Quizzes 30% Assignments + Recitation 25% Design problems 15% |
||||||||||||||||
| 7. | 6.035 Computer Language Engineering | Compiler project 58%
Paper discussion 12% In class quizzes 30% |
||||||||||||||||
| 8. | 6.055J: The Art of Approximation in Science and Engineering | Home work: 100% | ||||||||||||||||
| 9. | 6.837: Computer Graphics | Assignments: 40%,
2 Quizzes: 20%, Team project: 405 |
||||||||||||||||
| 10. | 6.878: Computational Biology: Genomes, Networks, Evolution | Problem set: 40%, Midterm: 20%, Final project: 25%Scribing: 10%, Participation: 5% |
putchavn
March 16, 2012
That is a very good and relevant presentation for educational system design including evaluation. Although the title refers to the Grading Policy, the real difference is in the way the subject is taught and learnt. All the forms of student engagement (SE) must be carefully planned and implemented to ensure that superior learning occurs. Testing and evaluation is important but secondary to SE.
In many Indian schools and colleges we too have laboratories, workshops, field work, project work, Quizzes, INVERSE Quizzes (that is my peculiarity at the places I worked / taught), Reviews and evaluation by students etc., but are most neglected and even subverted both by the students and faculty. The reformation must start here also.
To my surprise I learnt that student projects are carried out by professionals and tutors in the USA also. One student called for bids for professional engagement to work on a project without revealing that it was a student project. I responded but refused to take up the project work after getting to know the truth. It is a different matter that I actually guided the project for an academic fee. Surely the student learnt a lot and I too learnt substantially.
kenablersys@yahoo.com