CSC 1301, Principles of Computer Science I Honors Lab, Fall 2025, Syllabus

Class Details

Lab Time: Wednesday 3.00 to 4.40
Location: Classroom South 305
Instructor: Dr. Raj Sunderraman
Office: 1 Park Place, Suite 629
Office Hrs: Wednesday Noon to 3.00 PM or email
E-mail: raj at gsu dot edu
Webex: https://gsumeetings.webex.com/meet/rsunderraman

Lab Overview

CSC 1301L supplements the lecture course CSC 1301 that you are taking simultaneously or have taken in the recent past. In the regular sections of CSC 1301L, there are weekly tasks that students complete, which include writing code to solve small problems within the lab time. In contrast, the Honors lab will assume that you are ready to learn the same materials in an accelerated mode. The Honors Lab will involve six reasonably challenging programming assignments that test your knowledge of programming in Python in solving computational problems.

Grading

The grading will be based on the following components:

1. Six Programming Assignments (6 x 10 = 60 points). Grades for assignments 2, 3, and 5 will be given based on an oral examination (15 minutes) in my office, wherein you will asked to answer a few questions about your understanding of your submission. The other three assignments will be graded in the traditional way.
2. Two in-lab exams (2 x 20 = 40 points) without use of GenAI or any other assistance.

Grades will assigned using the following scale:

A−: 90 to 92 	A:  93 to 96 	A+: 97 to 100
B−: 80 to 82 	B:  83 to 86 	B+: 87 to 89
C:  70 to 76 	C+: 77 to 79
D:  60 to 69
F:   0 to 59

Curves will be used depending in the difficulty of the assignments.

Policy on Academic Honesty:

We are piloting the use of GenAI tools in this lab. However, as can be seen in the grading criteria, your understanding of the underlying computational principles will be graded for 70% of the grade. So, it is very important that you use GenAI and outside assistance as little as possible. The objective with this approach is that you get a flavor for what GenAI is capable of and how to use it to improve productivity. We do not want to diminish our learning of the subject matter with the use of GenAI.

Attendance Etc.

Daily attendance is strongly encouraged. Any student missing a lesson is responsible for all material assigned or covered in class during his or her absence. Other Disruptive classroom behavior will not be tolerated. See the student catalog for more information. Class participation is strongly encouraged, please ask questions, make comments.

Disclaimer

This syllabus represents a general plan for the course and deviations from this plan may be necessary during the duration of the course.