UCSD CSE 11 Winter 2024
Accelerated Introduction to Programming
In this course, you will learn to write, trace, and test programs; explore the interactions between programs and data; and practice organizing programs for clarity and re-use.
We will explore these topics interactively in lecure, you will implement programs to practice your programming skills, and you will reflect on this learning through your own program designs.
This web page serves as the main source of announcements and resources for the course, as well as the syllabus.
On an average week in CSE11, you can expect to spend 4-6 hours, reading, lecture, and discussion; and 4-6 hours working on your programming projects. If you find yourself spending dramatically more time than this, it’s a good idea to contact the course staff and discuss more efficient strategies in office hours.
There are a few components to your grade in the course:
- 20% Completing exercises in Stepik textbook and course engagement activities (surveys)
- 40% Programming assignments
- 40% Exams
- 15% Midterm Exam
- 25% Final Exam
- Extra Credit: 10% Lecture/Discussion Participation
We may adjust the above scale to be more lenient (depending on a number of factors that we will not publicize), but we guarantee that we will not adjust the scale to make it harder to get a better grade. We will not adjust the scale for individual students.
Lectures will be led during the normally-scheduled lecture times in the normally-scheduled room, led by the instructor. They will be recorded by podcasting but will not be available remotely while they are ongoing. You can find the recordings in the Canvas Media Gallery and at podcast.ucsd.edu
Teaching Assistants (TAs) will hold a weekly discussion section to practice exam questions, review prior content, and answer student questions.
Like lectures, discussions will also be recorded and made available in the Canvas Media Gallery and at podcast.ucsd.edu
Lecture/Discussion Participation (Extra Credit)
Starting with the second lecture, we will take attendance during lecture (except exams) and for each discussion session.
Attendance for lectures and discussions is not required, but attendance at each lecture/discussion earns 0.4% extra credit, up to a maximum of 10% (25 total lectures and/or discussions).
In each lecture/discussion, we’ll have a paper handout (also available electronically). At the end of lecture/discussion you’ll have a chance submit your handout to Gradescope. You can do this by scanning it in the Gradescope app (for iOS and Android) or through the web interface. To get participation credit, you have to submit a handout filled in with the key provided by the instructor/TA.
The correct key for the lecture/discussion (given by the instructor or TA) must be used or credit will not be given for attending. Handouts will be graded for participation only and not for correctness of the response.
We will not accept any check-ins after lecture and credit for attendance will not be given retroactively.
Stepik Exercises (textbook) and Course Engagement
Along with each lecture will come some required pre-lecture work. Most often this will be reading and activities from our Stepik textbook, and will also sometimes include surveys or check-in quizzes so we can get your feedback about the course and check on your understanding.
The online texbook records your progress, and we give a schedule of expected times to finish the readings. There is no penalty for completing these late, but they are assigned so that you will be prepared to participate in problem solving session and so that you know the expected pace of the course.
All Stepik exercises must be completed by Saturday of Week 10 by 8am. After this time, no late submissions will be accepted, for any reason.
To ensure you get credit for the Stepik exercises, you must fill out this form by Friday of Week 2. Starting in Week 3, we will strive to post Stepik grades to Canvas every week.
Most weeks there will be a programming assignment. Direct practice with programming will make up the majority of your work in the course and will help practice course concepts to prepare for exams.
All PAs must be submitted to Gradescope before the PA deadline. We do not accept submissions over email or Piazza, everything must be submitted to Gradescope. Code can be submitted to Gradescope multiple times before the deadline and only the last submission will be graded.
There is an automatic 24-hour extension to submit the PA in Gradescope (in case of internet/technical issues, illness, AFA accomdations, etc.). Just submit your assignment after the deadline (but before 24 hours after the deadline) to automatically use the extension. There is no penalty for using the 24-hour extension.
Please note that all deadlines for PAs are at 8am.
Programming assignments are graded in two ways:
Most of the PA grading is through Gradescope’s autograder which checks that your code follows the write-up’s specifications. The autograded grade is displayed each time something is submitted to Gradescope. We will not manually grade code that is autograded so make sure to check Gradescope autograder output to ensure that it compiles and passes all requirements.
Some parts of PAs are manually graded by the course staff. Usually manually graded code is used to visually check code that cannot be autograded.
Not all PAs have manually graded parts, in which case your final score will be the autograded score displayed in Gradescope.
There are numerous opportunities to get feedback on your work and improve:
Shortly after the deadline for each assignment, the autograded portion will automatically grade your submitted code and for the manually graded portion, a staff member will grade your work and give feedback on what, if anything, you need to fix.
After you receive your grade you can continue to improve your assignment based on the feedback from grading. You can resubmit your work to the Late/Resubmit submission which will be open for up to two weeks (less for those assignments near the end of the quarter). Once the Late/Resubmit submission closes, your submission will again be graded.
There is no penalty for resubmissions, you can still earn full credit. We will take the highest score between your original submission and your late/resubmission.
The Late/Resubmit process also applies if your submission is late. You should strive to complete each PA before it’s posted deadline as the PAs are practice for the exams. You will also receive earlier feedback and an extra grading attempt if you submit before the original deadline.
For those assignments near the end of the quarter, the deadline for all late/resubmissions will be Friday of Week 10 at 8am. After the automatic 24-hour extenstion, we will not accept any submissions after that time, for any reason.
There will be two in-person exams in this course: a midterm and a final exam. The exam dates are shown below:
- Midterm Exam: Friday, February 16th 2024
- Final Exam: Wednesday, March 22nd 2024
The final exam will be cumulative and will cover all topics discussed in the course.
If your final exam score (in percentage) is higher than your midterm score, then your midterm score will be replaced by your final exam score!
Mistakes sometimes occur in grading. Once grades are posted for an assignment, we will allow a short period for you to request a fix (announced along with Gradescope grade release). If you don’t make a request in the given period, the grade you were initially given is final.
Regrades for exams must be done in person with the instructor or a teaching assistant (not undergraduate tutors).
Individual assignments will describe their academic integrity requirements. You should pay attention to the descriptions of what collaboration is allowed and expected on each assignment.
One challenge we face as an instructional team is verifying that students are submitting their own work. We rely on ID-checked exams to mitigate this particular challenge to academic integrity.
Assignments and exams will come with specific policies for what types of collaboration is allowed, but we have one course-wide policy – we may reach out to students to schedule a check-in on their understanding of work they’ve submitted if we’re suspicious about an academic integrity violation.
This would involve a meeting with a TA or instructor to check that the student has the understanding demonstrated by their work.
We don’t expect to use this option much (certainly you are a student that acts with integrity!), but we state it clearly in the syllabus in case it becomes necessary so it isn’t a surprise to anyone.
You should be familiar with the UCSD guidelines on academic integrity as well.
Diversity and Inclusion
We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives and experiences, and respects your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create a diverse and inclusive learning environment where all students feel comfortable and can thrive.
Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know, either in person, via email/discussion board, or even in a note under the door. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.
We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community (https://ucsd.edu/about/principles.html). Please understand that others’ backgrounds, perspectives and experiences may be different than your own, and help us to build an environment where everyone is respected and feels comfortable.
If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination: https://ophd.ucsd.edu/.