Policies
Class Meetings
Mondays and Thursdays @ 11:20 AM- 12:35 PM
in Science Center Computer Lab Hub 402
Prerequisites
Fulfillment of the Quantitative Reasoning (QR) component of the
Quantitative Reasoning & Data Literacy requirement.
No prior background with computers is expected.
Computer Science Department Guidelines
As a part of this course, students and faculty are expected to adhere to the Computer Science Department Guidelines, which are designed to create a positive and productive learning environment. These guidelines emphasize respect, integrity, inclusivity, and transparency, ensuring that our department prepares students to lead in a world shaped by computation and data. For a detailed description of these principles and guidelines on attendance, timeliness, respect for others, exam policies, and how to share your thoughts with us, please refer to the Computer Science Department Guidelines Document.
Topics
- Web Fundamentals (Internet, HTML, CSS)
- JavaScript Programming
- Information Representation in Computing
- Introduction to Artificial Intelligence and Machine Learning
- Web Development with AI Integration
- Societal Impacts of AI (ethics, democracy, privacy)
- Data and Bias in AI Systems
Textbook, Readings, and Materials
We will be using a zyBook titled "Web Programming". ZyBooks is an interactive learning platform that integrates text and learning activities. To access the book:
1. Sign in or create an account at Zybooks
2. Enter zyBook code: WELLESLEYCS110ShaerFall2024
3. Subscribe - the cost for a subscription is $64
We understand that the cost of textbooks can be a significant financial burden for some students.
To ensure that all students have equal access to the course materials, we offer a limited number
of scholarships to cover the full cost of the required Zybook. If you are on work-study or in a high-need financial situation and would benefit from this assistance, we encourage you to apply for a textbook scholarship. Applications are due by Friday 9/6/2024. All applications will be reviewed confidentially by the CS Academic Administrator, and recipients will be notified promptly.
In addition, we will read research and news articles as well as book chapters. Access to these readings
will be available online or through the course Google Drive.
Course Requirements
The course requires active participation in class through discussion and
hands-on lab activities.
Students are required to prepare for class by completing the reading prior to lecture.
Students are required to sarrive to class in time, actively participate in discussions, and ubmit all hands-on lab activities.
There course has two different types of homework assignments: practice and assesment.
Practice assignments will mostly require completing activities in the text book. Practice assignments will be graded for completion. For example, completing 80% of the assignment will receive a score of 80/100.
Assesments will be graded for correctness. Assesments will cover all reading materials and content discussed and practiced in class, as well as in the practice assignments.
In addition, the course has a final project that requires students
to work in teams to investigate a topic at the intersection of AI and one of the UN sustainable development goals. As part of your team project, you will be expected to do the following:
- Drafting a team contract
- Developing a paper proposal
- Conducting a literature and media review on the topic
- Writing a research paper on the selected topic
- Developing a project website
- Reflect on your own learning and contributions to the project
The dates of the assignments and project milestones are listed on the schedule.
Grading Policy
This course's grading is Mandatory Credit/Non-Credit (or Credit/Non), meaning that the course grading that does not result in a letter grade.
In order to earn credit for this class, all the criteria below must be met:
- Your average of the assessment assignment in this course must be greater than or equal to 70 (after dropping the two lowest scores).
- Your average of the practice assignment in this course must be greater than or equal to 75
- Your total project score must be greater than or equal to 75
If you meet all of the above criteria, you will earn credit for this class. If you meet only one or two of the above criteria, you will not earn credit for this class.
Late Assignments
You are encouraged to submit practice assignments on the requested deadline but
you may submit it up to 48h after the deadline.
Project milestones may also be submitted up to 48h after the deadline. There is an exception to this late policy:
P5 is a project presentation and will need to be presented in class on the date specified.
Assessment assignments must be submitted on time. However, we will drop the two lowest scores. If for some reason you cannot submit your assesment on time, we will consider the score to be 0 and will count it as one of the lowest score to drop when calculating the final score.
If you need extra time
beyond this grace period, it is required that you contact the class dean
and discuss a plan for completing your assignment.We will work together
to make sure that plan is a reasonable and effective so that it supports
both your learning and your health.
Using Generative AI
Aligned with its learning goals, this course encourages students to explore
responsible and critical engagement with generative artificial intelligence (GAI)
tools such as ChatGPT, DALL·E, Midjourney, Claude and Bard. The use of GAI or AI
powered tools is restricted and is allowed only when assignments specificall allow or require the use of such tools. Any use of AI powered tools in this course must follow the
CS110 policy on using GAI.
We draw your attention to the fact that different classes at Wellesley implement
different AI policies, and it is the student's responsibility to conform to expectations
for each course.
Collaboration
The Wellesley College Honor Code applies to CS110. This course emphasizes collaboration,
as working effectively within teams is an important part of the innovation culture.
Working with a team provides you with opportunities to develop and improve interpersonal,
communication, leadership, and follower-ship skills.
I strongly encourage you to get to know all of your classmates and to collaborate extensively
with them. Because of the interdisciplinary nature of this course, you may be strong in some
areas but weak in others. Please share your strengths, and feel free to ask others for help.
Here is a summary of the collaboration policy:
- In-class activities and discussion: This class requires
your active contribution during our time together. Please come to class prepared and ready
to contribute to our learning community. During class you will work in groups on various activities.
- Practice assignments: You are encouraged to collaborate with others when completing your practice assignments.
- Assessments: Collaboration is not allowed. Any form of collaboration with other students, people, or AI is a violation of the Honor Code.
- Project: Teams of 3-4 students work together to complete and submit project
milestones. You will be assigned to a team.
Health-related accomodations
If you are ever feeling ill, or if you believe that your being in class might pose a risk to others,
please do not come to class. Please be in touch with us at your convenience to let us know what is
happening. We will then work with you to help you get back on track *after* you feel better.
We also understand that illness may require you to seek an extension (past the automatic 48h-extension)
– we can work with each of you individually.
Slides with lecture notes will always be available online, as well as all the activities.
Should you have to miss a class, your first resort is to get the notes from other
students. After reviewing these notes and the materials on the course website, feel free to
be in touch with us for additional help. We will not record in person lectures.
Disabilities
If you have a disability or condition, either long-term or temporary, and need
reasonable academic adjustments in this course, please contact Disability Services
to get a letter outlining your accommodation needs, and submit that letter to me.
You should request accommodations as early as possible in the semester, or before the
semester begins, since some situations can require significant time for review and
accommodation design. If you need immediate accommodations, during the semester,
please arrange to meet with me as soon as possible. If you are unsure but suspect
you may have an undocumented need for accommodations, you are encouraged to contact
Disability Services. They can provide assistance including screening and referral for
assessments. Disability Services can be reached at disabilityservices@wellesley.edu,
at 781-283-2434, by scheduling an appointment online at their website www.Wellesley.edu/disability.
Computing and Laboratory Environment
We will primarily use the following platforms during the course:
