---
tags: Course Documents
title: Syllabus
---
# CSCI 0111 (Computing Foundations: Data) -- Syllabus

Computer programs do not exist in a vacuum: they process information based on observations of the world. These observations--of text, numbers, images, video, or anything else--become the data over which programs operate. We are surrounded by computer programs collecting, storing, and manipulating data. The choices programmers make about how to represent and access data affect the performance, usability, and maintainability of their programs.

CSCI 0111 is a data-focused introduction to computing and programming. Students will learn how to create, analyze, and test programs that manipulate and process data. Students will also discuss the social impacts of data collection, retention, and processing, and the responsibilities engineers have to society and to the people who use their software.

This course is designed for both potential CS concentrators and non-concentrators who have no programming experience. It provides a firm foundation for future courses in computer science, and also provides non-concentrators with useful programming skills for doing data analysis in their chosen fields.

## High-level information
**Time and location:** MWF 9:00-10:50am, 85 Waterman 130
**Instructor:** Kathi Fisler ([e-mail])
**Teaching Assistants:** Annie He, Ching Lam, Colton Rusch, Credo Duarte Lutton, Cristian Loor, Floria Tsui, Leah Lam, Giselle Garcia (HTA), Julia Windham (HTA), Mohamed Ali, Monica Roy, Moses Lurbur (HTA), Raj Paul, Thomas Castleman, Livia Maria Souza Gimenes, TzuHwan Seet
**Course website:** http://cs.brown.edu/courses/csci0111/spring2020/index.html

See the course website for the lecture schedule, assignments and information about how to get help.

### Learning objectives

After completing this course, students will be able to:
- Develop programs that process and manipulate data in the shape of tables and lists (with an introduction to tree-shaped data)
- Decide how to organize data for efficient and maintainable processing by programs
- Describe the social implications of large-scale data collection, retention, and usage
- Decompose programming tasks into solvable subtasks, informing the structure of your programs
- Develop good automatable tests for programs that give confidence in their correctness
- Work with others to develop, test, and analyze programs

### Potential pathways into computer science and data science

CS0111 can be taken either as a terminal course or as a lead-in to Computer Science or the Data Fluency certificate. Three paths from CS0111 are currently available:
* CSCI 0111 is the first course in the three-course introductory computer science sequence: 0111, 0112, and 0113. CSCI 0112 is starting this spring (and is likely to be offered again in fall 2020); CSCI 0113 will be offered once there is student demand for it (tentatively spring 2021).
* Students who do well in CSCI 0111 have the option of doing some extra work to prepare for CSCI 0180 (spring), which is the second half of one of the two CS year-long intro sequences.
* Students interested in data science can proceed to DATA 200 (spring); the 111-200 sequence leads into the Data Fluency certificate.

## Course culture
Students taking CSCI 0111 come from a wide range of backgrounds (both personal and academic). We hope to foster an inclusive and safe learning environment based on curiosity rather than competition. All members of the course community--students, TAs, and the instructor--are expected to treat each other with courtesy and respect.Some of the responsibility for that lies with the staff, but a lot of it ultimately rests with you, the students.

### Be aware of your actions
Sometimes, the little things add up to creating an unwelcoming culture to some students. For example, you and a friend may think you are sharing in a private joke about other races, genders, cultures, etc, but if you do this in a public space and a classmate overhears it, it can have adverse effects. There is a fair bit of research on something called “stereotype threat”, in which simply reminding someone that they belong to an particular culture or identity (on whatever dimension) can interfere with their class performance.

Stereotype threat works both ways: you can assume that a student will struggle based on who they appear to be, or you can assume that a student is doing great based on who they appear to be. Both are potentially harmful.

Bear in mind that diversity has many facets, some of which are not visible. Your classmates may have medical conditions (physical or mental), personal situations (financial, family, etc), or interests that aren’t common to most students in the course. Another aspect of professionalism is avoiding comments that (likely unintentionally) put down colleagues for situations they cannot control. Bragging in open space that an assignment is easy or “crazy”, for example, can send subtle cues that discourage classmates who are dealing with issues that you can’t see. Please take care, so we can create a class in which all students feel supported and respected.

### Be an adult
Beyond the slips that many of us make unintentionally are a host of explicit behaviors that the course staff, department, and university (and beyond) do not tolerate. These are generally classified under the term harrassment, with sexual-based harrassment a specific form that is governed by federal laws known as Title IX.

[Brown’s Title IX Web](https://www.brown.edu/about/administration/title-ix/policy) site provides many resources for understanding the terms, procedures, and policies around harrassment. Make sure you are aware enough of these issues to avoid crossing a line in your interactions with other students (for example, repeatedly asking another student out on a date after they have said no can cross this line).

Your reaction to this topic might be to laugh it off, or to make (or think) snide remarks about “political correctness” or jokes about consent or other things. You might think people just need to grow a thicker skin or learn to take a joke. This isn’t your decision to make. Research shows the consequences (emotional as well as physical) on people who experience harrassment. When your behavior forces another student to focus on something other than their education, you have crossed a line. You have no right to take someone else’s education away from them.

In light of recent reports about such issues on campus, Brown is taking additional steps to reduce this form of harm. Therefore, if we cannot appeal to your decency and collegiality, let us at least appeal to your self-interest. Do not mess around on this matter. It will not go well for you.

### Issues with Course Staff

Professionalism and respect for diversity are not just matters between students; they also apply to how the course staff treat the students. The staff of this course will treat you in a way that respects our differences. However, despite our best efforts, we might slip up, hopefully inadvertently. If you are concerned about classroom environment issues created by the staff or overall class dynamic, please feel free to talk to us about it. The instructor and the HTAs in particular welcome any comments or concerns regarding conduct of the course and the staff.

Sometimes, you may not be comfortable bringing this up directly to us. If so, you are welcome to talk to Laura Dobler (the CS dept diversity coordinator) or to the Department Chair, Ugur Cetintemel. You may also reach out to Rene Davis in the Title IX office.

As a department, we will take all complaints about unprofessional or discriminatory behavior seriously.

## Logistics
### Course location, hours, staff
Lecture will be in 85 Waterman 130 from 9:00-9:50am on Monday, Wednesday, and Friday. Labs will be on Thursdays and Fridays. The TAs and the instructor will hold office hours throughout each week. Specific times and locations for labs and office hours will be listed on the course website once the semester is underway.

### Time expectations
In addition to 3 hours a week in lecture and 2 hours a week in lab, students will be expected to spend 6-8 hours a week outside of class on homework, projects, and drills.

### Required materials
There is no textbook for the course; all readings will be provided digitally.

You do not need a computer to complete the assignments, as you will have access to several computer labs in the CIT. You do **not** need a laptop for lecture (indeed, we prefer taking notes on paper).

### The classroom
Our time in the classroom will be a mix of traditional lecture and discussion-based activities. We expect you to work in small groups with those around you during lecture. Please come to class ready to engage with the material and ask questions about things you don’t understand. The pre-class drills (discussed below) should help you with this!

Studies have shown that the use of laptops in the classroom can be detrimental to learning--not just for the laptop user, but also for the students around them! As such, we ask that students in CSCI 0111 take notes by hand rather than using laptops, phones, or other electronic devices.

For (much!) more information on the effects of laptop usage, see [here](https://cs.brown.edu/courses/cs019/2018/laptop-policy.html#(part._pop)).

### Getting help and clarification
Most questions and requests for clarification should be
* Asked on the Campuswire discussion board (default for basic information-seeking questions),
* brought to office hours, or
* asked in class (if it applies to many people).

#### Campuswire

Our course uses Campuswire for online discussions. You can use it to ask questions about course concepts, assignments, and logistics. Posts can be either public or private; public posts are visible to everyone, while private posts are visible only to course staff. Any questions having to do with your particular solution to an assignment should be private; all other posts should be public (if you have a question about something, it’s very likely that other students do, too!). The course staff reserves the right to make private posts public if the answer is of general interest.

Campuswire is a discussion forum, so please feel free to respond to questions and comments–it’s great when students can learn from each other! When doing so, keep in mind the Course Culture guidelines.

Posts made on Campuswire after 11pm are unlikely to get a response until the next day.

**We expect you to read Campuswire every day or two for announcements and clarifications to assignments**; you are responsible for all clarifications made at least 48 hours before an assignment is due. If you are new to using Campuswire, ask the TAs during lab or office hours.

#### Email
Please do not send private email about questions unless the questions are of a personal nature that only an individual staff member or Kathi should see. Campuswire allows you to post anonymously, as well as privately to the staff. Posting to campuswire allows the first available staff member to get to your question without work duplication on our end.

#### Office Hours
Each TA will hold two hours of walk-in office hours per week. Kathi will hold one walk-in hour, and is also available for appointments. Each week’s schedule is available on the course website.

Feel free to come to Kathi’s office hours even if you don’t have a specific question about an assignment; Kathi is happy to chat about the course material, computer science in general, careers in computer science, etc.

Please come to office hours! Coming to office hours does not send a signal that you are behind or need “extra help”; on the contrary, the most successful students are usually those who come to office hours early and often. Learning to program often involves learning different strategies for approaching problems than you've used before. Don't hesitate to ask us to help you review your strategies, even if you don't have a specific question on an assignment. If you are someone who typically resists asking for help, keep in mind that learning new strategies for approaching new areas is part of the college experience. We are happy to help guide you in this.

## Assignments, exams, and grading
All assignments (except for quizes and exams) will be posted and handed in online. Approximate grading weights for each type of assignment are listed below.

All homeworks and projects will be due on Tuesdays at 9pm, and you will never have a homework assignment due at the same time as a project (although homework due dates may overlap with project design checks). There will generally be either a homework assignment or a project due every week. Drills will be due at 11am on Mondays, Wednesdays, and Fridays (so if you're a late sleeper, please plan on doing them the day before!).

### Assignment types and weights

#### Drills (now 20%; was 10%)
We will assign three short online quizzes a week, which will be due shortly before each class session. These should take around 10-30 minutes to complete, and are designed to help us--and you!--understand which subjects you’ve internalized and which subjects we might need to spend more time on. Drills will be graded for completion only, and full credit will be given if you complete 70% of the assigned drills.

#### Labs (10%)
You will have a two-hour lab session every week. Labs are hands-on programming projects where you'll practice writing code and integrating concepts learned in class in order to solve new problems. You'll write programs in small groups guided by our course TAs. Labs are graded for completion.

#### Homework assignments (now 30%; was 25%)
Homeworks, due approximately once per week, are designed to help you understand the course material and put it into practice. They will consist of both written questions and short programming assignments, which you will work on individually. Programming assignments will be graded for correctness as well as code style and test quality. Some of your homeworks will include short, written reflections on readings related to the impact of data collection on society. These will be graded lightly--we're asking you to think seriously and carefully about these issues, but not to write full formal papers.

#### Projects (now 20%, was 25%)
There will be three larger programming-focused projects, which are designed to help you apply your programming knowledge to interesting problems and to learn how to program with a partner. For each project, your pair will design and implement a solution to a data-focused problem. Before starting to implement your solution, you will have a “design check” with a TA in order to make sure you've thought through the problem and come up with a reasonable design. For each project you'll hand in the code you wrote as well as a writeup describing your design and reflecting on the project. The course projects are independent of each other, and you'll work with a different partner for each one. You will have two weeks to complete each project: one week for the design and another week for the implementation.

#### Quizzes ~~and final exam~~ (now 20%; was 30%)

There will be 2 online quizzes and an online final exam. These tests are designed to assess your mastery of the course material. They will have a mix of multiple-choice, short-answer, and (very!) short programming problems (for which you won't be expected to remember the details of programming language syntax). These problems will be similar to problems on the homework assignments and drills. The quizzes will be weighted such that you can do poorly on one and still end up with a good overall grade for this component of the class.

### Assignment Policies

#### Late assignments
Each student will have five “late days” that can be used throughout the semester on homeworks and projects. Each late day allows the student to hand in a homework one day late. No more than three can be used on an individual assignment. Late projects count against each partner’s late days. Late days cannot be used on project design checks; missing a design check will result in a 30% penalty on that project’s grade.

#### Extensions
Extensions for illnesses and personal issues will be granted on a case-by-case basis. Please contact Kathi directly regarding extensions. TAs are not allowed to grant extensions.

#### Blocklists
To avoid conflicts of interest in grading, TAs may not grade students with whom they have current or past close personal or professional relationships. Either students or TAs may declare grading conflicts. If there are a particular TAs who you feel should not be grading your work, please contact the HTAs or Doug so we can configure grading assignments accordingly.

#### Regrade requests
You are encouraged to look over your assignments after they have been graded. If you find a possible error or believe that you lost too many points, please submit a regrade request through the course hand-in software. You should initiate such inquiries within one week of receiving your grade. The grading will be freshest in your TA’s mind during this time, and this prevents a backlog of requests from arising towards the end of the semester.

### Lab Attendance

Weekly lab attendance is required. You are allowed to miss up to two labs during the semester without penalty (to accommodate illness, interviews, etc). Students with significant issues affecting lab attendance may contact Kathi about make-ups.

#### One-time Lab Switches
If you discover that you cannot make your lab section during a particular week, you can email the TAs to temporarily switch into another lab section. You should send this email at least 24 hours in advance of your scheduled lab. That way, the TAs will have sufficient time to read your email, help you find an open slot in another lab, and confirm the change. If you email the TAs with less notice, say only 2 hours in advance of your scheduled lab, and no TA is able to help you before your usual lab time, you are expected to go to your assigned lab.

### Accommodations (SEAS and religious observance)

If you feel you have physical, psychological, or learning disabilities that could affect your performance in the course, we urge you to contact [SEAS](https://www.brown.edu/campus-life/support/accessibility-services/). We will do whatever we can to support accommodations recommended by SEAS. Students with SEAS accommodations should provide their letter to Kathi at the start of the semester. If your accommodations include something beyond extra time on assessments, email Kathi for a time to review your particular needs.

Students needing accommodation for religious observance should contact Kathi a week in advance to make suitable arrangements.

## Collaboration Policy

Our collaboration policy attempts to balance the benefits of students learning together and the need to work problems on your own for understanding.

### Labs
Labs are done in groups of 2-4 students, depending on the activites in a particular week. There are no restrictions on collaboration within lab groups.

### Projects
Projects are done in pairs. There are no restrictions on collaboration within project pairs. Project partners are expected to work on the entire project together, rather than to divide the project into parts to complete separately. Dividing the work defeats the learning goals for the project.

### Drills
Drills should be done alone, as they are designed to help you and us assess whether you understand the concepts needed for the next lecture.

### Exams
No collaboration is allowed on the final exam or quizzes.

### Homeworks

For homeworks, you are permitted to discuss high-level ideas with other students, but you must produce your code and other responses on your own. In particular, the following activities are NOT allowed when working on homeworks:

* Sharing code files with another student for any reason other than being partners on a project or lab
* Sitting next to another student while writing up solutions while looking at what the other is typing
* Sending code for a homework question to a classmate “just so they can look at it to figure out how to do the problem”
* Obtaining a solution on-line, or from someone not in the course
* Leaving your work in unprotected directories or services (including github) where other students can find them
* Showing a classmate your code so they can help you find or debug an error

In contrast, the following scenarios are fine:

* Asking the course staff for help
* Classmates discussing an assignment question at a more general level than the code: discussing what the question is asking, what topics it draws on, and other similar non-code issues
* Asking a classmate what general causes of a particular error message might be, or for debugging strategies, without showing them your code

We will follow Brown’s Academic Code procedures on any suspected violations. Note that those who provide solutions are held partially accountable, even if they didn’t think the other student would use their work. We understand the pressure to help friends when they ask: please don’t put other students in the position to say no to such requests.

If you have questions about the boundaries of the policy, please ask. There is never a penalty for asking.

## Course Announcements

Course announcements will be made via Campuswire. Time-sensitive announcements will also go out via email.

The course staff may issue clarifications to assignments up to 48 hours before the due date.