CSCI 0111 Course 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 10:00-10:50am ET, on Zoom (see Canvas for Zoom link)
Instructors
Doug Woos (doug_woos@brown.edu) and Kathi Fisler (kathryn_fisler@brown.edu)
Teaching Assistants
TBD
Course website
http://cs.brown.edu/courses/csci0111/fall2020/

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- Develop medium-sized programs with multiple interacting components

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:

  • Students who do well in CSCI 0111 have the option of doing some extra work during 0111 to prepare for CSCI 0180 (spring and summer), which is the second half of one of the two CS year-long intro sequences.
  • Students interested in data science can proceed to DATA 0200 (fall and maybe summer); the 111-200 sequence leads into the Data Fluency certificate.
  • CSCI 0112, a direct followup to CSCI 0111, is designed to prepare students for several upper-level computer science courses in addition to CSCI 0180. It will likely be offered next fall.

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 instructors–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. One key 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 (or are simply new to computing). 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 harassment, with sexual-based harassment a specific form that is governed by federal laws known as Title IX.

Brown’s Title IX Web site provides many resources for understanding the terms, procedures, and policies around harassment. 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 harassment. 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 instructors 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

The remote classroom

Our time in the classroom will be a mix of traditional lecture and discussion-based activities. 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!

CSCI 0111 will support both synchronous and asynchronous participation. Lectures include hands-on exercises. Students attending lectures synchronously will work on these exercises in small groups, simulating working with nearby students in a classroom. In synchronous labs, students will work on practice problems with classmates and a TA in the (virtual) room. Synchronous groupings will settle into having the same people, to foster community among students. Students attending asynchronously will have lecture capture and staff help to form alternative study groups. All students will have access to faculty and TAs through an online discussion board, as well as one-on-one appointment-based slots.

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, plus an average of 2 hours per week studying for the quizzes and the final exam.

Required materials

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

Students should have access to a computer to complete the assignments. We will be using several software tools, including Zoom, Google Docs, Google Jamboard, and Prismia during class. The software web page has information on the programming tools you will use.

Getting help

Our goal, as a course staff, is for every student to do well in the class. As such, we encourage you to ask questions about anything you don’t understand. Whether you are confused by something from lecture or are having trouble with an assignment, please reach out to us!

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.

Email

Please post questions about the course to Campuswire rather than emailing the course staff–it’s very useful to have all course questions in one place where any of us can answer them. Please don’t email individual TAs unless referring to a prior interaction with that TA.

If you have concerns of a personal nature (a problem with a project partner, for instance), please email one or both of the instructors.

Office hours

The TAs hold office hours every week via a combination of Campuswire and Zoom. Kathi and Doug also hold regular office hours, and are available by appointment. Each week’s office hours schedule is available on the course website.

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.

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

Assignments, exams, and grading

All assignments will be posted and handed in online. Approximate grading weights for each type of assignment are listed below. You must have a passing average across the code check-ins and exams (the non-collaborative components) in order to pass the course. Beyond that, we do not grade on a curve–everyone who earns an A get one. Some students may struggle in the beginning as they get used to programming, then get stronger as the course goes on. Grading in this course aims to accomodate this normal learning curve; to do this, we cannot publish a formula up front of how individual assignments will weigh in final grades (no single formula covers all students). You will receive feedback as the course goes on about your overall performance, so you can allocate your efforts according to any grading goals you have.

All homeworks and projects will be due on Tuesdays at 9pm ET, 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 9am ET on Mondays and Fridays (so if you’re a late sleeper, please plan on doing them the day before!).

Drills and lecture activities (10%)

Drills are short online quizzes that will be due shortly before class every Monday and Friday. These should take around 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.

Approximately once a week, there will be an extended lecture activity with an associated hand-in, to be completed with the study groups discussed above. Students attending lecture synchronously should complete these activities in lecture. Asynchronous study groups should meet virtually to complete these activities. We understand that students will sometimes have to miss lecture or be unable to meet with their group, so it’s fine if students occasionally need to complete and hand in these activities individually; most of them, however, should be done in groups, and students may not get credit for repeated individual handins. If you’re having trouble meeting with your study group, please reach out to us!

Drills and lecture activities will be graded for completion only as long as you appear to be taking them seriously, and full credit will be given if you complete 80% of them.

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 based on attendance, and you can miss two labs during the semester without penalty. Students who have confirmed conflicts for all available lab sections can make arrangements to complete labs independently and discuss them with the TAs in office hours.

Homework assignments (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 thee issues, but not to write full formal papers.

Projects (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 work with a team. For each project, you will work in groups of 4 or 5 to design 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. You’ll then implement the code for the project, either on your own or with other members of your project group. For each project you’ll hand in the code you wrote as well as a writeup describing your design and reflecting on the project. Students who worked together on the project implementation should hand in only one implementation. The course projects are independent of each other, and project groups must be different for each one (the course staff is happy to help with forming project groups). You will have two weeks to complete each project: one week for the design and another week for the implementation.

Code check-ins (15%)

On two homework or projects during the semester, we will ask you to schedule a short meeting with a TA to discuss your code. The goal is to ensure that you have a solid understanding of the work you’ve handed in. TAs might ask you to talk through some potential extensions to your code, or to explain some functionality. We will ask you to schedule a check-in appointment after grading the homework or project in question. Students should try to be flexible in scheduling these meetings.

Code check-ins will be graded on a course-grained basis. Students who demonstrate good understanding will receive full credit.

Exams (15%)

There will be two graded online exams–a midterm and a final. 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). The exams 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.

The date of the midterm will be announced at least a week in advance. The final will take place during the time listed on https://cab.brown.edu.

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 without a documented emergency will result in a 30% penalty on that project’s grade.

If your assignment is handed in late, you (or your project partner) are out of late days, and you have not been granted an extension (see below), your assignment will not be graded.

Extensions

Please contact the instructors directly regarding extensions. Requests for routine issues such as work in other courses or interviews should normally come out of your allotment of 5 late days. Extensions for more substantial illnesses and personal issues will be granted on a case-by-case basis. If you think you need an extension on an assignment, please reach out to us as early as possible. Only in the most extreme circumstances will an extension or time change be granted on an exam.

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 the instructors so we can configure grading assignments accordingly.

We use anonymous grading for as many assignments as possible (roughly, everything except the course projects). For assignments graded anonymously, blocklists apply–TAs will not know whose work they are grading.

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.

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.

Accomodations

If you feel you have physical, psychological, or learning disabilities that could affect your performance in the course, we urge you to contact SAS (formerly SEAS). We will do whatever we can to support accommodations recommended by SAS.

Religious Observance

If you require accommodation for religious observance, please contact the instructors at least a week before the deadline in question to make arrangements.

Personal Emergency

In the event of a medical or family emergency, contact the instructors to work out accommodations.

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 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 are done in small groups. There are no restrictions on collaboration within project groups. Students working together on project implementations 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, and we may ask questions about the projects on exams and in code check-ins. Aside from your group, you shouldn’t consult other students about the projects.

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.

No collaboration is allowed on the exams.

For homeworks, you are permitted to discuss high-level ideas with other students and provide limited debugging help. You should feel free to help classmates understand why a program is resulting in an unexpected output or error. You can also discuss 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. However, you must produce your code and other responses that you hand in on your own.

The following activities, for example, are NOT allowed:

  • Sharing code files with another student for any reason
  • 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”
  • Looking at a classmate’s code and suggesting changes beyond those needed to help debug an error
  • 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

For homeworks and projects, we will use automated tools to detect code similarity. These tools have proved effective in detecting students who have shared code, despite efforts to “fool” them. 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.