Table of Contents

Quick Facts

Fall 2022

Instructor: Anya E. Vostinar

Room: Olin Hall 310

Prefect: See Moodle

Course materials:

Specific free versions (linked on Moodle) of:

Drop in student hours:

M: 2-3pm in Olin 306 W: 3-4pm in Olin 306

Remember that you are always welcome to schedule an appointment with me outside of these times. To schedule an appointment, please see my calendar, find a time that isn’t marked ‘Busy’ within 9-5 M-F and either send a calendar invite to an event or email me.

Overview and Learning Goals

Computers are completely pervasive in our lives. We use them for entertainment, for productivity, and for communication. We overwhelmingly rely on programs written by others for each of these purposes. But what exactly makes up a computer program? What process is involved in creating, writing, and testing computer programs? Most importantly, how can you learn to write your own computer programs? This course is an introduction to the key concepts of computer science, and it focuses on the questions raised in the previous paragraph. But it’s also, at its heart, a course on problem-solving. After all, programming a computer involves understanding what problem we are trying to solve, identifying one or more ways we can approach solving that problem, and coming up with a step-by-step process for solving the problem. This step-by-step solution, translated into a computer language (Python in this case) is what ultimately becomes our computer program. This whole procedure is called algorithmic thinking, and is a big part of what this class is all about.

By the end of this course, you should be able to do the following:

  • Take a problem, break it down into a series of steps (an algorithm), identify the programming components most appropriate to use for each step, use those components in Python to tell the computer how to solve the problem. Those components include variables, loops (for and while), conditionals, functions, objects, lists, and dictionaries
  • Debug syntactic and logical errors in a program in a systematic fashion
  • Read and explain code written by others and approach that process in a systematic way
  • Write code that is easy for others to understand because it uses effective variable names and comments, and is well-organized using functions (including main) and objects as appropriate
  • Explain why different solutions to a problem will be more or less efficient than each other at a high level (using Big-O notation)
  • Explain the process and code used for insertion, selection, and merge sort, as well as binary search
  • Implement basic recursive functions

Prerequisites: None!

Course expectations

While we’re back in person this year, we’re not yet out of the pandemic. In these unprecedented times, we will need to exhibit flexibility and patience with each other throughout the term. I have done my best to design the course so that everyone can be successful, regardless of personal circumstances. Communication will be key; please keep me updated about your situation in addition to reaching out to the other relevant offices on campus. If you experience significant technological problems that limit your ability to participate, please contact the ITS Helpdesk at 507-222-5999 or helpdesk@carleton.edu. For announcements of known technical issues, visit the Helpdesk portal. If your personal situation (due to COVID-19 illness or other circumstances) begins to impact your ability to engage with the course, please contact the Dean of Students Office and also let me know.

I expect you to attend every class session and log in to Moodle and CampusWire every day for updates on activities and assignments.

All out of class written communication will happen via the class announcement forum. Please make sure you are checking it regularly and/or have email or push notifications setup. Each class day will have preparation activities for you to complete and a section on Moodle to guide you through what you should do before class. All materials will be released at least 48 hours before they are due.

Types of Engagement and Collaboration Policies

We’ll have lots of different ways of engaging with the course material:

  • Readings written by me and from the textbook, which will introduce ideas and provide details. You will have prompts or quizzes to check your understanding of the readings.
  • Mini-lectures at the start of class that will include discussions to check your understand of the reading and give you a chance to ask questions.
  • Labs for writing somewhat longer code with significant guidance from the instructions in order to make ideas from readings more concrete.
  • Programming assignments where you complete more extended projects to provide opportunities to design solutions and see the ideas from class applied in real contexts. Some of these you will complete with a partner and some will be individual.
  • In-class quizzes, generally on Wednesdays, for you to demonstrate your understanding of specific learning objectives.
  • Final project, where you pull together everything you’ve learned to create something that interests you.

I believe each of these types of activities will give you a different lens on the core class ideas and help you to deeply learn and understand the material. In many of these activities you’ll have the option to work collaboratively, and throughout the course you’ll have assigned programming partners who you will complete the labs and homework with. You are required to work with your assigned partner to complete these assignments using pair programming. Please see the Collaboration guidelines for more details.

Assessment

One of my goals for you in this course is for you to start to develop as an independent programmer and continue to develop as an independent learner. I’m much more interested in what skills and understanding you have mastered by the end of the course than the exact pace at which you master them. However, it isn’t healthy for you or me if you leave everything to the last minute. It also isn’t fair to your partners on an assignment or in class if you haven’t prepared as much as they have. Therefore, my goal with the following evaluation metrics is to balance providing you flexibility to learn at your own pace while also making sure to spread your learning out over the entire term.

Towards that end, your performance in this class will be evaluated in the following ways according to the learning goals for the course:

  • Programming deliverables There will be weekly programming homework assignments during the term, some of which you’ll complete individually and some with a partner. You will also complete a final programming project at the end of the term. The programming deliverables allow you to demonstrate mastery of some of the key learning objectives in this course – particularly those focused on writing and organizing larger programs. These contribute to your final grade according to the specifications grading scale outlined below. You will have the opportunity to revise these individually (regardless of whether they were originally individual or paired assignments), as detailed below.

  • In-class quizzes Some of the learning objectives for the course can’t be measured through programming assignments. Instead, your mastery of these objectives will be assessed in weekly in-class quizzes, generally on Wednesdays. There is a specific list of learning objectives that you should demonstrate your mastery of on these quizzes, and each objective will appear on at least two quizzes, though often more. This means that you have multiple chances to demonstrate your understanding, and where you are with each objective at the end of the term is what will matter for your grade. I realize this is different than how you are probably used to having quizzes, so we’ll discuss this more in class and throughout the term. There are also more details below.

Programming Grading Scale

I’ll be using a version of specifications grading this term for the programming deliverables. Each programming assessment that you hand in will be evaluated against a checklist or rubric related to one or more of the course learning objectives. I will distribute the rubrics and checklists I’ll use to assess each assignment so that you know exactly what constitutes each of these levels. I will rank each learning objective, and the overall submission, according to a four-level scale:

  • Insufficient evidence (basically nothing turned in)

  • Does not yet demonstrate proficiency (something was turned in but it did not completely fulfill the criteria)

  • Demonstrates proficiency (the submission provides evidence of proficiency in the learning objective(s))

  • Demonstrates mastery (the submission provides evidence of strong mastery of the learning objective(s))

An important aspect of specifications grading is revision. You may revise any programming deliverable up until the end of exams. Learning is not a linear process, and learning involves making mistakes and learning from them. You may individually revise and resubmit a deliverable at least once, within a week after its assessment has been released. I will keep the higher of the {original, revised} levels (though if you end up with a revised submission at a lower level than the original, we should meet to discuss it). You may individually further revise that deliverable before the end of the term and request additional feedback via a form (link TBD), however I make no guarantee of how quickly the resubmission will be assessed; it might not happen until the end of the term. Even if an assignment was initially a paired assignment, all revisions should be completed individually.

Quiz Assessment

Each weekly quiz will have a subset of learning objectives that can be demonstrated on that quiz, which you will know ahead of time. Each of the ‘quiz’ learning objectives will appear on at least two quizzes, so that you will have multiple chances to demonstrate your understanding of the material. Answers on quizzes will be assessed on the same four-level scale:

  • Insufficient evidence (basically nothing written down)

  • Does not yet demonstrate proficiency (something was written down but it did not demonstrate proficiency of the learning objective)

  • Demonstrates proficiency (the answer provides evidence of proficiency in the learning objective(s))

  • Demonstrates mastery (the answer provides evidence of strong mastery of the learning objective(s))

How this translates to course grades

To earn a C in the course: you must show that you are proficient in all the learning objectives of the course by having all programming deliverables and quiz objectives at ‘demonstrates proficiency’

To earn a B in the course: you must show that you are proficient in all the learning objectives of the course and have mastered half of the learning objectives by having all programming deliverables and quiz objectives at ‘demonstrates proficiency’ and half of programming deliverables and quiz objectives at ‘demonstrates mastery’

To earn an A in the course: you must show that you have mastered all of the learning objectives in the course by having all programming deliverables and quiz objectives at ‘demonstrates mastery’

Late work and extensions

In this course, we need to balance flexibility for individuals with structure for partners, the class as a whole, and a reasonable workload for the grader and me (your instructor). I also want to help you avoid procrastinating to the point that you can’t get everything submitted by the end of the term.

All programming deliverables have a 1-hour grace period after their posted due date and time to account for slight delays in submission while allowing assessment of submissions to start soon after the due date. If you miss that cutoff, you will still be able to submit something during the revision period. I highly recommend you aim to submit something in the original submission window, even if it isn’t complete, so that you can benefit from feedback and revision.

In-class quizzes cannot be made up because missing one quiz will not at all impact your grade. If you fall behind on quiz objectives, there is the possibility of demonstrating your understanding outside of class, and there will be extra assessment opportunities towards the end of the term. If you’re worried about where you are on the quiz objectives, get in touch and we can make a plan.

Preparation work does not specifically contribute to your grade, and so a late work or extension policy doesn’t make sense for it. It is expected that you complete the preparation work ahead of the class period that it is associated with, however if you aren’t able to, I recommend you complete it as soon afterward as you can.

All work must be submitted by the end of the last finals period as per College policy. All that said: This term is going to be weird, and hard, and disruptive, for all sorts of non-academic reasons. If you’re staring down a deadline that you know you can’t meet, or if you’ve fallen behind, get in touch with me immediately and we’ll work something out. While I need to put boundaries in place for my own health and wellness, and for fairness to everyone in the class, I also want to make sure you are progressing in your learning.

How to Succeed in this Class

  • Keep trying and ask for help: Learning a new topic can be challenging, and one of my hopes for this class is that you’ll struggle at times and learn more because you had to really work to understand something. That means you’re expected to be willing to try again when things don’t work the first time, and to seek out help when you’re truly stuck. (See below for more on seeking help!)

  • Work consistently: For all learning engaging with the material in shorter, more frequent sessions is likely to be helpful. Set aside time each day to work on the course, and make sure that you’re keeping up with the daily activities.

  • Take notes: Research has shown that writing things down in your own words helps you to remember and understand it better. Take handwritten notes when in class and reading from the textbook. Research has also shown that handwritten instead of typed notes help you retain the information better.

  • Pay attention to homework assignments and start early: When I’ve asked students what advice they’d give to future 111 students, the most common thing they said was to start the homework early! By starting early, you have more opportunities to work through problems that come up and time to ask for help. Even if you can’t immediately start on the homework, read over the prompt so that your brain can start thinking about it in the background; it really does help.

  • Test your code: One of the key parts of writing successful code is debugging it - testing whether it works, finding where it doesn’t, and fixing it so it does. Learning to debug your code is essential for any later coding projects you may do.

  • Ask questions and reach out for help: If you have a question about something, chances are other people do too. By asking questions in class, on CampusWire and in office hours, you’ll keep up with the course and gain a deeper understanding of the concepts.

All grading questions should be directed to me and not to the grader.

How to Get Help

I want to see all of you succeed in this class, and I believe you can succeed if you engage with the class material and activities consistently and reach out for help when you’re confused. To learn computer science, you’ll need to be willing to try new things and experiment with different solutions. Cultivating persistence to keep trying will be helpful not only in this course, but in any other problem solving activities. Sometimes, you may need assistance - here’s how you get it:

  • Take a break: Often, taking a break from homework will help you to regroup and you’ll be able to succeed when you come back to it. Leave yourself enough time to be able to take breaks!
  • Prefect sessions: This course has a prefect. The Prefect Program offers in person tutoring and/or optional collaborative learning sessions for participating classes. Prefect sessions review course concepts and often focus on critical thinking and problem-solving exercises centered on the course material. Our course prefect(s) will use email or Moodle to inform everyone in the class about upcoming sessions and availability for 1:1 tutoring.
  • Help Forum: You’re welcome to post questions about readings and labs on the appropriate channel as well as about homework and the final project. You shouldn’t post much homework code, but you can post code related to other assignments. If you’re unsure if a question contains too much detail about the homework, email me instead.
  • Talk to me: I have both drop in student hours and student hours that are by appointment (for one on one conversations). See links at the top of this document for more details. Talking to students is literally my favorite part of this job, please talk to me!
  • Other Carleton resources: There are lots of resources to help you at Carleton. Lab assistants are available on a regular basis; see the top of Moodle for details. They can help you with debugging and making progress on your homework, or if you’re having trouble understanding something about Python. The Academic Skills center is a wonderful resource for helping you develop study skills, improve your ability to prep for exams, or manage procrastination. Oscar Alarez is an academic skills coach in the office with whom you can make individual video conferencing appointments.

Attendance

Attendance is not strictly required in this class, though I believe that you will do much better if you attend every session. Because much of the classtime is spent working with partners on lab activities, if you miss class, you will miss out on that opportunity.

Inclusivity and Universal Learning

I strive to create an inclusive and respectful classroom that values diversity. Our individual differences enrich and enhance our understanding of one another and of the world around us. This class welcomes the perspectives of all ethnicities, genders, religions, ages, sexual orientations, disabilities, socioeconomic backgrounds, regions, and nationalities.

My goal is that everyone should be able to learn from this class and feel comfortable asking questions and participating. In class, on the forums, and when working with one another, be respectful and inclusive. If something makes you uncomfortable or you’re concerned about an interaction, please come talk to me!

Carleton College is committed to providing equitable access to learning opportunities for all students. The Office of Accessibility Resources (Henry House, 107 Union Street) is the campus office that collaborates with students who have disabilities to provide and/or arrange reasonable adjustments. If you have, or think you may have, a disability (e.g., mental health, attentional, learning, autism spectrum disorders, chronic health, traumatic brain injury and concussions, vision, hearing, mobility, or speech impairments), please contact disability@carleton.edu or call Sam Thayer (’10), Accessibility Specialist (x4464) to arrange a confidential discussion regarding equitable access and reasonable adjustments. If you’ve already arranged adjustments, please let me know if there’s anything you want me to know beyond what’s in the adjustments letter or if there are particular challenges for your specific circumstances. If you do not have official adjustments, I am still happy to discuss with you ways in which I can help you succeed in this class.

The Assistive Technologies program brings together academic and technological resources to complement student classroom and computing needs, particularly in support of students with physical or learning disabilities. Accessibility features include text-to-speech (Kurzweil), speech-to-text (Dragon) software, and audio recording Smartpens. If you would like to know more, contact aztechs@carleton.edu or visit go.carleton.edu/aztech.

Carleton College urges you to make yourself –- your own health and well-being –- your priority throughout this ​term and your career here. It is important to recognize stressors you may be facing, which can be personal, emotional, physical, financial, mental, or academic. Sleep, exercise, and connecting with others can be strategies to help you flourish at Carleton. If you are having difficulties maintaining your well-being, please contact me and/or pursue other resources, such as Student Health and Counseling or resources on the Office of Health Promotion website. Student Health and Counseling is currently offering telehealth services.

Carleton is committed to fostering an environment free of sexual misconduct. Please be aware all Carleton faculty and staff members, with the exception of Chaplains and SHAC staff, are “responsible employees.” Responsible employees are required to share any information they have regarding incidents of sexual misconduct with the Title IX Coordinator. Carleton’s goal is to ensure campus community members are aware of all the options available and have access to the resources they need. If you have questions, please contact Laura Riehle-Merrill, Carleton’s Title IX Coordinator, or visit the Sexual Misconduct Prevention and Response website: https://www.carleton.edu/sexual-misconduct/.

Academic Honesty and Collaboration Policy

As noted in Carleton’s policy on academic integrity, violations of academic honesty are dealt with at the college level. If I suspect academic dishonesty, I will refer the case for appropriate action to the Academic Standing Committee (ASC) via the Associate Dean of Students or the Associate Dean of the College. Please familiarize yourself with Carleton’s academic integrity policies and make sure that you have read the collaboration and academic honesty policies for this course. A possible penalty for academic dishonesty in a course is an F in the course. It’s not worth it – please seek help using the resources above instead.

Pedagogy

This section discusses some of the pedagogical principles that you’ll see in this class. If you are interested in why the class is structured how it is, you might find an answer here (and I’m also happy to discuss it with you). If you aren’t interested in pedagogy, you can skip this.

Active Learning

Research has shown that active learning in the classroom leads to better retention of material for all students, but especially those from historically marginalized groups. Computer science classes are well-suited to active learning, because we can practice ideas in class by programming and writing out algorithms, for example. In this class, a large portion of in-class time will be spent with you grappling with ideas and trying to solve problems that I’ve given you while I and the prefect circulate to answer questions. This requires that you’ve read the assigned reading ahead of time, so that I don’t need to lecture and we can spend more time learning how to actually use the ideas. Active learning can feel less effective or productive in the moment, because you are struggling to figure things out instead of me just explaining things to you. However, that process of struggling is exactly what is needed for you to learn the material most effectively for long-term retention.

Interleaving

There are two main ways that content can be organized in a course: block and interleaved. Block learning is the idea of first learning all about topic X, taking a test, and then forgetting all about it to learn about topic Y. Interleaving is the process of learning a bit about topic X, a bit about topic Y, a bit more about topic Z, being tested on all of them, then learning more about all of them and being tested again.

Again this is a situation where block learning feels the most effective and efficient in the short term, and you’d do best on the tests in the short term. However, copious research shows that interleaving is the most effective in the long term. It is again the very process of struggling to recall something you learned a while ago that triggers your brain to then store that information into long term memory. Interleaving also leads to higher transfer abilities, where you are able to apply what you know to a new problem. (If you want to learn more about this, there are several excellent books, but one I recommend currently is Range: Why Generalists Triumph in a Specialized World by David Epstein.)

Pair Programming

Pair programming is a very common practice in computer science industry, where two programmers sit at a shared computer and both engage in the process of writing a program. One is the ‘driver’ at the keyboard for a block of time while the other is the ‘navigator’ that is watching and thinking through the overall program, as well as spotting typos. You switch roles regularly (every 10-15 minutes or whenever the navigator has an ‘aha’ moment) and are both fully engaged in the task for the whole time. This method of programming has been shown to be highly effective in producing better code (not necessarily in a shorter period of time though) and leading to a better understanding of the problem for both programmers. We’ll use pair programming a lot in this course for several reasons: 1) as I said, it is very common in industry, so it’s good for you to get comfortable with it; 2) it is used in many upper level courses at Carleton, so again good for you to be comfortable with it; 3) ultimately it improves the learning and understanding of the people involved; and 4) when you are struggling with new concepts, it can feel a lot more doable when you have someone else there who is struggling with you.

This syllabus is based heavily on the syllabus from Anna Rafferty.