Department of Mathematics and Statistics
James Skon
- Section 1: Hayes 215, Tue & Thu 9:40-11:00 am
- Section 2: Chalmers 320 Tue & Thu 2:40-4:00 pm
- Office hours:
- Mon, Wed, Fri: 9-11 am, (Chalmers 428).
- Other times by appointment. Sign up here.
Tutoring Schedule (MSSC)
Course Overview
This course presents an introduction to computer programming intended both for those who plan to take further courses in which a strong background in computation is desirable and for those who are interested in learning basic programming principles. The course will expose the student to a variety of applications where an algorithmic approach is natural and will include both numerical and non-numerical computation. The principles of program structure and style will be emphasized. The course teaches both Python and C++ programming. Offered every semester.
- An introduction to computer science and computing systems
- An introduction to algorithm development and problem solving
- An introduction to programming with Python
- An introduction to C++ programming language
- POGIL group activities during (almost) every class meeting
- Regular individual lab assignments
- Computer history essays weekly
Course Objectives
- Learn basic principles and structures of computer programming.
- Provide an understanding of the role computation can play in solving problems in various disciplines.
- Become proficient in the Python and C++ programming languages.
- Help students feel confident of their ability to write small programs that allow them to accomplish useful goals.
- Position students so that they can compete for research projects and excel in subjects with programming components.
Texts/Online resources
This course uses several online tools for learning and assessing student progress. All of these resources are free of cost but some require the creation of a login account. It is essential that everyone participate in the associated activities as all are part of the learning process, and some are graded activities.
- How To Think Like A Computer Scientist: Interactive edition (kenyoncollege_thinkcspy_summer25) This is an interactive book. You must register, and complete the exercises in the assigned readings. Follow this link and register using your Kenyon email. Use “kenyoncollege_thinkcspy_summer25” as the course name. You will read the text as assigned in the calendar below, and I encourage you to do the included problems in the text. I will give you a grade
- C++ for Python Programmers (kenyoncollege_cpp4python_summer25) This is an interactive book. You must register, and complete the exercises in the assigned readings. Follow this link and register using your Kenyon email. Use “kenyoncollege_cpp4python_summer25) as the course name. As in the Python book, you will be assigned readings.
- Kenyon POGIL ITS (http://csits.kenyon.edu) – This is a Kenyon created collaboritive learning system we will use in this course. You must sign up with your kenyon email address and actual Kenyon name. Once logged in, you sign up for your section. In the “Join a Course by Code” field enter “COMP118FALL25-1” for section 1, and “COMP118F25Sec2” for section 2.
- onlineGDB This is an the environment for programming Python and C++. You can complete your assignments here Link. You should go to the site and create an account using your Kenyon College email address.
- CodeLab This is an online platform that gives you problems to solve. You will be assigned problems on a regular basis. You can keep trying until you get the problem right with no penalty. You must sign up with your Kenyon email, then click the “+ Add A Course” button. You then add an access code. The two access codes for this class are: “KENY-32656-LPKK-66” (Python) and “KENY-32657-KNLK-66” (C++).
- Trinket.io This is an IDE for programming in Python with graphics. You should sign up before Lab 3 with your Kenyon email.
Alternate Python IDEs
- codeboard.io
- https://replit.com/
- https://www.online-python.com/
- https://www.programiz.com/python-programming/online-compiler/
- https://www.jdoodle.com/python3-programming-online/
Methodology
This course uses a variety of learning strategies in order to both enrich and enhance learning for every student of every background, as well as to keep the course interesting. Methods include:
- Group (collaborative) activities:
- POGIL (Process Oriented Guided Inquiry Learning). Discussed below, this is a team oriented, discovery based approach to learning with small groups of students. Teams report back to the whole classroom and share their discoveries.
- In class small group programming. This is to allow learners to explore and solve a problem as a small group, such that each student engages with the material and each other, experimenting, teaching, and learning together.
- Individual activities:
- Laboratory assignments. These programming assignments give each learner the opportunity to develop skill, experience, and confidence as programmers as individuals. There will be a lab assignment approximately every other week in the first half of the semester (3), and about once a week after the spring break (6).
- Programming problem solving. These small guided exercises, based on the CodeLab online learning platform, provide small problems for the learners to gain experience programming with, and are automatically checked by the environment to give immediate feedback to the learner. There will be multiple sets in most weeks, with relatively more assignments in the first haf of the semester.
- Reading Assignments and Daily Quizzes. For every class, the students are expected to read certain sections from the textbook (online, interactive) BEFORE the class. For encouragement and accountability, there will be a short quiz in this class every day (except for the first day, but there is a survey and syllabus quiz that should be done before the first day that will count as quiz 1). A number of low quiz scores will be dropped.
- History essays – these small writing assignments, about one a week, give each learner the change to explore computer science in its larger historical context. We will have a brief discussion of these in class.
- Instructional Presentation and discussion. Occasionally the instructor will give a presentation related to the course topics. These will normally include discussion, and sometimes interleaved with in-class, hands on programming activities.
Group generator: https://www.randomlists.com/team-generator
Course Attendance
Given the methods of instruction, especially the group work and the hands on work, attendance in class meetings with full engagement is essential. Students are expected to attend all classes unless they have a legitimate excuse such as illness, participation in official collegiate athletic activities. In the case of any absence students are expected to contact the instructor prior to the absence. In the case of such excused absences the student are expected to complete course activities they missed in class. According to the Math Department’s attendance policy any student who missed six class meetings will be expelled from the course. Missing class will result in no credit that for day’s in-class activities. After one unexcused absence, each unexcused absence will lower your overall course grade by 1% . Being tardy and walking out of the classroom during the class period must be avoided. Each occurrence of tardy and walking out of classroom counts as half of an absence.
Python 3 and C++
In this course we will be learning the Python 3 and C++ programming languages. We will be using an online programming environment onlineGDB. This allows you to program anywhere with any device (including smartphones and tablets!), while maintaining access to all your current and previous work.
You can also install Anaconda Python and an IDE (Integrated Development Environment) call Spyder by following these instructions: PythonInstall.
POGIL
Process Oriented Guided Inquiry Learning (POGIL) is a pedagogy that is based on research on how people learn and has been shown to lead to better student outcomes in many contexts and in a variety of academic disciplines. Beyond facilitating students’ mastery of a discipline, it promotes vital educational outcomes such as communication skills and critical thinking. Its active international community of practitioners provide accessible educational development and support for anyone developing related courses.
We will be learning about POGIL early in the course, and then use this method on a daily basis.
Each activity is a link to a Google Doc. You must be logged into your Kenyon account to access. One member of the team will open the link, and make a copy in the same directory with your team name (color). The team will then work together to document the process on that document.
Useful POGIL links
POGIL ROLES:
- Spokesperson/Facilitator
- Process Analyst
- Quality Control
Teams will normally have 3 people. On teams of less than 3 students some will have 2 roles
POGIL Process Analyst Report – The Process Analyst is encouraged to fill this out to give feedback to the instructor.
POGIL Feedback – complete this after every activity
Assignments
Due Date: All assignments are due as specified in the grading table below.
Missing Lab Assignments: Labs are an important part of this class; the effort spent on them is a crucial part of the learning process. Failure to submit labs is unacceptable: students earning 0s on two labs cannot receive a grade higher than a B- for the course; students earning three 0s on labs will receive an automatic F for the course.
Collaboration and Academic Honesty: In order to facilitate learning, students are encouraged to discuss assignments amongst themselves. Copying a solution is not, however, the same as “discussing.” You must follow the Math Department’s Guidelines on collaboration. A good rule of thumb is the “cup of coffee” rule. After discussing a problem, you should not take away any written record or notes of the discussion. Go have a cup of coffee or cocoa, and read the front page of the newspaper. If you can still re-create the problem solution afterward from memory, then you have learned something, and are not simply copying. (The in class assignments are exempt from this, as they are intended to be done together.)
Academic Honesty and using code you did not write: Turning in code you did not write is cheating.
- You should never receive code from other students, use code from the internet, or use instructor solutions from past semesters. Any code you submit must be written entirely by you. (See the “cup of coffee” rule under collaboration.)
- Likewise, “facilitating academic dishonesty” is a violation of academic honesty. Thus sharing your code with other students is also forbidden.
- The instructor has tools for checking the similarity of code, and will use them periodically to see if students’ code is too similar to be explained by coincidence.
- If you suspect someone has used your code, you should report it.
Computer History Assignments: Once a week you will turn in a brief essay on some computer history fact from the Computer History Museum ( Timeline) (or other computer history source). One or two people people will be chosen each week to orally describe what they found in 1-2 minutes at the beginning of class. I will ask for volunteers, and everyone will speak at least a couple of times during the semester. The idea is give to us all an opportunity to explore the history of computer science, and to find something that interests each of us. Start by going to the computer history timeline, and for each assignment explore the requested years until you find something interesting. Then write up a 200-300 word essay about what you found, what you found compelling, and why you think it is significant. Write the essay in Moodle, and include a link to the item you found so it can be displayed while you share in class. These are due midnight before the day they will be presented (and appear in the calendar below). Late submissions will not be accepted on these assignments.
Expected Workload:
There will be more due dates in this course than in any you’ve likely taken. There will be work due several days per week in most weeks. Most of these assignments will take well under an hour, but working consistently and staying on top of what we’re doing is absolutely imperative. These assignments include CodeLab exercises, Readings required for daily quizzes, History essays, and Labs. Tools for More Effective Studying.
Use of Generative AI as a Tool
We’re entering a transformative era with generative AI — a technology that is already reshaping how we work, learn, and solve problems. But despite its power, AI has clear limits. It cannot design or build complete systems without the guidance of skilled humans — humans who understand how computers work, how to program, and how to create real-world solutions. That’s where this course comes in.
The purpose of this class is to help you build that essential foundation. If your goal is to use computing effectively in your career or personal projects — in any domain — you need to know how to think computationally and write code yourself. This course is designed to scaffold your learning, so you can reach the point where tools like AI actually become helpful rather than misleading.
It’s true that generative AI can likely complete many (if not all) of the assignments in this course — and do so with more polish than a beginner programmer. But that’s missing the point. It’s a bit like learning Arabic: Google Translate can handle most beginner-level sentences, but copying and pasting phrases into a translator isn’t the same as learning to speak the language.
I’m assuming you’re in this course because you — or your advisor or major — believe programming will be useful to you. If that’s the case, you need to learn the fundamentals yourself, without relying on AI to do the thinking for you. Later, once you’ve built confidence and experience, AI can become a powerful assistant — helping you prototype, review, or debug your code. But as a beginner, leaning on it too early is not just unhelpful — it’s counterproductive.
Policy on Generative AI Use
Unless explicitly permitted in a specific assignment or by the instructor, any use of generative AI (such as ChatGPT, GitHub Copilot, or similar tools) is strictly prohibited on any assignment in this course.
You should follow this rule for two important reasons:
-
You’re undermining your own learning if you rely on AI to “help” you write code before you’ve learned how to think through problems and build solutions yourself. Programming is a skill — you don’t acquire it by watching a machine do the work for you.
-
It’s a matter of academic integrity and respect. I’d like to believe that you’re decent and respectful people. If you prioritize your grade over honesty and growth, then you may have bigger concerns than learning to program — and that would be unfortunate.
Also, keep in mind: the final exam will be completed in class without access to AI or any digital tools. If you haven’t built real skills during the semester, that will become obvious.
Grading
| Category | % | Collaboration allowed? | Notes |
| History Essays | 5% | No | Due by midnight the day before. |
| POGIL Activities | 10% | Yes | You must be in class to get credit for these, except in cases of excused absence. |
| Individual Labs | 35% | No | Due by midnight on the day due. |
| Textbook reading | 5% | No | Due by class on the day due. You must read the text and click on “Mark as Completed” on each page to get credit. You are encouraged to complete the problems in the text to learn, but not required to do them all. |
| CodeLab | 10% | No | These are problems in the online learning tool CodeLab. Due by noon on the day due. You will get 100% for completing 80% of the problems assigned. |
| Quizzes | 15% | No | A quiz at the beginning of each class. The quiz opens 10 minutes before class, and you are encouraged to finish the quiz prior to class starting. You must finish the quiz in the first 5-10 minutes of the class. You cannot make up quizzes, but the lowest 7 quiz scores will be dropped. Each quiz will include questions from the previous class as well as on the content of the reading assignment for that day. |
| Kattis Midterm | 5% | No | Take home, 1 week long |
| Final Exam | 15% | No | In-class, 3 hours long |
| TOTAL | 100% |
Late Assignment policy
Getting work done is essential to success in this course. Late assignments are problematic, they create a backlog of work for the student, as well as a grading backlog for the professor. Neither of these are optimal. Late assignment will be allowed, but ONLY when application has been made in advance. The following three options are permissible. The form for requesting a extention is here: Request Form.
- One week extension. This is for major conflicts with academic or other college responsibilities are known of in advance, and can be planned for. For example a major assignment in another class (or classes) is overlapping with this assignment, and you believe more time will with needed. This request MUST be made at least one week before the assignment is due.
- Three day extension. This is for conflicts or issues with course work or responsibilities that emerge while the assignmebnt is being worked on. For example perhaps you hit a roadblock on the assignment, or you are srtruggle to keep up with all your courses due to somethinng that was not known in advance. Appplications MUST be make at least three days before the assignment is due.
- 24 hour extension. This is for when you are just struggling to get it right, but almost there. This application can be made up to the due date/time.
Schedule
Create groups: Section 1, Section 2
| Date | Topics | Reading | Notes/Activities | Slides & Video |
Assignments Due |
|---|---|---|---|---|---|
| Aug 28 | Introduction to Computer Science and course, Introduction to POGIL Text Book. |
Will AI take our computing jobs? POGIL-ITS POGIL Role Wheel POGIL Roles POGILQualityIndicators POGIL Activity 1 |
Create Accounts: |
||
| Sep 2 | Programs, languages, simple programming Introduction to algorithms History Assignments First Python Program |
Python Chapter 1 | Slides | ||
| Sep 4 | Input and Variables Variables, data types, names, keywords, statements and expressions, operators and operands |
Python 2.1-2.7 | Quiz 2 POGIL Input and Variables POGIL – Arithmetic Operations and Assignment Statements |
||
| Sep 9 | Python Work Algorithms Formatting Data |
Python 2.8-2.11 | Quiz 3 POGIL – Formatting Output |
First set of CodeLab exercises due tonight |
|
| Sep 11 | Decision Making in Python | Python 3.1-3.6, 7.1-7.3 |
Quiz 4 |
Slides | 1940s(Comp History) |
| Sep 16 | Selection in Python | Python 7.4-7.5 | CodeLab Set2 | ||
| Sep 18 | Looping in Python. (Ignore xrange(). It does not exist in Python 3) | Loops | 1950s(Comp Hist) | ||
| Sep 23 | For Loops Nested Selection, Strings |
Python 7.6-7.7, 9.1-9.9 | Quiz 7 POGIL – FOR Loops POGIL Nested If-else statements More fun: Computing Loan Payoff |
||
| Sep 25 | Python Turtle Graphics, Strings | Python 4.1-4.6, 9.10-9.19 | CodeLabSet4 1960s |
||
| Sep 30 | Built in and Void Functions | Python 5.1-4, Chapter 6.1-6.5 | Quiz 9 POGIL Built-In Functions POGIL Void Functions |
CodeLabSet5 | |
| Oct 2 | Functions, local variables, parameters | Python 6.6-6.10, 7.8, 8.1-3 | Quiz 10 POGIL Functions Returning Values |
1970s | |
| Oct 7 | Nested Loops, Strings |
Python 8.1-8.3 |
|||
| Oct 14 | Reading Files | Python 11.1-11.5 | Quiz 12 POGIL Reading Files Emily Dickinson Experiment Kattis Practce Contest |
Lab 2 Student Grades 1980s |
|
| Oct 16 | Writing Files | Python 11.6-11.7 | CodeLabSet6 | ||
| Oct 21 | Lists, Passing lists | Python 10.1-10.5 |
|
||
| Oct 23 | Lists and Strings, List Comprehension | Python 10.6-10.20 | Quiz 15 POGIL – More Lists and Strings start on Lab 4 |
Lab 3 |
|
| Oct 28 | Dictionary | Python 12.1-12.5 | Quiz 16 POGIL Dictionary Dictionary Examples Exercises |
Slides Dictionaries |
1995-1999 |
| Oct 30 | Dictionary | Python 12.1-12.5 | Slides Dictionaries |
||
| Nov 4 | Python Classes | Python 17.1-17.6 | Quiz 18 Special POGIL activity |
Slides | |
| Nov 6 | Python Classes | Python 17.7-17.9 | Quiz 19 Object Activity POGIL Classes Model 1 Code Model 2 Code Model 3 Code |
||
| Nov 11 | Introduction to C++, First program | Sign up for the C++ textbook at runestone | Quiz 20 C++ Intro |
Slides | CodeLabSet9 Lab 5 2010s (the last one!) |
|
Nov 13 |
C++ Data types, control structures | CPP Chapter 1 | Quiz 21 C++ POGIL Intro C++ Cast |
Slides | CodeLabSet10 |
| Nov 18 | C++ Strings, Arrays, Vectors | CPP Chapters 2, 3 | Slides C++ Arrays vs Vectors C++ Vectors |
CodeLabSet12 Lab 6 |
|
| Nov 20 | C++ Functions | CPP Chp 4 | Quiz 23 C++ POGIL Functions Type Conversion |
Slides C++ Functions |
CodeLabSet13 |
| Dec 2 | C++ Files | CPP 6.1-6.6 |
Quiz 24 |
Slides C++ Reading and Writing Files |
CodeLabSet14 Lab 7 |
| Dec 4 | C++ Classes | C++ Classes Reading C++ Classes Tutorial |
Slides C++ Class Intro |
CodeLabSet14 | |
| Dec 9 | C++ STL Vectors and Pairs |
C++ Vectors |
Quiz 26 |
CodeLabSet15 Lab 8 |
|
|
Dec 11 |
C++ STL Map | C++ STL | Quiz 27 POGIL C++ STL MAP |
Slides Several Map Examples Word Count C++ Map Example |
CodeLabSet16 |
| Dec 16/19 |
Final Exam |
Section 1: Fri, Dec 19 at 8:30am (Hayes 311) | Section 2: Tues, Dec 16 at 6:30 pm (Chalmers 320) |
Non Discrimination Statement
Kenyon College does not discriminate in its educational programs and activities on the basis of race, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, disability, age, religion, medical condition, veteran status, marital status, genetic information, or any other characteristic protected by institutional policy or state, local, or federal law. The requirement of non-discrimination in educational programs and activities extends to employment and admission.
All employees, including faculty, are considered Responsible Employees and must notify the College’s Civil Rights & Title IX Coordinator with any relevant information.
For further information, please refer to the following Kenyon College policies:
Sexual Misconduct & Harassment: Title IX, VAWA, Title VII:
https://www.kenyon.edu/directories/offices-services/ocr/title-ix-vawa/kenyon-policies/title-ix-policy/
Discrimination & Discriminatory Harassment Policy (non sex or gender):
https://www.kenyon.edu/directories/offices-services/ocr/discrimination/
ADA & Section 504:
https://www.kenyon.edu/directories/offices-services/ocr/discrimination/504-ada-grievance/student-grievance-procedure-resolving-complaints-under-ada-section-504/
Accessibility and Accommodations:
Students who anticipate they may need accommodations in this course because of the
impact of a learning, physical, or psychological disability are encouraged to meet with me privately early in the semester to
discuss their concerns. In addition, students must contact Student Accessibility and Support Services (SASS) (740-427-5041 or sass@kenyon.edu), as soon as possible, to verify their eligibility for reasonable academic accommodations. Though I am happy to help you in any way I can, I cannot make any special accommodations without proper authorization from the SASS staff. Except in extraordinary circumstances (and at the very start of the course), accommodations must be certified and discussed with me at least one week before they are to take effect.
Statement on Title IX
Kenyon College does not discriminate in its educational programs and activities on the basis of race, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, disability, age, religion, medical condition, veteran status, marital status, genetic information, or any other characteristic protected by institutional policy or state, local, or federal law. The requirement of non-discrimination in educational programs and activities extends to employment and admission.
All employees, including faculty, are considered Responsible Employees and must notify the College’s Civil Rights & Title IX Coordinator with any relevant information.
For further information, please refer to the following Kenyon College policies:
Sexual Misconduct & Harassment: Title IX, VAWA, Title VII:
https://www.kenyon.edu/directories/offices-services/ocr/title-ix-vawa/kenyon-policies/title-ix-policy/
Discrimination & Discriminatory Harassment Policy (non sex or gender):
https://www.kenyon.edu/directories/offices-services/ocr/discrimination/
ADA & Section 504:
https://www.kenyon.edu/directories/offices-services/ocr/discrimination/504-ada-grievance/student-grievance-procedure-resolving-complaints-under-ada-section-504/
Tutoring (MSSC)
[Details to come with hours and location]