Fall 2026 – Kenyon College
Instructor: JAmes Skon
Meeting Time: MWF TIme: TBA
Location: TBA

Course Overview

This course introduces programming through a modern, AI-assisted workflow. Students will learn how to design, build, and evaluate software systems using Python and JavaScript, while leveraging AI as a structured development partner.
Prerequisites: None (some background is programming is recommended)

Rather than focusing only on writing code, this course emphasizes:

Problem decomposition and algorithm design
Writing effective prompts to generate and refine code
Critically evaluating AI-generated solutions
Incremental development and testing
Understanding—not outsourcing—computation

Students will work in a POGIL (Process-Oriented Guided Inquiry Learning) environment using coLearnAI, where they will collaboratively explore concepts and individually apply them.

Learning Objectives

By the end of this course, students will be able to:

Design algorithmic solutions to real problems
Write and refine prompts to guide AI code generation
Evaluate correctness, efficiency, and clarity of code
Implement programs in Python and JavaScript
Debug and improve both human- and AI-generated code
Understand core programming concepts:
- variables, control flow, functions, data structures, and objects
Develop confidence building working software systems

Course Philosophy: Programming in the Age of AI

AI is a powerful tool—but not a replacement for understanding.

In this course:

You will use AI extensively
You will not blindly trust AI
You will learn to think first, then prompt, then evaluate

Think of AI as:

A junior developer who is fast, confident, and often wrong.

Your job is to:

Ask the right questions
Guide the solution
Detect mistakes
Improve the result

Tools and Environment

We will use a browser-based development environment integrated into coLearnAI, so no installation is required.

Tools include:

Python runtime (in-browser)
JavaScript runtime (in-browser)
AI assistant (structured prompting interface)
POGIL collaborative system

Course Structure

Each week follows a consistent pattern:

Monday (Concept + Design)
Problem solving, modeling, algorithm design
Wednesday (AI + Implementation)
Prompting, code generation, debugging
Friday (Refinement + Reflection)
Testing, evaluation, extension

Assignments

1. POGIL Activities (15%)

Collaborative, in-class guided inquiry activities.

2. AI-Assisted Labs (35%)

Individual assignments where students:

Design a solution
Prompt AI to generate code
Refine and debug
Submit:
- final code
- prompt history
- reflection

3. Weekly Exercises (10%)

Short programming + prompting tasks.

4. Prompt Design Reflections (10%)

Short writeups analyzing:

what worked
what failed
how prompts improved

5. Midterm Project (10%)

Design + implement a small system using AI workflow.
This is completed as a small group.

6. Final Project (20%)

End-to-end system:

problem definition
data model
prompt strategy
implementation
evaluation

Grading

Category	Weight
POGIL Activities	15%
Labs	35%
Weekly Exercises	10%
Prompt Reflections	10%
Midterm Project	10%
Final Project	20%

Collaboration and AI Policy

Collaboration is encouraged in design and discussion
All submitted work must reflect your understanding
AI must be used transparently
You must include:
- prompts used
- explanation of decisions

You are graded on:

how you think, not what AI produces

Attendance

Attendance is essential due to collaborative work.

6 absences → course failure
Each absence impacts participation

📅 Course Schedule (14 Weeks)

Week 1 – Introduction to Programming with AI

What is programming now?
Human vs AI roles
First prompts and first program

Week 2 – Variables, Expressions, and Prompting Basics

Python basics
Writing precise prompts
Debugging AI misunderstandings

Week 3 – Input, Output, and Simple Algorithms

Data flow
Step-by-step reasoning
Prompting for structure

Week 4 – Conditionals and Decision Making

Boolean logic
AI mistakes in logic
Testing correctness

Week 5 – Loops and Iteration

While / for loops
Efficiency awareness
Infinite loop debugging

Week 6 – Functions and Abstraction

Function design
Prompting for modular code
Reusability

Week 7 – Strings and Lists

Data structures
Transformations
AI hallucination detection

Week 8 – Files and Data Processing

Reading/writing files
Structured data
Real-world datasets

Week 9 – Dictionaries and Data Modeling

Key-value thinking
Modeling problems
Designing representations

Week 10 – Introduction to JavaScript

Syntax differences
Same concepts, new language
Translating ideas

Week 11 – JavaScript Control Flow and Functions

Event-based thinking
Debugging across languages

Week 12 – Objects and Systems Thinking

Basic OOP concepts
Designing small systems

Week 13 – Integrated Project Work

Full workflow:
- design → prompt → build → test

Week 14 – Final Project and Reflection

Presentations
Reflection on AI + programming

Important Dates

Classes Begin: August 27
October Break: October 8–9
Thanksgiving Break: November 21–30
Last Day of Classes: December 11
Finals: December 14–18

Accessibility and Support

Students needing accommodations should contact SASS early in the semester.

Final Note

This course is about learning how to build with intelligence—both yours and the machine’s.

If you finish this course successfully, you will not just “know Python” or “know JavaScript.”

You will know:

how to create working software systems in a world where AI is always present.

Non-Discrimination, Civil Rights and Title IX Compliance

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. As a faculty member, I am deeply invested in the well-being of each student I teach. I am here to assist you with your work in this course. If you come to me with non-course-related concerns, I will do my best to help. However, it is important for you to know that all faculty, are considered Mandated Reporters of any incidents of harassment, discrimination, and intimate partner violence and stalking. Meaning, I must report any such discussion to the Civil Rights/Title IX coordinator. I cannot keep information involving sexual harassment, sexual misconduct, interpersonal violence, or any other form of harassment or discrimination based on a protected characteristic, confidential. The Health and Counseling Center, the College chaplains, and the staff at New Directions Domestic Abuse Shelter &
Rape Crisis Center are confidential resources.

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.

Tutoring (MSSC)

[Details to come with hours and location]