INFO 1300: Introductory Design and Programming for the Web Syllabus (Fall 2026)
Credits: 4, Letter Grade
Prerequisites: None
Expected Weekly Workload: 8 hours/week outside class
Instructor: Dr. Kyle Harms (he/him); https://kharms.infosci.cornell.edu
Course Website: https://infosci.cornell.edu/courses/info1300/2026fa/
Course Email: info1300@cornell.edu
Send all private communication to the course email. I strive to respond to each email within 2 business days (Monday-Friday, excluding holidays and breaks), during business hours (Monday-Friday, 9am-4pm).
Lectures: Mondays, Wednesdays, 1:25pm-2:40pm, Olin Hall 255
Friday Sections: Fridays, 50 minutes. See the class roster for details.
Office Hours: calendar
Required Materials: Pen or pencil, paper, a functioning laptop, an active github.com account, and a GitHub Copilot Pro subscription ($10/month + additional credits).
Textbooks: None
This course requires GitHub Copilot Pro, with the costs paid directly by the student, estimated at ~$40/semester. (Free GitHub Copilot Pro accounts are available through GitHub Education for verified students.) Note that AI pricing is difficult to accurately estimate and can change with little notice. Contact info1300@cornell.edu if this cost presents a hardship for you.
Course Description
This course is designed to introduce students to the conceptual, design, and technical aspects of developing static, accessible front-end websites. No prior knowledge of programming or web design is assumed nor necessary. In the course, we will cover basic web technologies such as HyperText Markup Language (HTML), Cascading StyleSheets (CSS), and some JavaScript (JS). Design and development best practices are emphasized, including effective usage of AI coding assistants.
We will also introduce students to theories and principles that will help you become a better UX designer. This includes information, visual, and interaction design principles; usability and user testing principles and processes.
This class is about design and programming; not just programming. Design and user experience are significant components of this course. Please note this class assumes you have little prior programming experience; this course is likely not appropriate for most CS majors.
Course Objectives
By the end of the course, a student will be able to:
- Develop accessible client-side/front-end static websites using HTML, CSS, and JavaScript.
- Structure content with HTML, style it with CSS, and add client-side interactivity with JavaScript.
- Plan and implement complex layouts using CSS Flexbox and CSS Grid.
- Apply user-centered design methods to create websites for specific audiences.
- Design and implement usable, responsive websites for narrow and wide screen devices.
- Organize content and navigation using information architecture principles.
- Design usable websites leveraging the visual design principles of color, contrast, typography, proximity, alignment, hierarchy, repetition and consistency.
- Orally communicate and defend design and coding decisions to project stakeholders.
- Gain experience with developer best practices: utilizing reference documentation, version control using Git, and authoring documentation using Markdown.
- Troubleshoot programming problems independently.
- Utilize generative AI tools effectively as a coding partner through prompt engineering and critical evaluation to assist in development.
- Demonstrate a high standard of professionalism.
Course Structure & Assignments
To create the best learning environment for you, this class provides a lot of opportunities for practice with rapid feedback. However, the fast pace means that it's easy to fall behind. The course structure and policies are designed to help you stay on track and to help you succeed.
There are weekly class preparation exercises, 8 homework assignments, a project (four milestones) with an oral defense, 6 practice quizzes, and 3 exams, including a cumulative final exam.
- Every week you will be expected to complete a homework assignment or submit a project milestone.
- Every week during your registered Friday section you complete a practice quiz.
- 2 exams are held during the regular scheduled lecture time. The final exam is scheduled by the University registrar.
Grades
Grades are earned, not given. Your grade is a reflection of your mastery of the course content and your ability to apply that knowledge to the assignments. Your grade is not a reflection of your effort, your potential, or your worth as a person. This course does not offer extra credit.
Your grades are posted to Canvas. The grade you see in Canvas is your current grade.
Assignment/Exam Grading
Some assignments, like projects and exams, are graded for correctness. When assignments are graded for correctness, your grade is based on how well your submission demonstrates your mastery of the course learning objectives. Because grading is based on demonstrated mastery of the learning objectives, partial credit is awarded only as half credit.
Some assignments, like class preparation and homeworks, are graded for completion. You must demonstrate that you attempted all parts of the assignment, and you put forth a good faith effort to complete the assignment for full credit. No partial credit is provided for completion-graded assignments.
Practice quizzes are graded 50% for completion and 50% for correctness.
Final Grade Calculation
Your grade is computed using the following weighted averages:
| Component | Weight |
|---|---|
| Attendance | 0%† |
| Class Prep + Homeworks | 10% |
| Practice Quizzes | 10%‡ |
| Project + Oral Defense | 20% |
| Exam 1 | 20% |
| Exam 2 | 20% |
| Final Exam | 20% |
† If you arrive to class before it starts and attend at least 86% of all lectures, your final course percentage will be rounded up to the next whole number; you may miss 4 lectures without penalty.
‡ Lowest practice quiz score is dropped when calculating your final grade.
Letter Grades
Grades are never rounded. Like your GPA, letter grades are assigned by the integer-part of your final percentage. For example: 96.01, 96.5, and 96.99 are all A's. 97.0 is an A+.
| Letter | Percent | Letter | Percent | Letter | Percent | Letter | Percent |
|---|---|---|---|---|---|---|---|
| A+ | 97-100% | B+ | 87-89% | C+ | 77-79% | D+ | 67-69% |
| A | 93-96% | B | 84-86% | C | 74-76% | D | 64-66% |
| A- | 90-92% | B- | 80-83% | C- | 70-73% | D- | 61-63% |
| F | 0-60% |
70% and above is a passing grade (S). Below 70% is an unsatisfactory grade (U).
Course Policy Summary
By being here, you have earned the right to be held to a high standard of professionalism.
The course policies are summarized below. For additional details about each policy, see the respective policies.
Contact the Instructor:
- Email info1300@cornell.edu using your Cornell email to privately contact the instructor.
- I strive to respond to each email within 2 business days (Monday-Friday, excluding holidays and breaks), during business hours (Monday-Friday, 9am-4pm).
- Only the instructor, course administrator, and select PhD teaching assistants have access to the course email; undergraduate course assistants will never see your messages.
- I do not respond to Canvas messages. Send all course-related communication to the course email.
Inclusivity & Accommodations:
- Everyone belongs in this class. Let me know if you have any concerns.
- Email the course for accommodations. The sooner, the better (per university policy, accommodations are not applied retroactively.)
- All students are provided with built-in accommodations: 4 automatically excused absences, 3 slip days, and 1 assignment resubmission.
- The provided accommodations are specifically intended to support most student accommodation needs and should only be used for legitimate reasons for needing an accommodation.
Lecture:
- As per university policy, lecture attendance is required.
- Take your own notes during class. You are responsible for all information presented in lecture, including information not available elsewhere, such as in the slides, course website, Canvas, etc.
- It is your responsibility to complete the in-class activity handout and physically submit it before leaving the classroom to be counted as present for that class.
- If you arrive after the start of lecture (class starts exactly at 1:25:00pm), but within 10 minutes of the start time (1:35:00pm), you will be counted as half present for that class.
- If you arrive more than 10 minutes after the start of lecture (after 1:35:00pm) or you leave before lecture is dismissed, you will be counted as absent for that class.
- Catch up with a peer if you miss lecture.
- You may not record or take photographs during class without the explicit permission of the instructor.
Assignments & Late Work:
- Professionalism necessitates that you plan ahead for technical issues and begin assignments early so that you have time to seek assistance if needed.
- Handwritten work should be legible; no credit is provided for illegible work.
- It is your responsibility to ensure that your submissions are complete, valid, and ready to be graded; no leniency is provided for submitting broken or incomplete work, including submitting the wrong file.
- Assignments are due when stated regardless of whether you encounter technical difficulties.
- Late work receives 0 credit without an accommodation. (Reminder: accommodations are not retroactive and must be coordinated in advance.)
- You have 3 slip day accommodations to use for the entire semester. You may submit any non-group work assignment (homework or project milestone only) 24 hours late using a slip day.
- You may not combine late submission / deadline extension accommodations.
- If you submit an assignment late, you should not expect timely feedback or grading of your submission; your grade may be delayed for around 2 weeks.
[Submission Policy] [Late Work Policy] [Accommodations Policy]
Exams:
- Exams are closed-book and closed-notes.
- Because exam dates are known in advance, all students are expected to take the exams at the scheduled times unless they have an accommodation and have made arrangements well in advance of the quiz/exam date (minimum 7 days).
- All exam accommodation logistics are handled by SDS Alternative Testing Program.
Grades:
- All submitted work is assessed for your mastery of the course learning objectives; grades are not based on effort.
- All assignments are graded exactly once; once your assignment is graded, the grade is final (unless there is a grading mistake).
- You may resubmit up to one non-group work assignment (homework or project milestone) for a new grade using the provided resubmission accommodation one week after your grade was returned to you.
- In the interest of fairness to all students, the instructor and course/teaching assistants cannot pre-grade your work or tell you if your work is correct.
- Submit a grade clarification request if you don't understand your grade on an assignment.
- Submit a regrade request if there is a mistake with your grade on an assignment. You have one week to submit a regrade request from the date that your assignment's grade was returned to you.
Getting Help & Collaboration:
- Only the instructor may clarify assignment instructions/requirements or course content.
- The best place to get help with an assignment is from your peers and office hours.
- When getting help, keep in mind that we prioritize helping you learn. We cannot fix nor debug your code for you.
- You are encouraged to collaborate/work with your peers in this class so long as you do your own work. You may not share or copy code/solutions.
- Course/teaching assistants do not have the authority to endorse solutions, provide clarifications, regrade your assignment, or debug AI generated code.
- We answer questions on the course discussion forum exactly twice a day, once before noon and again before 4pm, Monday-Friday.
Citations:
- Cite all content (text, images, videos, etc.) in your submissions.
- Cite all resources you referenced to complete your work.
Generative AI:
- GenAI use is permitted, but you may not upload copyrighted or proprietary class materials (slides, readings, recordings, lecture notes, etc.) unless otherwise specified.
Academic Integrity:
- Submit your own work. Do not copy from anywhere, including the course provided code. (Copy does not simply mean "copy and paste". You can also produce a copy by typing out a nearly identical code snippet, etc.)
- You are encouraged to use additional resources, like tutorials. Though you may use them as reference material only: study the resource so that you understand it and can use the same ideas in your project/code independently.
- If found guilty of violating the Code of Academic Integrity, the minimum penalty is a 0 for the offending assignment. The maximum penalty is failing the course.
- All course materials are copyrighted. Do not share course materials outside this class, including sharing the materials with generative AI.