Computer Science

Fall 2024 | Instructor Page | HCC

Course Homepage

Syllabus

Please note: this syllabus may be updated based on the needs of the class and at the discretion of the instructor (the same is true for other course materials).

Course Description

This course introduces students to the fundamental concepts of computer science, including an overview of how computers work. Students will learn about the hardware components of computers, operating systems, and the internet.

Students will also learn the basics of computer programming using the Python language. Students will learn about control flow, variables, data types, functions, and problem solving. While some skills will be Python-specific, high-level concepts will be language agnostic.

Course Objectives

By the end of the course, students will have learned:

Students will build projects throughout the semester to apply their knowledge. The project subject and scope will vary depending on students’ interests. Early projects may include:

Course Structure

This course is a hybrid which has both in-person and online class times.

The first class period (Thursday, September 12th) will be in-person. The following week we will meet at 8:00am online (video platform to be determined). This pattern is repeated throughout the semester, where every other week is in-person.

Virtual Classes

Required Materials

Students will need access to a computer with internet access in order to access course materials, complete online quizzes, and work on programming assignments. For in-person class time, Chromebooks will be available for students to use (but students can bring their own computer if they have one).

Students (or their parent) are required to sign up for a free account for the online development environment Replit.

No textbooks are required; free digital course materials will be provided throughout the semester.

Grading Policy

Letter Grades

Letter grades will be awarded according to the following scale:

LetterGrade
A93%-100%
A-90%-92%
B+88%-89%
B83%-87%
B-80%-82%
C+78%-79%
C73%-77%
C-70%-72%
D+68%-69%
D63%-67%
D-60%-62%
F< 60%

Grading Rubric

Student work will be evaluated on the following criteria:

CategoryPercentage
Participation20%
Projects30%
Quizzes30%
Exams20%

Participation

Student participation will be evaluated on the following criteria:

CategoryPercentage
Interaction (see classroom expectations)30%
Attendance30%
Communication40%

Projects

Student projects will be evaluated on the following criteria:

CategoryPercentage
Functionality60%
Subjective Elegance40%
Timeliness(see below)
Project Late Penalties

Late projects will be penalized by subtracting 10% of the graded points for each day that has elapsed since the deadline.

Example Grading for Late Assignment
  60% (passes required functionality)
+ 35% (formatted well but solution is not idiomatic)
= 95% (base score)

- 20% (2 days late) = 76% (final score)

Quizzes

There will be online quizzes every week that evaluate non-cumulative knowledge retention.

Quiz Late Penalties

Quizes are subject to the same late penalties as projects.

Corrections

Students may re-submit a corrected quiz up to 1 week after its initial due date.

Since quiz corrections were not available until week 5, there will be a grace period through week 6.

You may submit corrections for quizzes week 2-5 through 10/16. After that, the normal corrections rules apply (can only submit up to 1 week after due date).

Corrected questions are worth 50% of their original score.

Questions that were correct on the first attempt will retain their full score, regardless of whether they were answered incorrectly on the second attempt.

Example Grading for Quiz Corrections
   80%  (first attempt)
  100%  (corrected quiz)

100% - 80% = 20% (score improvement)
20% * 50% = 10% (corrections adjustment)
80% (first attempt) + 10% (additional score) = 90% (final assignment score)

Exams

There will be two in-person exams: one midterm and one final. Exams will evaluate cumulative knowledge retention.

Expectations

Behavior

Students are expected to exemplify the following characteristics:

Similarly, I will do my best to be respectful, attentive, and encouraging.

Students are encouraged to take ownership of their own experience in this class. In addition to completing assignments, students should proactively reach out for help when necessary and inquire about ways to expand projects beyond the minimum requirements. While this is an accredited course, students will get out of the class what they put in.

Artificial Intelligence

Artificial intelligence (AI) should not be used in this class unless explicitly stated otherwise.

Using AI to assist with quiz quesions, write code, or otherwise behave disingenuously is subject to disciplinary action.

Not only is it plagiaristic but it is detrimental to the learning process.

There is a time and a place for AI, but that time and place is not this class.