AUSTIN COMMUNITY COLLEGE

DEPARTMENT OF COMPUTER STUDIES AND ADVANCED TECHNOLOGY

Course Syllabus:  COSC 1336 (3-3-1) – Programming Fundamentals I

Section 25       Synonym 34668          ‘MW13’              Spring 2026

January 16 - May 12 (16 week session)

Lecture:          HLC 2412       Monday/Wednesday   1:30 pm – 2:50 pm (1:20)

Lab:                HLC 2411       open lab or ONL (online), DIL (distance learning)

Instructor:  Paul Thayer

Office:  online only, email to pthayer@austincc.edu any time, can get response at any time

Office Hours: Monday/Wednesday: 1:00 pm – 1:30 pm; 2:50 pm – 3:20 pm in class

                        (30 minutes before and 30 minutes after each class meeting)

E-mail:  pthayer@austincc.edu          Please put MW13: first in the email subject line!

Course Description:  Introduces the fundamental concepts of structured programming.  Topics include software development methodology, data types, control structures, functions, arrays, and the mechanics of running, testing, and debugging.  This course assumes computer literacy.

Pre-requisite:  This course requires the same math skills necessary for College Algebra.  Students should either have taken or be currently enrolled in College Algebra or a course that requires College Algebra.  TSI complete in reading.

Approved eText:

Starting out with Python, Sixth edition, Tony Gaddis, Pearson, 2023

ISBN-13: 978-0-13-792251-2 (eText provided on-line in Blackboard Ultra)
Instructional Method: 75% lecture and 25% lab time. This is a classroom course. We meet twice a week in a classroom at Highland Campus (HLC), building 2000, room 2412. Lab time is ONL (online), DIL (distance learning). HCL1 2411 is a nearby lab room with a tutor.

Course Rationale:  This is an entry level programming course designed to teach students the basic concepts of computer programming.  The course will include designing, coding, debugging, testing, and documenting programs using a high level programming language (Python).  This course is intended to prepare students for a programming-oriented academic path.  The course is included in several degree plans.

Communication:  Blackboard Ultra provides a Message feature, which allows communication with anyone in the class, including the instructor. This is the preferred way to communicate with the instructor. Be careful in selecting the recipient(s), so your message is sent to the desired person(s). Use Blackboard Message to communicate with the instructor when away from campus.

ACC email is another option, but less desirable, because of the very large number of emails that pile up and can get buried.  If you send an email to the instructor, please put Subject: MW13… in the email subject line. This helps your email to stand out and not get lost.

Course Objectives / Learning Outcomes:

1. Demonstrate problem solving skills by developing and implementing algorithms to solve problems.
2. Derive problem specifications from problem statements.
3. Develop algorithms using modular design principles to meet stated specifications.
4. Create code to provide a solution to problem statements ranging from simple to complex.
5. Test and debug programs and program modules to meet specifications and standards.
6. Create programs that contain clear and concise program documentation.
7. Implement programs that use data types and demonstrate an understanding of numbering systems.
8. Incorporate both basic and advanced control structures appropriately into algorithms.
9. Demonstrate an understanding of structured design by implementing programs with functions, including parameter passing and value returning.
10. Implement programs using classes, including strings and files.
11. Implement algorithms using one-dimensional and indexed data structures.
12. Demonstrate an understanding of array searching and sorting algorithms by desk-checking and/or modifying algorithm implementations.
13. Design and implement simple classes.

SCANS Competencies:

Refer to http://www.austincc.edu/cit/courses/scans.pdf for a complete definition and explanation of SCANS.  The following list summarizes the SCANS competencies addressed in this course:

Approved eText:

Starting out with Python, Sixth edition, Tony Gaddis, Pearson, 2023

ISBN-13: 978-0-13-792251-2 (eText provided on-line in Blackboard Ultra)

Grade Policy: Grades will be assigned based on concepts and practical application. Exams, quizzes, and labs will be a part of the grade. There is no curve. Your grade is based on your individually earned point total. Point totals are not “rounded up” to the next higher grade level. Extra credit opportunities are included. Final grades are based points awarded out of 1000 using this scale:

Graded work includes: quizzes (20%), labs (30%), exam1 (20%), exam2 (30%) as shown below:

Quizzes are on-line (Blackboard) T/F, multiple-choice, etc. tests. There are 2 attempts, highest score counts. They check the student’s reading and comprehension. Quizzes are open-book, open note. The student should complete the quiz without help from another person prior to the upcoming exam. The student may save a quiz attempt over multiple sessions, but it must be submitted for grading and credit.  Quizzes are due within two weeks of being assigned. Quizzes are inaccessible 4 weeks after being assigned.

Labs are usually python programming assignments. Labs are due 2 weeks after being assigned or before the upcoming exam. (Lab 10 has less than 2 weeks.) Labs are considered late if submitted after two weeks of the date assigned, but will be accepted with a 50% late penalty if submitted within four weeks of the date assigned. Four weeks after a lab is assigned, the lab will disappear from Blackboard and the student will not be able to submit that lab assignment.

Use the naming convention to name files submitted for grading. The student shall prepend the course designator (‘MW13’), underscore (‘_’), L# or H#, and lastname to the lab name. Example: Jordan Jones attends a Monday/Wednesday class starting at 1:30 pm. For lab 3, he submits the file: MW13_L3_Jones.py for grading. Files are submitted via the Blackboard assignment link.

To undo and redo a submission before grading, ask the instructor to clear the submission. In an emergency, if Blackboard is unavailable, use ACC email to send the .py file as an attachment. Labs are downloaded and executed as part of the grading process. If the lab is not named properly, it is difficult to identify, locate and grade after it is downloaded.

You should complete assignments prior to being tested on them in an exam. Each exam covers skills learned from the preceding quizzes and labs. The exam tests concepts from all prior labs. A common penalty for late work is that you lose points on the exam because you were not prepared.

Exams 1and 2 may consist of several parts. One part may be like a quiz, and can be completed outside of class time. A time-limited programming part will require in-class programming in python.

All parts are submitted on Blackboard. There are NO scheduled makeup exams in this course. If a student knows ahead of time that an exam cannot be taken on the assigned date and will be missed, arrangements must be made in advance with the instructor. Arrangements include: taking the exam early, taking the exam late. If an exam is missed during its originally scheduled period without prior arrangements with the instructor, points for that exam are forfeit. In an emergency situation, a student may request submitting a late exam after the exam is over and without prior notice. In this case, a late penalty will apply. Exams simulate a programming job interview scenario, where AI is not allowed.

Python lab and exam programs must be submitted on provided BlackBoard assignment links. Assignments submitted via email are not accepted! (Except in emergencies when BlackBoard is not available.) The instructor will clear a mistaken submission upon email request, so the lab may be resubmitted provided time has not expired.

The last date to submit assignments for a grade this semester is Friday, May 15, 2026 (last weekday of the semester, by 11:59 pm).

Academic Integrity

A student is expected to complete his or her own projects and tests.  Students are responsible for observing the policy on academic integrity as described in the current ACC Student Handbook.

Students may work together. At most two students may work together on the same lab. Each student’s program is expected to be uniquely coded, tested and submitted independently. If you collaborate on a lab with another student and your lab is similar to another student’s lab, both students who worked together must record who developed the code in the comment header. If substantially similar labs are submitted without a declaration of collaboration, the score for the labs may be reduced to zero on suspicion of cheating (submitting another student’s work as your own). The reduction to zero applies to both the sender and receiver of similar lab code.

For lab assignments, including exams, you may refer to course notes, the eText, previous lecture and lab notes, and online resources using instructor approved web links. We will be using artificial intelligence (AI) tools in this course on a per-assignment basis. Quizzes should be completed without AI – know your python! Lab assignment instructions will specify whether AI may be used or not; and how it may be used if allowed. During exams, you will not be allowed to use AI tools.

Incomplete: A student may receive a temporary grade of “I” (Incomplete) at the end of the semester only if ALL of the following conditions are satisfied:

1. The student is unable to complete the course during the semester due to unforeseen circumstances beyond their control.
2. The student must have earned at least half of the grade points (500) offered by the course by the end of the semester.
3. The request for the grade must be made in person at the instructor’s office and necessary documents completed.
4. To remove an “I”, the student must complete the course by two weeks before the end of the following semester.  Failure to do so will result in the grade automatically reverting to an “F”.

Attendance / Withdrawal

Regular participation is expected and observed via BlackBoard statistics. An attendance sheet will be provided each class and should be initialed to indicate class attendance. No points are awarded for attendance, but 1 point is deducted per absence. Points for absences are deducted from the student’s point total at the end of the semester. Up to 32 points (3.2%) may be deducted for absences.

Students will be held responsible for all assigned material. Regular weekly progress helps ensure satisfactorily course completion. Spring Break is Monday, March 16, 2026 to Friday, March 20, 2026 (college closed). See: http://www.austincc.edu/calendars/academic-calendar

It is the student’s responsibility to follow the Course Withdrawal/Drop Instructions if they wish to withdraw from this class. See: http://www.austincc.edu/online-services/course-drop-withdrawal. The last date to withdraw for this semester is Monday, April 27, 2026.  It is not the responsibility of the instructor to withdraw the students from their class even though the instructor has the prerogative to do so. Typically, the instructor does not withdraw students! If it appears, on the final withdraw date, that a student will surely receive an ‘F’ for the course, the instructor may withdraw a student.  Do not rely on the instructor to withdraw you from the course! If you do NOT wish to be withdrawn, despite low scores, advise the instructor before the final withdrawal date.

Students who enroll for the third or subsequent time in the same course may be charged a higher tuition rate.  State law permits students to withdraw from no more than six courses during their entire undergraduate career at Texas public colleges or universities.  With certain exceptions, all course withdrawals automatically count towards this limit.  Details regarding this policy can be found in the ACC College Catalog. See: http://www.austincc.edu/catalog/.