CS 108 - Introduction to Computing
Fall 2024
Calvin University

Rocky K. C. Chang

September 1, 2024

A welcoming message

Welcome to CS108! This is the first CS course for those CS students who do not have much background in Computing. Even though you may have learned some programming language before, this course will help you further develop your computational thinking skills. This course is also required/recommended for other non-CS majors. So you will find students from various disciplines and different stages of study.

Underpinning our endeavor of learning problem-solving skills is the Christian Reformed perspective. Learning this subject (and other subjects) is not a way of meeting our needs or securing our future. As instructed from the book of Genesis, we are called to work (learning is a form of work) and to reflect God’s glory in what we do. It is therefore important to keep this mindset as we strive to improve our problem-solving and programming skills in this course.

Instructors

Lectures and labs

We will meet in a classroom for the lectures and in the gold lab for the labs. There are two sessions (A and B) for this course. Please attend only your own sessions unless you get my prior permission.

  1. Lectures:

  2. Labs:

Communications

Course objectives

This course introduces computing as 1) a way of solving problems using the Python programming language for implementation and 2) a way of living out our Christian faith in technology-dominated societies. Students who complete this course will demonstrate that they can:

  1. (L1) Use an Integrated Development Environment (IDE), such as Thonny, to write and debug programs;

  2. (L1) Explain how the basic Python constructs below work.

    1. Python built-in data types (numbers, strings, boolean, lists, tuples, dictionaries, and sets)

    2. Control structures (if, else),

    3. Iterations (for loop and while loop),

    4. User-defined functions,

    5. Python classes and objects,

    6. String processing and text files,

    7. Built-in modules (e.g., the math module) and imported modules,

    8. Guizero for graphical user interfaces (GUIs), and

    9. Python’s exception handling;

  3. (L2) Document code using best practices and document functions and modules using Python’s docstings;

  4. (L2) Improve code readability through naming, structure, and others;

  5. (L2) Debug programs by inserting debugging code or using debuggers;

  6. (L2) Design test cases to validate the correctness of a program;

  7. (L2) Identify the data present in a problem to be solved;

  8. (L2) Identify the key tasks required to solve a problem;

  9. (L2) Implement the data in the problem using Python’s built-in data types and/or user-defined data types;

  10. (L2) Design and implement a Python function to perform a task;

  11. (L2) Design and implement one or more classes for a problem;

  12. (L2) Design and implement a correct algorithm to solve a problem;

  13. (L3) Compare different algorithms for solving a problem from the perspectives of time complexity and space complexity;

  14. (L3) Articulate the limitations of computing (non-computability, intractability, precision, etc);

  15. (L4) Propose, design and implement a feasible and useful class project using what is learned inside and outside classes; and

  16. (L4) Articulate how learning this subject is part of your faith journey.

We classify these student learning outcomes (SLOs) into four levels (L1 - L4) which are adapted from the Bloom’s Taxonomy. In our model:

  1. (Concepts and skills) L1 corresponds to the Bloom’s levels on “understand and remember”. You will spend most of your time on accumulating enough programming concepts and skills on this level using the Python programming language.

  2. (Problem solving) The next layer L2 corresponds to the “apply and analyze” levels in the Bloom’s taxonomy. An important focus of L2 is to identify the data in the problem to be solved and the tasks required to solve it. Another equally important one is to implement these data and tasks using what is learned in L1. Code documentation and code readability are also part of this layer.

  3. (Evaluation) L3 corresponds to the “evaluate” layer in Bloom’s taxonomy. This includes comparing different algorithms of solving a problem and understanding the limitations of computing.

  4. (New creation) The highest level L4 is to create a new app to address an important problem and to understand how the learning of this subject is part of your spiritual formation.

Pre-requisites for this course

CS 108 does not assume that you have any programming experience, but it does assume a background in basic mathematics. Contact Rocky if you have any questions about your preparedness for this course. On the other hand, if you think you have already learned most of the materials in this course and would like to skip it, please also contact Rocky.

Teaching approaches

To achieve the SLOs in the Course Objectives section, we will employ various in-class and outside-class activities, which include:

  1. POGIL (Process Oriented Guided Inquiry Learning) — L1 + L2

  2. zyBooks reading — L1 + L2

  3. In-class quizzes — L1 + L2

  4. Code reviews — L1 + L2

  5. In-class exercises and problem sets — L1 + L2 + L3

  6. Weekly lab — L1 + L2 + L3

  7. Programming homework — L1 + L2 + L3

  8. Midterm project — L1 + L2 + L3

  9. Weekly devotion — L4

  10. Perspectival homework — L4

  11. Lectures — L1 + L2 + L3 + L4

  12. Final project — L1 + L2 + L3 + L4

POGIL is a student-centered, group-learning instructional strategy and philosophy which is proven to be effective over traditional teaching approaches. Together with the zyBooks reading assignments, you will be able to attain some basic knowledge and skills required in the SLOs under L1 and L2 through self- and group-learning. Based on this foundation, other activities, such as quizzes and lectures, are needed to achieve the SLOs in L1 and L2.

The SLOs in L3, on the other hand, can be achieved by learn-by-practising (e.g., in lab and homework) and expositions through interactive lectures and in-class exercises. The midterm project is designed to have you apply what you have learned in the first 8 weeks to solve a “small” problem. The final project goes a step further into the L4 SLO on creating a new app. As for the spiritual formation SLO, it will be achieved through weekly devotions, lectures, and perspectival homework.

The weekly rhythm and tasks

Each week is devoted to one (and occasionally two) topic in the syllabus. In a full week (i.e., with no missing class),

Weekly tasks and projects

  1. ZyBook reading assignments: Due at 9:00 on the first class day of the week (usually Mon)

  2. Homework: Due on Tue at 23:59 (have 10 days to finish it)

  3. Perspectival assignments: Due on Wed at 23:59

  4. Lab: Due on the next day (i.e., Fri) at 23:59

  5. Quizzes: Given on the first day of the week

  6. Midterm project: Due on Nov 5 (Tue) at 23:59

  7. Final project:

Table 1 show a tentative teaching schedule.

A tentative teaching schedule. There will be a devotion at the beginning of the first class every week. Not included are the deadlines for other assessments.
Week Topic Mon Wed Thu Fri Remarks
1 Introduction - Lecture Lab 1 Lecture
2 Variables and expressions POGIL, quiz Lecture Lab 2 Code rev and refl
3 Data types POGIL, quiz Lecture Lab 3 Code rev and refl Rocky will be in a conf. on Fri
4 Decision structures POGIL, quiz Lecture Lab 4 Code rev and refl
5 Iterations POGIL, quiz Lecture Lab 5 Code rev and refl
6 Functions POGIL, quiz Lecture Lab 6 Code rev and refl
7 Classes and objects POGIL, quiz Lecture Lab 7 Fall break
8 - Fall break Advising Lab 8 Code rev and refl
9 List, dictionary and set POGIL, quiz Lecture Lab 9 Code rev and refl
10 Strings and files POGIL, quiz Lecture Lab 10 Code rev and refl Midterm proj due
11 GUI and modules POGIL, quiz Lecture Lab 11 Code rev and refl
12 Exception handling POGIL, quiz Lecture Lab 12 Code rev and refl
13 - POGIL, quiz Thanksgiving Thanksgiving Thanksgiving
14 TBD TBD, quiz Lecture Proj consul TBD
15 TBD TBD Lecture Proj consul Study day Final proj’s code and report due
16 Project showcase

Assessments

Assessment components

CS 108 (3 credits)

  1. 5% — Preparation assignments (zyBook reading)

  2. 20% — Programming homework assignments

  3. 15% — Quizzes (cannot be made up without legitimate reasons)

  4. 15% — Perspectival assignments

  5. 20% — Midterm Project

  6. 25% — Final Project

CS 108L (1 credit)

  1. 100% — Lab (pair programming)

  2. Lab attendance is required. Failure of attending a lab without legitimate reasons will receive 0 marks.

Note that there is no final exam. Instead, we will have a project showcase during the time allotted by the registrar for the final exam. The date and time corresponding to your section will be different from the normal weekly meeting times.

Grade computation

  1. zyBook reading: Each reading assignment carries the same weight, regardless of the actual marks given by zyBook’s auto-grading.

  2. Programming homework: The full mark for each assignment is usually 40 marks.

  3. Quizzes: The full mark for each quiz is usually 20 marks.

  4. Perspectival assignments: The marking for each question is based on a 4-point scale (0 to 4).

  5. Lab: The full mark for each lab is generally different. The final mark is the sum of them.

  6. Midterm project: The marking for each criterion is based on a 4-point scale.

  7. Final project: The marking for each criterion is based on a 4-point scale.

  8. The marks obtained from a 4-point scale will be converted to the marks in the 100-point scale using linear interpolation.

The mark-to-grade mapping for determining the final grade is given in Table 2. Note that this is different from the one in the Moodle system.

The mark-to-grade conversion table for the final grade.
Highest mark Lowest mark Grades
100 90 A
89.99 85 A-
84.99 80 B+
79.99 75 B
74.99 70 B-
69.99 65 C+
64.99 57 C
56.99 50 C-
49.99 46 D+
45.99 39 D
38.99 30 D-
29.99 0 F

Other important notes

  1. Lab — pair programming

  2. For other assessments, you must work on your own.

  3. Your grades will be available in the Moodle gradebook, generally before the next assignment of a similar type is due.

  4. Incompletes

  5. Late work

Textbook and other resources

Throughout the class, we’ll use the following platforms and tools:

  1. edstem — for posting and answering questions on labs, homework and other relevant topics

  2. Moodle — Teaching plan, slides, perspectival assignments and projects

  3. zyBooks — Reading, lab and homework assignments.

  4. Activities for CS1 in Python, T. Shepherd, C. Mayfield and H. Hu, Creative Commons

  5. Thonny 4.1.4 (Python 3.10.11)

The lab

The SB 354 lab is pre-configured to support this course, so if you are on campus, you are free to do all your course work there. If you are off campus, you have two options: configuring your own machine and accessing the lab machines remotely. We suggest that you install the software on your own machine and then use the option you find most convenient.

Configuring your own machine

If you would like to configure your own machine, you can configure the following tools.

Accessing the lab machines remotely

There are a limited number of remote and virtual machines available for CS courses. You can find:

The course software for CS 108 is installed on both the Linux and the Windows remotes.

Values and policies

Accommodation policy

Calvin University is committed to providing access to all students. If you are a student with a documented disability, please notify a disability coordinator in the Center for Student Success (located in Spoelhof College Center 360) to discuss necessary accommodations. If you have an accommodation memo, please come talk to Rocky in the first two weeks of class.

Academic integrity in computing

Code re-use can be a valuable practice in computing, but mindlessly copying code is not an effective way to learn programming and reusing code or algorithms without attribution is plagiarism. If you’ve copied code with attribution, we’ll grade you on the code you wrote not on the code you copied. If we detect copying without attribution, i.e., plagiarism, we’ll be forced to give you a failing grade for the assignment and perhaps for the course. Additionally, we will report you to the office of Judicial Affairs, which may result in the incident being part of your student record.

Calvin’s general statement on academic integrity

The student-faculty relationship is based on trust and mutual respect, which can be seriously undermined by the suspicion or reality of academic dishonesty. Academic Dishonesty includes, but is not limited to, plagiarism (students plagiarize when they do not credit the sources of their writing - the words, information, ideas, or opinions of others), improper group work, reuse of a paper from another course and/or cheating on a test. Students are encouraged to speak to their faculty member with specific questions related to academic dishonesty. For further clarification or information, please visit this link.

Responsible use of technology

We expect you to abide by the guidelines expressed in the policies given in your institution’s technology policy (for students on campus, see Calvin’s Technology Policy Documents).

Diversity and inclusion

It is our intent that students from all backgrounds and perspectives are well served in this course. God delights in diversity; so will we in this course. If you or someone else is hurt by anything said or done in class, let us know so we can work toward a remedy.

Etiquette

We expect you to treat students and instructors for this course with respect by adopting courteous communication practices throughout the semester in all venues, including online forums. No personal attacks, trolling, or other kinds of bad language will be tolerated.