← Ayaan M. Kazerouni

CSC 313 Teaching Computing

Contents

Syllabus

Welcome!

Course description

An introduction to pedagogical methods and practical techniques for computing education: selecting appropriate content, designing assignments and activities, evaluating student learning, and evaluating teaching efficacy. Hands-on guided curricular design activities and real-world practice.

Course learning objectives

Assessments and grading

Details

Programming: To think about teaching computing, we will begin with reflections on our own coding process. This course includes programming assignments that involve process documentation and reflections. This process will include code review and shared assessment of one’s process and code.

Reading: I will assign course readings to help you engage with the material. Please complete these readings before class. Expect in-lecture reading quizzes in addition to turning in complete reading responses each week.

In-class discussions: We’ll have frequent small-group discussions during lecture and lab sessions. These will often be accompanied by Canvas submissions.

Attendance: See the attendance policy later in this Syllabus.

Teaching/tutoring: We will practice teaching computing via both shadowing experienced CS tutors and tutoring in the online tutoring for 101, 202 and 203 students. If time permits and we aren’t totally spent by week 10, you’ll also hold brief sessions for the intro classes.

Culminating experience: In consultation with the instructor, students will design and teach a computing workshop to interested students. I will provide a number of possible opportunities to which groups will be assigned based on student interests. If you (or your club, etc.) have an organised teaching activity you’d like to set up, that can also count. Please talk to me ASAP if this is the case.

The following workshops were taught in Winter 2025:

Click to see workshops taught in previous quarters.

Course communication

Please bookmark this Slack workspace, and also make sure to do at least one of the following:

All communication for this course will take place in the Slack channel linked above. Questions that are of general interest to the class should be sent to the #general channel. If you’re not comfortable asking questions publicly, you can DM me, and I might post the question and answer to the public channel if I think it would be helpful.

The Slack workspace also provides a convenient way for you to interact with your teammates.

Attendance policy

I will take roll in most class sessions. 5% of your course grade is based on attendance — this will be given as a binary score, i.e., either 0% or 5%. You must attend at least 85% of class sessions to get credit for attendance.

Additionally, there will be in-class discussions that cannot be completed outside of class.

Here is why I have instituted this attendance policy:

All this adds up to: I strongly recommend that you come to class!

In case of emergencies, don’t worry about attendance, and talk to me when you are able to do so.

Accessibility

I know that everyone is unique, and I may have unintentionally overlooked something that limits access to some materials or activities. Please let me know if you cannot access any content. If you need additional accommodations to complete the required course work, please contact me as soon as possible! You should also contact the Disability Resource Center.

SensusAccess is a self-service, alternate media solution made available by Kennedy Library to automatically convert files into a range of alternative media including audiobooks (MP3 and DAISY), e-books (EPUB, EPUB3, and Mobi) and digital Braille. The service can also be used to convert inaccessible files such as image-only PDF files, JPG pictures, and Microsoft PowerPoint presentations into more accessible and less tricky formats. This service is available at no charge.

Classroom climate

All members of this class are expected to contribute to a respectful, welcoming, and inclusive environment. I expect us to strive to build a community in which:

Course schedule

This is the schedule used in Winter 2025. This schedule shows the “big assignments” and doesn’t include the quizzes or discussion activities.

WEEK TOPIC READING NOTES/SLIDES ASSIGNMENT DUE/RELEASED
1 Course intro + computing for all Good (and Bad) Reasons to Teach All Students Computer Science (Lewis) Slides Survey about workshop topic interests
1 How people learn How Can I Teach Students the Skills They Need When Standardized Tests Require Only Facts? (Willingham)
Decoding Your Confusion While Coding (Hermans)
Slides Tutoring centre shadowing sign-up and reflection released
The programming process assignment released
2 Mental models, notional machines, and misconceptions Getting better at solving programming problems (Hermans) Slides  
2 Learning to program The Buggy Path to the Development of Programming Expertise (Pea, Soloway & Spohrer) Slides Programming process reflection due

Workshop initial proposal
Educational data mining assignment released
3   NO CLASS. ACADEMIC HOLIDAY.    
3 Programming language syntax, behaviour, and environments
Pedagogic programming languages
What is a Pedagogic IDE? (Krishnamurthi)
Programming paradigms and beyond (Krishnamurthi and Fisler)
Hedy: A Gradual Language for Programming Education (Hermans). Also, try the Hedy language
The Pyret programming language. Why Pyret? and Examples
Slides  
4 Tutoring What’s known about tutoring (Orendorff) Slides Tutoring centre shadowing reflection due
4 Learning a 2nd PL Understanding Conceptual Transfer for Students Learning New Programming Languages
📽️ Talk recording (Tshukudu & Cutts)
Notes  
5   EDUCATIONAL DATA MINING REPORT PRESENTATIONS   Educational data mining reports due
5 Instructional design Chapters from Teaching Tech Together (Wilson) Slides Workshop proposal presentations begin
6 Classroom instruction
Mastery learning
Teacher perspectives
The 2 Sigma Problem: The search for methods of group instruction as effective as one-on-one tutoring (Bloom) Slides  
6   NO CLASS. CLASS CANCELLED DUE TO WEATHER.    
7 Classroom climate A Climate-first approach to training student-teaching assistants (Huang and Fox)
Communication in computer science classrooms: understanding defensive climates as a means of creating supportive behaviors (Garvin-Doxas and Barker)
Slides  
7 Diversity barriers Diversity barriers to K–12 computer science education: structural and social (Wang & Moghadam)
An Equity-minded Assessment of Belonging among Computing Students at Cal Poly (Stewart)
Slides Mind-mapping activity
8 AI-based code synthesisers in computing pedagogy Exploring the Design Space of Cognitive Engagement Techniques with AI-Generated Code for Enhanced Learning (Kazemitabar, Huang, Suh, Henley, Grossman)
Learning to code with and without AI (a blog post by Austin Henley, summarising a couple of research papers)
Slides AI in computing education reading and reflection due before class
8 Metacognitive scaffolding   Notes
These notes were written pre-LLMs, but the skills involved are still worth discussing.
 
9 Spatial skills Investigating the Relationship Between Spatial Skills and Computer Science (Parkinson & Cutts)
Spatial Encoding Strategy Theory: The Relationship Between Spatial Skill and STEM Achievement (Margulieux)
Notes  
9 Open discussion about degree programs, our degree programs, and our upcoming transition to the semester system.      
10 Spoken languages and programming languages Native Language’s Effect on Java Compiler Errors (Reestman & Dorn)
Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages (Prat, Madhyashtha, Mottarella, & Kuo)
Slides  
10   NO CLASS. ALL THE BEST FOR FINALS.    

Acknowledgement

Early versions of this course were based on Zoë Wood’s initial offering of the course.


  1. We didn’t go a good job advertising this with enough time, so these were not well attended.