This is under construction, but I wanted to post a couple of my materials from MAT135 Differential Calculus.Continue reading University Calculus Materials
This term I’m auditing CSC311 Introduction to Machine Learning. I’ve tried learning this topic before, but it wasn’t at the right level for me. This time I’m optimistic because my colleague Sonya Allin is teaching the course, and I feel comfortable bombarding her with naive questions.
As I was sitting in the first class, I had my mathematician hat on and I noticed some things. I’m not saying these are deep, or unknown things, but they were interesting to me. Maybe they’ll be interesting to you too!
Observation 1: When we turn a picture into a vector we seem to lose a lot of geometric data
A standard way of storing a (greyscale) picture as data is to first write it as a matrix of data (an nxn table) where the entries are intensities (on a scale of 0-255). Then it cuts chopped up and reconstituted into a vector.Continue reading Machine Learning Observations 1 – Turning a picture into a vector doesn’t lose information!
“O God, I could be bound in a nutshell, and count myself a king of infinite space – were it not that I have bad dreams.”Hamlet, Act 2, Scene 2. Lines 252-254.
Recently, a colleague asked me:
I know that there are different sizes of infinity, but what I want to know is how many different sizes of infinity there are?-Curious Colleague
This is a great question! I tried to explain my answer at the time, but it came out garbled and I think I confused him more than I helped. So this post is an effort to remedy that and answer his question.Continue reading How many sizes of infinity are there?
Note: This was originally made as an announcement to my MAT224 class, but I am making it public so that colleagues can adapt this announcement for their own classes.
Continue reading Thursday September 30 – National Day for Truth and Reconciliation
My brief, unfair summary
At its best, the book Ungrading (Blum, 2020) and its authors
- Provide many blueprints, implementations, and reflections on ungrading practices.
- Address many practical difficulties of implementing these practices.
- Repeatedly make calls for revolution, and provide tools and recipes for making that happen.
- Encourage critical pedagogy.
- Come from a variety of disciplines and settings (K-12 vs post-secondary).
At its worst, the book and its authors
- Rely on unjustified assumptions and emotional arguments.
- Tend to hide or downplay the (serious) concerns related to ungrading.
- Never grapple with the critical scholarship or discuss the case of University of California, Santa Cruz that was gradeless for its first 35 years and then moved to traditional grading in 2000.
- Implement grading disguised as ungrading.
This term I’m teaching (and coordinating) a 1200 person Integral Calculus course at UTM. Term Test 1 went surprisingly well for students, and Term Test 2 was an unqualified success (very high average, lots of people got 100% on the test).
This lead to the following (paraphrased) question on our course message board:
Is the exam going to be a lot more difficult because the averages on the term tests were so high?
I took the time to think about exactly why I don’t like adjusting the difficulty of exams based on students doing well previously. Here’s the answer I posted on our message board.Continue reading Aligned teaching and punishing student success
Every summer, Canadian undergraduate students in mathematics meet at the Canadian Undergraduate Mathematics Conference (CUMC). Hundreds of students attend, and it gives them a chance to meet other people excited by mathematics. Students are also encouraged to give a short presentation on a math topic that interests them.
In the summer of 2018, while I was a Post Doc at the University of Calgary, we hosted a “mini pre-CUMC conference” for undergrads to give their presentations ahead of time. It was so successful that I ran an expanded version of this at the University of Toronto for CUMC 2019.
I think these events and workshops are important for all students, but in particular it helps break down barriers to entry for marginalized students. With that in mind, I’m sharing my resources, thoughts and experiences about our pre-CUMC conference with the hope that other universities and colleges in Canada will benefit.
I made a resource for teaching people how to use Jupyter notebooks. Really it’s about learning LaTeX anywhere, but Jupyter notebooks are very well suited to this.
In November 2018, 41 of the top researchers in Ramsey theory met at the BIRS in Banff for the Unifying Themes in Ramsey Theory conference. By all measures the conference was a big success. What makes Ramsey theory so special is that it has wide ranging impacts in diverse fields in mathematics. The participants gave talks showing how Ramsey theory has impacted fields like graph theory, topological dynamics, set theory, model theory, operator algebras, logic and statistics.
Since I have a somewhat broad base of knowledge in Ramsey theory, I tried my best to give a short description of each of the speakers in language that makes sense to me. My view is biased, and my intent is always to show off the amazing work everyone is doing. I hope nothing comes across as negative or critical; that is not my intent.