#UNI03: The first class: appreciation, ranting, and algorithms

That first day of class! Always so intriguing, full of expectancy (the killer of all joys?) and sometimes overwhelming, but overall: a lovely experience.

I might be able to count with one hand and a couple more fingers the times I experienced the positive anxiousness of attending a first class, not knowing who you’ll sit beside with, not knowing who and how the professor will be, if you’ll find yourself comfortable with the peace or not, and a lot more incognitos.

In this post entry I’ll cover how I felt, a reflection of this experience and what contents we’ve seen (the topic is algorithms).

Table of Contents

1. A reflection on my experience
2. Sitting at front and a rant for the ones “in the back”
3. The professor
4. The topic: Algorithms
5. References

A reflection on my experience

This might’ve not been “my first class”, as I went through an admission course first, where I did have my official first class, but the feeling was different: it was a short (2 months) process, there were lots of students, content was packed and an there was an immediate individual objective, also, there wasn’t much place to deepen relationships between pairs or with the professor. Easily more than half people dropped, and the ones who didn’t and passed the exams were redistributed in different classrooms. Because of this, even though I was in class with a professor and students, I take it more as a warmup session.

Differently, once the “school year” has started, both the professor and the students you’ll see around you are the ones that you’ll share the, coincidentally, school year with.

Sitting at front and a rant for the ones “in the back”

Of course I sat at front, the best ever place you can take in class: you can hear and make eye contact with the professor, you can properly read the board (really important for me as a poor sighted folk), there are no interruptions, and usually you’ll be seated alongside peers that value these same things.

Now, not that I’m surprised, but how come there’s always a group of people that don’t stop talking during the lecture! come on, you’ve chosen to be here! I find it so annoying. Voices get mixed up, it makes it confusing. Also, and probably the biggest factor of my annoyance is that you can see how the professor starts to be annoyed, how his willingness about having a collaborative class group diminishes, how the class focus starts to fade. I can understand a comment or two, but a full timed, developed, group conversation? S.T.F.U. And considering how poorly paid public university professors are in Argentina, I feel it careless to not be silent during class, specially when you’re not paying a tuition.

The professor

For the professor, Marcelo Lipkin, I can only say nice things. I perceived him as a very professional, calm, and involved person. He started the class by engaging ourselves (the students) in a conversation of one of today’s hot topic in Buenos Aires: the dengue fever[1]. This mitigated the usually hierarchical first contact with the professor, where students are trying to decipher how much of a person the professor is. This also made the students speak, myself included. We shared personal related stories and debated for a bit. He then proceeded to present himself (which I’ve observed to be an ego-less approach, not presenting himself in the first place). After his presentation, he shared how classes will go, his grading system and an introduction to the topics we’ll go through the year.

Teaching algorithms and programming gets usually quickly related to computers, a practice that Marcelo avoided, not taking for granted that people know what’s that about. He went through the topic with real-life examples, mentioning the computer as a medium only.

The topic: Algorithms

We’ve briefly went through the topic, explaining over the surface that an algorithm is the definition of an ordered process of logical instructions that are independent between each other but dependent on the intermediate modified overall state, that serves as an input for the next logical instruction and as output of the previous ones. In other words, in an algorithm, a logical step would produce an output that’ll be the input for the next logical step. On any given exit condition, defined as part of the algorithm, the same would end, making the last output the overall output of the algorithm.

In terms of algorithms and computers, there is no direct relation. Algorithms can be independent of computers, being them only logical processes, they can be represented in any form that’ll allow the interpreter (it being a machine or a human) to understand it.

The intersection between algorithms and computers exists at the programming discipline, where algorithms -that a computer would be able to execute- are defined by writing them in a software programming language[2] of different characteristics (low/high level, compiled or interpreted).

References

[1] https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON498
[2] https://www.cs.odu.edu/~zeil/cs390/latest/Public/turing-complete/index.html