Introduction to Cognitive Science

This class is incredibly easy and most can finish with a solid A if you put in some effort. It's also an excellent work-ahead class and is ideal if you foresee a busy period of your life coming up or simply want to pair with a more difficult class. Although I would avoid pairing this with a report-heavy class like ML as the final report legitimately requires a significant amount of time.

Quizzes (15%): The quizzes are open-book and you have two attempts. They are heavily based on the lectures and associated readings and you can easily figure out the answers from skimming the readings. The quizzes are also open from day one and can be knocked out in a few hours.

Individual exercises (35%): For summer we had 6 individual exercises in which you are presented with readings and questions to answer. The requirements are pretty clear and a slightly deeper reading of the literature will give you everything you need to know. I'd say just give them what they're asking for as clearly and succinctly as possible.

Term project (45%): The term project is the hardest aspect of this class and honestly the most time consuming. The project has four milestones in which you pitch your project, submit the final project, and prepare a presentation on the project. There is an optional milestone that you can submit if you want further feedback early into your project. The project itself is an individual effort and you have options of writing a literature review, performing a cognitive science experiment, or creating a computational model. I would say START EARLY and budget more time than what the course requires (~100 hours). I had to take a couple days off work before the due date to bring this one to the finish line. I would also say to put some serious thought about what project you want to do early on as pivoting halfway will seriously put you behind.

There are no real downsides of this course except for the fact that the TAs can be a bit unresponsive at times. However, the grading is VERY generous so you really can't complain. If you address all of the points for the exercises and term paper clearly, then you will get an A.

Overall, what you put in is what you get out, but I honestly feel that putting in a significant amount of effort is not rewarded as equally as just doing the bare minimum. I will say that the course content itself is interesting and very thought-provoking, but again, the class itself is not challenging and it leaves plenty of space for you to take the initiative if you want to dive deeper into the material.

To be honest, the main reason I took this course in Spring 2025 was that I was planning a 2 week vacation abroad, and I was looking for a course that was easy and in which I could work ahead. This course satisfied both requirements. This is more a social science rather than a computer science course. You will learn a lot about how we think, and, by extension, how computers should think. You get out of the course what you put in. There were some flashes of brilliance, but they were few and far between. The course has weekly quizzes (simple), some written exercises (some thinking), and a course project worth, in all of its parts, 45% of the grade. I am neutral on the course- several of my classmates really liked it.

A good choice if you want to :

1. Have less workload (potentially combined with some other intense course)
2. Still want to learn something (not fully waste of time)
3. Push yourself to build or research something creative and interesting

Pros:

1. The reading materials are pretty sufficient and useful, not only for homework doing, but also for knowledge expansion
2. The assignment is not tough. As long as you read the materials and watch the lecture video. You are good to go.
3. Pretty good grading. Got an A even tho I missed 2 quiz.
4. Flexibility for final project. Basically they give you a whole semester to do it and you can choose the topic that you are interested in as long as it makes sense. (Still, good grading, got more than full scores for the 2 check points)

Cons:

1. Might be too easy. You have to push yourself to do the reading to learn something. Otherwise you can just redo all quiz and get full grades.
2. Lecture video is not that meaningful from my point of view.

Full disclosure: I signed up for CogSci thanks to the reviews that painted the course as a relatively easy, mostly stress-free break from the rigors of the more challenging programming-heavily courses in the curriculum. And honestly, it was. I currently have a 99.8% pending the final deliverable grades.

However, I enjoy writing papers, which this the crux of this course. There are no exams, and the quizzes / surveys are basically free points to bolster your grade, in my opinion. The philosophy and other related topics covered, several that parallel those of HCI, was something I found interesting. And the timeliness and professionalism of the course staff in terms of grading and responses on Ed were among the best of any prior class I've taken in this program to date.

With that said, if you're looking for a course to write code or learn coding, this is not it. Yet, during the course project, you're welcome to develop a study that leverages coding fundamentals (for example, my project was basically a cognitive science-inspired ML study). And, the best part: save the project report and see about getting it published (for example, consider the IEEE SIEDS conference as a potential avenue for this!). That's what I'm planning to do, at any rate.

Oh: and to not forget --- but the course opens up almost all of the deliverables on the first day, meaning working ahead is doable.

So if you have a curiosity for learning more about cognitive processes, particularly how they relate to technological applications, and don't mind writing, then I'd highly recommend this course.

Again, this is not a programming class. If you hate writing papers and would rather find comfort compiling scripts, then skip this one. Otherwise, this was a really neat class that is among the best organized and lowest stress courses in the program, in my opinion.

This is the ultimate work-ahead class. I'd recommend it for people looking for a class with a lighter workload or one to double up with another class.

All together, my semester had the following assignments/deliverables/readings:

• 1 book
• 31 papers
• 28 lessons
• 12 quizzes
• 6 exercises
• 4 term project deliverables (1 optional)

The book was a decent read. Could get a little boring at times but it wasn't dry reading. Overall, I enjoyed it.

The papers were a slog to get through. Some were more interesting than others. Just skimming and/or dumping the text into ChatGPT for a summary was often good enough. If I was really trying to get something out of a paper, I'd spend anywhere from 1-3 hours on it, but most papers I'd just skim in about half an hour, meaning I'd retain basically nothing. Definitely a weak point of the class since we don't really need to read the papers for anything (you get the jist of the important papers from the lessons).

I LOVE the way a lot of the slides in their lessons are designed. A lot of good ideas for use of diagrams/images could be gleaned for my own future presentations. Overall, the content in the lessons is provided in short, digestible, and interesting chunks. My only real critique of the lessons is that they often have a moment that asks you to reflect on something, but there's no real incentive to actually take the time to perform the reflection. Most of my reflection in the course came about through the exercises.

The twelve quizzes are a joke. They were unlocked after the first week of class during the Fall 2024 semester, and I was able to get them all done in a single batch over the course of about an hour or two. You get a second chance at each quiz and they give you the correct answers after your first attempt, so there is no reason not to get 100% on each one.

The exercises were fairly straightforward. Most of the time, you're only allowed to write 1000 words in your response, which is a nice amount of writing compared to a class like HCI, where my 8 page papers would get to around 2500 words. You need to write in IEEE format, so I'd recommend using Overleaf. You don't need to use Overleaf, but once you do, it saves a lot of future hassle. This Conference Paper template was my go-to: https://www.overleaf.com/latex/templates/ieee-conference-template/grfzhhncsfqn

Note that the only submission you will need an abstract for is milestone 3 of the term project (the final report submission).

The term project is interesting. It is an individual project (yay, no group!) that you have to spend at least 100 hours on during the semester. You have the option of doing one of three tracks:

• Literature Review: a detailed analysis of a problem from the perspective of cognitive science and survey of the related literature
• CogSci Experiment: a cognitive science experiment
• Computational Model/Tool: a small computational “proof-of-concept” system for the task

The staff provides examples of well written project papers so you get an idea of what they're expecting.

Oh and the monthly Zoom meetings with Prof. McGreggor were fun. They don't have much to do with the assignments though. They are 90 minute open discussions about anything in philosophy/psychology/linguistics etc. He would get into some pretty crazy tangents that make you think and get you excited. His love for the field of cognitive science really shows.

Overall, this was a very enjoyable class and a welcome breather from OMSCS's harder content.

I have been out of school for a few years, and I work full time as a software engineer, so I needed a class that wasn't super work heavy to get myself back into the groove of school. This class is that. Super easy class, and as long as you put the necessary effort in, you are primed to get an A.

Quizzes: There are 12 quizzes, based on the readings. They are open-book, and two attempts are given. The lowest quiz grade gets dropped.

Individual Exercises: There are 6 of these, and they are essentially easy if you follow the prompts. Based off of the readings.

Term Project: It is a self-directed project based on a topic of your choosing, and you are required to submit a pitch, final report, and final video presentation (varies depending on the track that you choose). Essentially you're free to either go in your own direction with this, but you're also able to just answer the prompts for each phase to ensure a good grade.

Overall, very easy class, definitely recommend taking it if you can.

This is a super easy course and it's good for your GPA. However, if you're looking to learn something valuable for coding, it might not be suitable for you.

Quiz: There are 10 open-book quizzes, and you can attempt each quiz twice.

Individual Exercises: There are 5 short essays based on the lectures and slides.

Term Project: You can choose a topic from the list provided by the professor. The topics are related to computing areas and cognitive science. By the end of the course, you will need to complete 3 essays for this project, with the final essay having a word limit of 5000 words. Additionally, you will need to record a video presentation for your term project. Although it is simple, it is recommended to start the term project early because it may take more time than expected.

Overall, this course is more focused on essays and theory.