comment_fhdvsyc
Comment_fhdvsyc
I would say think long and hard about what your trying to get out of university before choosing QC. Not that it’s bad, but because different people are looking for different things (both students and staff)
This post is both for those looking at QC and those already trapped here. I am a doing a second degree at Queens College and well aware of the CUNY ecosystem, within the department I would be considered a Senior.
First of all the CS program at QC is over maximum capacity at this point. It’s doubled it’s enrollment from just a few years ago (due to tech boom) and overtaken psychology as it’s top major at QC, and frankly the department does not have enough staff to facilitate all the students. They barely have enough classrooms; for the most part all your classes will have every seat filled unless the professor is known to be a tough grader.
Students initially choose CS for many reasons, lucrative career prospects, growing up as “the person good with computers”, and a love for video games. Generally there is a rude awakening when they realized that CS@QC is essentially an engineering program with an heavy emphasis on theory.
There are four classes where you will learn programming CS 111, 211, 212, and 313 (you will likely start 111 in your upper freshmen semester, because the classes filled up before your registration time, disappointing but also extremely common so get your liberal arts and math classes done during the first semester)
After these classes the rest of the major consists mostly of heavy theory classes, where while you might have to write some programs, the emphasis in the lecture is no longer put on this. Essentially you are on your own to debug your code and to continue to get better at coding. A lot of students don’t do this and cannot code at this point (barely passing 211 and 212 and just continuing to plow through)
A lot of the complaints stem from a misunderstanding of the major before entering, not realizing it is for the most part a heavy theory curriculum. Computer Science is as much about Computers as Astronomy is about the study of Telescopes. 320 Theory of Computation is one of those classes where we have some great professors, but the students expectations don’t align with the professors. If your not up for theory I would suggest going more into IT route. Data Science and Machine Learning routes require even heavier math (Statistics and Linear Algebra respectively) so avoid those if math is a personal weakness.
Cheating is rampant, some if it is justified in that the professor is undecipherable, other times it’s because teachers don’t have the resources to track cheaters (reassigns same assignment from prev. semester in class sizes of 200+ students) , lastly a lot of professor use an online textbook. There’s a QC Chegg server that will get you any textbook/virtual textbook answer you need; to some degree I blame the professor for switching to online resources like WebAssign and Zybooks where the answer pool is going to be shared somewhere, but what else are they going to do, when each prof. is assigned four/five classes with 38 students each? If there’s an easy route to a passing grade a lot of the students at QC will take it, despite it biting them in the ass later.
The most common reason though is because students can’t program and they refuse to retake classes that they “passed” (often with a C+, I think it’s a disservice for Waxman to give so many C+’s in 211). There’s some weird desperation factor that comes into play around Upper Junior/Senior year where everyone is extremely desperate to graduate whether they can program or not. They are incorrectly assuming that the degree is all that matters and they won’t be tested on this material ever again, which is false for jobs that require a CS education (Discord had a post about some dude failing 20 interviews once they got to the white board question).
These cheaters are both hurting the CS program (they hurt the curve) and the industry (My resume has gone straight to the trash as soon as they see Bachelors from QC, cause the other QC grad bombed the interview so bad). Even ratting them out won’t due anything because professor’s already look so burnt out.
Professor’s are hit and miss, but its mostly adjuncts and the best adjuncts get poached by better universities or industry. Adjuncts make $20k~25k at QC (St. Johns pays double), this is the union rate, and it also ignores how difficult the class is to teach. Yes that adjunct teaching your 300 level class and the one teaching CS12 are making the same amount. QC really does keep it’s best Full Time professors for it’s incoming students though. Ryba and Waxman who cover 111 and 211 are great teachers who genuinely get student’s excited about the material. But IMO they are way to generous in grading, (Waxman changed his curve from sqrt(grade)*10
to sqrt(grade)*11
despite his test being out of 200 points) leaving 313 to be the real gatekeeper class.
313 is where a lot of students drop the major. There are no more reserved lab class hours (so you are expected to have syntax down 100% by here). Staff for 313 changes constantly, but there’s usually at least 1 professor who is both competent and clear. This might be why there is so much desperation and cheating at this level everyone feels so invested. After this class though, it’s a dice roll though, get reviews from other students and avoid teachers who can’t teach (even if they are easy to pass)
If your going to QC picking your classes and trying to get them as early as humanly/roboticly possible is going to be key. Heck pay a senior to hold a seat for you if it comes down to it. The difference between a good professor at QC and a bad one is a huge margin. If you do get stuck with a bad professor you essentially need to self-study the course. Almost all your classes will have a free alternative on MIT edX, Coursera, or Udemy. (I avoid Udacity, because it’s not university backed, but other students swear by it.) These courses are difficult, but they are generally considered by all to be the best resource (so your not really gonna find anything better without hiring a private tutor) Speaking of tutors, QC offers tutoring up until your 300 classes, where the tutors will no longer be able to assist you (because they are likely taking the same classes, further fueling desperation)
The ultimate secret weapon to why CUNY is a great school is the ePermit. 99% of students don’t utilize this, but if you do you can avoid shitty professors and instead take some of the best professor’s CUNY has to offer. The drawback is of course commute, but it’s worth it for certain classes where at QC there are 0 good teachers available. (IMO 323 is shit at QC and you should ePermit to Brooklyn College or CUNY graduate center for a good algorithms class) Again my definition of good is clear and competent professor (has nothing to do with ease of passing) If you’re deciding between two CUNY schools, ePermit lets you get the best of both universities.
I’ll end this post with just my personal recommendation of who I consider good (clear and competent) professors and who I would suggest avoiding, but of course this is just my opinion. If I don’t list a professor most likely I never encountered them or I don’t feel strongly either way.
Good
- Ryba
- Waxman
- Alayev
- Kong (Probably the best QC has to offer)
- Boklan (Have your GPA nuked in exchange for taking a class with Albert Einstein himself)
- Yeh
- Obrenić (She’s mean and unapproachable, but it’s an act)
- Leavitt
Avoid
- Brown
- Phillips
Cited In
- Chapter 1 Revised Outline - 1.2.2 Why Reddit for This Study? Methodological Advantages
- Chapter 1 Revised Outline - 1.3.3 Critical Infrastructure Theory
- Chapter 1 Revised Outline - 1.3.5 Educational Theory and Digital Resistance
- Analysis/Chapter 1/Section 1 3 5 Evidence Report 20251009 - 2. Peer-to-Peer Educational Navigation (Study as Sociality)
- Analysis/Chapter 1/Section 1.3 Evidence Validation 20250104 - ✅ FOUND - Verified Correct
- Analysis/Chapter 1/Section 1.3 Evidence Validation 20250104 - ePermit Campus Arbitrage
- Analysis/Chapter 1/Section 1.3 Evidence Validation 20250104 - Recommended Actions
- Analysis/Chapter 1/Linguistic Markers Evidence Crossreference - Current De Certeau Section (Lines 259-263):
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - 3A. Organized Abandonment
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - 3B. Repair as Innovation
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - ePermit Arbitrage
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - 4C. The Undercommons - Study Despite Institutions
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - Evidence Cross-Reference Table
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - Line 234 - Feature More Prominently:
- Analysis/Chapter 1/Theoretical Concepts Evidence Taxonomy - Usage Guidelines for Chapter Writing
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- Analysis/Chapter 1/Section 133 Evidence Summary 20251009 - Top Evidence (Beyond existing
- Analysis/Chapter 1/Taxonomy Evidence Full Text Extraction 20250104 - 1. Tactical Knowledge Systems
- Analysis/Chapter 3/Vernacular Search - Top Comments
- Analysis/Chapter 3/Transit Stress - Top Comments
Cited In
- chapter_1_revised_outline - 1.2.2 Why Reddit for This Study? Methodological Advantages
- chapter_1_revised_outline - 1.3.3 Critical Infrastructure Theory
- chapter_1_revised_outline - 1.3.5 Educational Theory and Digital Resistance
- analysis/chapter_1/section_1_3_5_evidence_report_20251009 - 2. Peer-to-Peer Educational Navigation (Study as Sociality)
- analysis/chapter_1/section_1.3_evidence_validation_20250104 - ✅ FOUND - Verified Correct
- analysis/chapter_1/section_1.3_evidence_validation_20250104 - ePermit Campus Arbitrage
- analysis/chapter_1/section_1.3_evidence_validation_20250104 - Recommended Actions
- analysis/chapter_1/LINGUISTIC_MARKERS_EVIDENCE_CROSSREFERENCE - Current De Certeau Section (Lines 259-263):
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - 3A. Organized Abandonment
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - 3B. Repair as Innovation
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - ePermit Arbitrage
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - 4C. The Undercommons - Study Despite Institutions
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - Evidence Cross-Reference Table
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - Line 234 - Feature More Prominently:
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - Usage Guidelines for Chapter Writing
- analysis/chapter_1/THEORETICAL_CONCEPTS_EVIDENCE_TAXONOMY - Usage Guidelines for Chapter Writing
- analysis/chapter_1/section_133_evidence_summary_20251009 - Top Evidence (Beyond existing
- analysis/chapter_1/taxonomy_evidence_full_text_extraction_20250104 - 1. Tactical Knowledge Systems
- analysis/chapter_3/vernacular_search - Top Comments
- analysis/chapter_3/transit_stress - Top Comments