[acbart]

Isn't it amazing how people pass courses, even perhaps demonstrate mastery at a point in time, but manage to get to later courses without fully understanding things? Students end up with a very strange mental framework by the time they graduate, and it seems like most students actually know shockingly little. I don't know that there's a solution, or even that it's an issue. To me, this is simply a reflection of how people learn.

Regardless, this seems like a nice little document for those 20% of students who are still willing to read supplementary materials. Then again, this is short and clear enough that if it were properly chunked within a course and had graded assignments attached, many students would probably actually skim it.

If you ever want to develop this some more, I hope you'll consider something like Runestone[0], in order to give it some auto-graded questions along the way!

[0] https://runestone.academy/runestone/default/user/login?_next...

[henrikschroder]

When I did my CS programme decades ago, we all started with Scheme, which is very high-level, and forced everyone to focus on the algorithms, the math of it, instead of what the hardware is doing, or how the Scheme interpreter is implemented. It gets you going, thinking about values and execution and iteration and recursion.

Starting with bits and bytes and hardware would be pretty goddamn boring, I think. You'd lose a lot of students that way.

That said, in the third year we had a course in analog electronics, which was basically transistors and logic gates.

Following that course was one in digital electronics, where we all built our own little toy 8-bit computer, wiring the CPU ourselves, writing the microcode ourselves. I'll never forget the a-ha moment when you realize that your instruction set are just binary patterns representing which wires to put a current on, which units to toggle on and off. The instruction to move a value from a register to an address in RAM has to look like this, because you need to toggle the read input on the correct register, and the write input on the RAM unit, and everything else has to be off. Blew my mind at the time.

The clock was manual if you wanted to, so you could step through and watch your little CPU run a program, or you could set it to like 1Hz and watch the thing go. And from there, you can sort of get how a modern computer works, it's just a matter of going from 1Hz to 1GHz, wider buses, wider instruction sets, but it's no longer "magic" how the CPU works, it's all ones and zeroes, for a reason, and you now know that reason.

[puzzledobserver]

I think it depends on the audience.

For a group of prospective CS majors, or people learning programming for its own sake, I think it would be good to start with a high level language, say Python, Scheme or Ocaml, and then progressively deconstruct the layers of abstraction between the language and the physics.

For a group of electrical engineering majors, it might actually tie in better with their other courses if one starts with simple physical constructs like bits, bytes, and gates, and gradually introduce abstraction layers to form more convenient programming models.

[smallcharleston]

That’s basically how they taught my computer architecture course, but they started from C (instead of Python) and worked back to assembly and then to transistors or whatever those gate things are (I studied enough to make an A and don’t care anymore unless someone pays me to).

I think it must be a reasonably normal approach.

[gedy]

It's interesting as I studied Computer Engineering which focused on the hardware and low level, with some programming on top of that. I was pretty good at that too. However afterwards the Google-style interview algorithm questions do not come naturally for me, and you'd think I'm a complete imposter by the look in some 20-something interviewers eyes, even though have been programming for 20 years...

[cmroanirgo]

I feel exactly the same way: Computer Systems Engineering. Took to programming easily, as well as digital. (Not as good in analogue though). Was teaching my tutors programming by the end of first year. Getting asked to hack/ deconstruct software in 2nd.

Would fail miserably in these Google style tests.

I think the difference is that our brains are wired to solve issues from first principles. Some of the best CS I've come across use pattern recognition to determine the best algo to apply to a situation.

The end result is the same code, but we speak different languages until we arrive at the same end. Other design methodologies help give us a better framework for cross communication.

Eg. Voronoi diagrams. Absolutely fantastic way of doing mesh reduction. Took a CS guy to point it out to me ... (I was mostly thru designing my own).

Eg. Same CS would never consider using ASM to save clock cycles.

[burfog]

Scheme is deadly boring. You'd lose a lot of students that way. Starting with bits and bytes and hardware would be pretty goddamn fun, I think.

I first really got into things with assembly language for DOS. It was interesting to directly control the IRQ controller, real-time clock, interval timer, and keyboard interface. These were all motherboard chips that could be messed with.

Years later I passed a mandatory Scheme class. I tolerated it to get my degree, but I was furious. I handed in just enough assignments to pass the class. If the degree had started with Scheme or required very much of it, I would have found something less miserable to do with my life.

[henrikschroder]

Another positive aspect of starting off with Scheme was that it leveled the class out, it removed the edge that all the self-taught programmers thought they would have over the people who hadn't really done much programming. Everyone was pretty much equally clueless. Very refreshing.

[lbatx]

You make an interesting (unsupported) assertion here. You, who find talking to an IRQ controller, real-time clock, etc. interesting, find Scheme boring, therefore others (who may not share your interests in such details) will also find it boring. Bit of a logical fallacy there...

[acbart]

I've run a lot of surveys of introductory students trying to find what topics are more or less interesting to them. A part of my dissertation was committed to it, actually.

At this point, I'm more or less certain you'll rarely find situations where you have a mass-appealing context. One students' dream context is another students Most Boring Possible. You're probably better off having many diverse contexts and hit all the MUSIC guidelines (eMpower students, Useful to their long/short term goals, make students Successful, make it situationally and domain-based Interesting, and give people opportunities to demonstrate that they Care about each other).

[aldanor]

Agreed.

I recall, in high school, we were writing a disassembler for a custom weird assembly language which was written by one of the school's graduates a few years prior to that... and we had to use this assembler as a language of choice :) That's high school! And it was quite fun. These days, many CS grads/post-grads know tensorflow and other flashy high level stuff while having very vague understanding of how things actually work at the lowest level (source: interviews).

[314]

Most students approach courses as a form of top-down search with a cache for items they see often. It is generally difficult to get them to reason about subjects from the bottom up.

A smaller proportion of students approach courses from the bottom-up (10-20%?) - they tend to start with the basic pieces and glue them together over time to understand larger concepts.

I’ve read about this phenomenon (it is extensively documented in pedagogic literature) and seen it in action (I taught CS for about ten years) but still could not explain to you why that split occurs.

I would speculate that it is a difference in type-1 vs type-2 reasoning based on the level of familiarity and comfort with the prerequisites to each course, but even that guess is heavily biased by studying constructivism in CS pedagogy.

[mycall]

I think middle-out is superior for learning both bottom and top at same time ;)

[314]

Allows much better compression of knowledge :)

[giovannibonetti]

When I was in college I was very interested in learning computer fundamentals bottom-up, but I had some pripr experience programming a high level language. With that prior knowledge everything made sense to me.

Maybe if I didn't have this prior knowledge back then the classes would be very boring.

[Metus]

Can you link a document discussing this phenomenon or at least give the relevant keyword to search myself? I have noticed something similar when TA'ing, observing my colleagues and also when learning myself.

[314]

I can't give you a direct link to such an article, although I can do a bit more and less. Five years I was writing such an article, although sadly I got side-tracked by other activities, I still have the rough outline that I was working on. From there I can give you a list of keywords / some seed articles to read in the area that you can snowball from to find more relevant material.

Keywords: CS1, cognitive approaches, curricular planning, programming, difficulties, learning, novices, programming, teaching, student retention.

Articles: * SIGCSE Bull. A cognitive approach to identifying measurable milestones for programming skill acquisition. http://doi.acm.org/10.1145/1189136.1189185

* IJ of Man-Machine Studies. "Novices and Programming" by Soloway and Spohrer (Book Review). 1993

* Lawrence Erlbaum Associates. Studying the Novice Programmer. 1989 (Soloway, E. and Spohrer, J. C.

* ITiCSE '05. A study of the difficulties of novice programmers. 2005. http://doi.acm.org/10.1145/1067445.1067453

* Using Alice in Overview Courses to Improve Success Rates in Programming I. Johnsgard, Karin and McDonald, James. 10.1109/CSEET.2008.35

* ITiCSE '03. Using lab exams to ensure programming practice in an introductory programming course. http://doi.acm.org/10.1145/961511.961519

* SIGCSE. Constructivism in computer science education. Mordechai Ben-Ari. http://doi.acm.org/10.1145/273133.274308.

* Signs. Epistemological Pluralism: Styles and Voices within the Computer Culture. Turkle, Sherry and Papert, Seymour. 1990. http://www.thinkingcurriculum.com/turklePapert.pdf

Based on your question I would recommend the last two articles as the most interesting. It's been a long time since I read the Turkle article but I recall that it is the most relevant to understanding why we observe this behaviour, and the Ben-Ari article is a comprehensive framework to wrap that understanding within.

Although I never finished the article (fairly typical academic story :) I did write the software / courses that used it and tried it out successfully for five years. I can't give you a link to the software / results for fairly boring reasons to do with IP and confidentiality, but my overall view was that we can build learning experiences that can be successfully accessed by both types of student - but the level of polish and integration that is required to pull it off is about an order of magnitude greater than what is typically invested in undergraduate education. Obviously there is such a huge variation in the effort that goes into individual courses that such an observation is only relevant to a similar institution / student group at a particular point in time.

[vegetablepotpie]

>it seems like most students actually know shockingly little

I think that having students take 5-6 classes together in 16 weeks doesn’t promote mastery in any of those classes. Tying the performance in those classes to scholarship eligibility and job placement incentives grades, not necessarily understanding. Grades and mastery can be separated because 2-3 exams in a class, which determines the majority of the grade, rewards students the most, on a time investment vs. performance basis, for understanding technicalities in the grading system and for hyper focusing on the types of problems that can be on an exam. This doesn’t promote mastery, this is a game academia and students play for the satisfaction of government, finance and corporations. Definitely, a problem, solutions could include more frequent sampling of understanding, more diverse ways of measuring knowledge, decoupling performance from financing and longer periods to learn topics.

[bjornsing]

I’ve been thinking a lot lately about why understanding and mastery is not rewarded in education to the extent some/I believe it should be. My current thinking is that it’s simply not how most people learn, and few systems can withstand pressure from the great majority.

There are interesting exceptions though: take the Putnam math test for instance. It’s taken mostly by math and theoretical physics majors who want to go to grad school in those subjects. The maximum score is 125, and the top scores are typically 115+. The median score however is usually... [wait for it]... zero.

I suspect a lot of grades would have that kind of distribution if they really tested for deep understanding and mastery of the subject.

[inanepenguin]

> Isn't it amazing how people pass courses, even perhaps demonstrate mastery at a point in time, but manage to get to later courses without fully understanding things?

People remember what they are required to recall (citation needed). Classes can only test for so many things, so people are going to remember what they needed for assignments or tests. It feels like that's one of the reasons apprenticeships are hailed by some as useful. They "test" what is required in real world application. I've never needed to know that 2^10 is a kilobyte as a developer building websites, but would that be surprising/amazing? There are many things I've needed outside of school that were never taught.

As long as CS is used as the path to software development, it will be a balance between theory and application.

[Abishek_Muthian]

Recently I had a conversation with someone who has been featured in Kaggle leaderboard(top 1%) telling 'CS background isn't helpful for Machine Learning'.[1]

I believe that he didn't understand what Computer Science actually is, besides having a degree in it. I'd say it's because of the educational system, where one could attain a degree without actually qualifying in it.

In under developed/developing economies if only qualified people get their degrees, then only a fraction would get their jobs and it would be very bad for that economy and so bad educational systems are by design.

[1] https://twitter.com/heavyinfo/status/1209330850363404288

[xenihn]

What does he think Computer Science is, and what do you think it is?