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Comment by kqr | Hacker News Reader

I took a data visualisation class in uni that handled this really cleverly. The second assignment sounded very easy. The teacher provided links to the sources where we could find data.

Most people figured that with such a simple assignment (not significantly harder than the first one, which was also easy-ish) they could put off doing it until the last moment.

Most people failed.

This real world data needed hours upon hours of cleaning before it was in any way useable. Of course, the teacher knew this, gave bonus points to the ones who did start in time, and then extended the deadline as he had expected to from the start.

Never again will I underestimate the dirtiness of real world data. One of the best teachers I had.

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This is universal to STEM degrees I think. In mechanical engineering classes you analyze a beam, in real life you analyze an assembly with 50 components that have undergone 100 revisions with 20 different materials and loading from 4 directions that vary with time. Oh, and you have 4 sensors to give you information to analyze critical stresses. But one of them is broken, and Bob who can fix it is on PTO until next Monday, so...

Internships are supposed to fill this gap but it'd be nice if all students could get a taste of real world systems and data. For tech, maybe if they could partner with the IT department at the school to get them exposed to real, messy data. Maybe there are some teaching datasets with over a billion rows that people could play around with.

> This is universal to STEM degrees I think. In mechanical engineering classes you analyze a beam, in real life you ...

Hard to believe this. Don't these degrees require rigorous laboratory assignments where the student learns to differentiate best case scenario with real world uncertainties? STEM is not just some IT certification

As a mechanical engineer : No, my education didn't.

The problem is that most real world problems take too much time to really solve to fit in any modern ciriculum.

Hmmm. We had a whole course on measurement systems that get to the heart of understanding that source of your data and inevitable bias/error is more important than just crunching the data as given. For example, from a typical four year degree.

Not really. MechE courses are really theoretical, and the labs are focused on just being enough to demo the theories. Most of my professors had never worked in industry, they had been in academia their entire lives. Even they wouldn't know how to bridge the gap.

In an ideal world, we'd have separate tracks for people entering industry versus academia/research, but that's a long way off.

That's insane. ME degrees that I know seem to be defined by industry (ie. application of theory). Nobody pursues that degree to stay in academia/research. Anyway you can always pursue an advanced degree if you want to stay in academia. Don't get it twisted though - STEM is not a vocation as per your suggestion that "people entering industry" deserve a special path.

> get them exposed to real, messy data

This times 1,000.

The biggest surprise to me when I got out of school was how messy things were - data, systems, management, priorities...everything.

When I went back to grad school, we had arguments about the assumptions. It was a total 180 from undergrad, and much more useful. So when I came out of grad school, I was able to deal with the ambiguities - maybe even thrived because I understood them.

I majored in nonprofit management and every class had a required field work component with an area charity. I learned so much from the combination of intense coursework and real world experience. Now that I'm the head of data science at a corporation, I wish such integration existed in this field.

Edit: the comment I replied to has since been edited to show how the teacher understood what he was doing, and how he made it teachable lesson and not a punitive one.

Not to miss the point, but I don't think "All my students failed" is the mark of a good teacher. It sounds like the teacher failed to prepare their students for the nature of the assignment. Perhaps he was surprised as they were when they all failed, as I doubt failing most of his class was his intention.

You are being downvoted but you are exactly on point. If some fail they may be bad students, but if the majority of my students fail they're not bad students, it is me who is a bad teacher.

> Of course, the teacher knew this, gave bonus points to the ones who did start in time, and then extended the deadline as he had expected to from the start.

I think what he meant is they 'failed' to get it completed on time and it was meant as a teaching lesson.

That wasn't in the original comment.

Failing is a form of learning. Enabling to fail (preferably in a safe way) is very valuable for learning.

Agreed, and the now edited comment illustrates how the teacher made it a safe lesson. That portion wasn't in the comment when I replied, and it sounded more like the teacher simply failed to prepare their students.

"Of course, the teacher knew this, gave bonus points to the ones who did start in time, and then extended the deadline as he had expected to from the start."

Similarly, it's not good teaching practice to trivialize deadlines.

Yeah plenty of time for workplaces to do that for you. I can count on my hand the number of times something has been a hard deadline. This teacher taught a valuable lesson usable for the rest of the student's carreers and "the most students shouldn't fail mentality" has led to professors I know personally questioning the caliber of student they are receiving and this is a top 30 program I'm referring to. More people should fail, maybe they'd start treating things seriously and the problem of underqualified technical applicants would resolve itself.

That wasn't in the original comment. It has been edited since I replied, which is fine. I do it all the time, sometimes you miss that someone replied during your editing.

I’m currently preparing a data visualization course to be taught this fall, and I would love to hear more about this! If you’d be willing to share some of those resources or the contact information for your professor, I’d really appreciate it. You can find contact info at the link in my profile :)

Not parent poster, but Thomas Powell is the Data Viz instructor at UCSD.

Do you still have the assignment?

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