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The Engineering School Survival Guide: 4 Frameworks To Dominate Your Degree

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Hey all! This week I’m happy to bring you an absolutely fantastic guest article from Tom Miller.

Tom is an engineer and physics tutor obsessed with independent learning. He writes about unconventional study methods at WTF Professor , aimed at simplifying the learning process for engineers and technical students.

I first met Tom a few months ago when he emailed me with some questions on starting his own blog. In the short time between then and now, I’ve seen WTF Professor turn into an awesome resource for any student who’s interested in hacking their learning methods.  On to you, Tom!

Isn’t it funny, that when you tell older people you’re doing an engineering degree, that they tend to only have one of three responses:

• “Ooooh you must be so smart.”
• “It’s gonna be so easy for you to find a job when you leave college.”
• “Smartypants. You’re going to make the big bucks.”

For them, it’s the logical choice. Little Johnny’s gonna grow up and build robots and have job security. That’s what they see on the outside.

But little do they know, the insider’s world is a whole different ballgame.

Before freshman year started, the picture was so rosy. Everyone was encouraging. Mom and dad were happy. High school friends congratulated you on your brilliance.

“You’ve always been good at math. This will be perfect for you.”

But within a week of starting classes, the reality of the situation starts to hit. The wonderful story everyone has been telling you doesn’t look so wonderful anymore, as upperclassmen start to come out of the woodwork.

• “Engineers have no life.”
• “All you guys do is study!”
• “I had a roommate who stayed up for 2 weeks straight and lived in the computer lab!!!”

Doubt creeps in as you start to wonder, “Am I really cut out for this?”

The truth is, both sides have it wrong. The reality is this:

Yes, engineering school is hard.

Yes, you have to put in the time.

Yes, the exams are sometimes ridiculous (e.g. a 37% was the class average on my first Vibrations exam).

But it’s doable . And if you learn the approach, stay diligent, and do the right work, you not only will graduate, but excel – and leave your Econ major buddies wondering how in the hell you did it because you were out with them every Friday night.

Now, based on my extremely professional, authoritative, expert opinion, there are 3… no actually 4 key frameworks that – if you master – will unlock the secrets of the annoyingly super-productive engineering student.

1. Learning to play the game

Engineering school is a game. And like most games, it has rules, a score, and levels. But also like most games, it can be optimized . There are strategies and shortcuts that go beyond simply going to class and doing the homework. Learn to play it.

2. Hacking the learning process

These are the best practices top engineering students stumble upon. Platitudes like “find a quiet place” or “use a study buddy” have no place here. The brain is a learning machine and hacking that machine means the difference between the dude who never seems to “study” but destroys the curve, and the students who spend hours at the library on weekends but just manage to scrap by.

3. Completing group projects without being charged for homicide

You can master the game. You can become a learning machine. But nothing can derail your confidence and progress like a horrible group project experience. Resentment. Spiteful all-nighters. Pain. It can all be avoided if you prepare yourself beforehand.

4. Landing an awesome entry-level job

A complete and utter mystery for us analytical folk. Should I go to the career fair? What should I say? Should I do research? What about internships? Learn the truth about how to find the good ones.

Framework 1: Learn to play the game

If you’ve spent any amount of time at all in the engineering building(s) at your school, I’m sure you’ve come across the zombies .

The homework zombies, that is.

The individuals who seem to spend every waking minute in the ASME lounge, books strewn about, head in hands, looking like they’re about to be told they’ve just lost their life’s savings after not sleeping for a week…

You know, this guy?

Contrary to popular belief, this is not the inevitable life of the dedicated engineering student, but actually the result of some less-than-optimal choices about how to approach your engineering program.

You can have good grades, sleep, and a social life (well, at least among other engineers), despite what business majors will tell you.

Step 1: Before the semester starts, study the syllabus and do an 80/20 on your grade.

It’s late. Friday night. So naturally you and your roommate do what every other normal college student does on a Friday night.

Challenge each other to a Super Mario deathmatch.

The stakes are high (pride is on the line here), so you start thinking strategy.

What should you do?

Well, probably figure out some combination of speed vs. risk of death, and try your damnest to finish each level as fast as possible.

You’re definitely not going to just jump in and indiscriminately start collecting coins, ignoring the fact that you could die at any moment by way of a stray turtle shell or angry Goomba.

Well it’s the same story in your coursework.

If you walk into Physics II, attempting to take on every single scrap of textbook reading, ace 100% of your Mastering Physics homework (kill me), do all the recommended practice problems (Gauss’ Law – seriously is this really necessary?), you will destroy your brain and any semblance of a real existence you hoped to have in college (yes, studies have shown this – my own personal studies on myself…).

The point is, classes are goal-oriented .

Yes, we all want to “learn,” “expand our horizons,” “other platitude you hear on your campus tour.” But we’re not in school just to satisfy our intellectual curiosity. If you’re just interested in that, why not pick up a textbook in your free time? Or spend thousands of hours on Google, Wikipedia and Youtube where you can find virtually everything you can expect to be taught in any engineering curriculum. Learning on your own is easy .

So when we say, “I want to learn engineering,” you’re really saying is, “I want to study the specific things about engineering that I need to know in order to get my degree with a respectable GPA.”

It’s the same as saying “I want to get good at Super Mario.” What you really mean is: “I want to get good at finishing levels as quickly as possible, and defeating Bowser at the end.”

And as you’ll find, it’s a more effective approach to learning anyway. Humans are goal-directed animals. Establish a target or a problem to solve and our brains immediately start churning on it.

The more clear and focused the goal, the faster you can develop a strategy and start taking action towards it. You might even set a world record in the process.

So all of this is to say that before you even start the semester, there are two things you can do to 80/20 your course, a. la. Tim Ferriss ( per Mr. Pareto ).

First, get your hands on a syllabus as soon as possible. Identify the few key assignments that are going to heavily determine your grade.

The top spot is, of course, usually reserved for the final exam, or in some cases the final project report/presentation for project-based courses.

• Then midterms
• Then quizzes
• Then homework assignments (problem sets)
• Potentially “class attendance” (whatever that means)

What do most students spend the vast majority of their time working on and stressing over?

That’s right: homework assignments! The least, or second-least, important component of your grade.

Hence, zombies.

Zombies dedicating large 5-hour chunks of Friday nights towards assignments that make up 0.42% of their grade.

Yes, yes I know what you’re going to say:

“But homework problems are the absolute best practice for the exams. If you don’t spend hours and hours on the homework you’ll failllll…”

Okay, somewhat true. Focused practice solving problems likely to show up on the exam is just about the most effective use of time grade-wise you can invest as an engineering student.

But in many cases homework problems give you the run-around, and 50% of those problems will never ever show up on an exam.

Which is why you should…

Step 2: Look for past exams on Koofers

Don’t you wish sometimes your professor could just show you what’s going to be on the final at the beginning of the semester, so that you can just cut to the chase? Start studying now, instead of waiting for 2+ months of anxiety?

Well there’s actually nothing stopping you from doing that.

It just takes a little digging (and not much really to be honest) and you can have 20 final exams in your hands that represent pretty much everything you would see on your Calc final.

From that point you can “reverse engineer” what you need to focus on for the course. Organize the exam problems by topic area and make sure you’re hitting practice problems that cover what you’re seeing on past exams.

Professors have time constraints like everyone else, and really aren’t that imaginative when it comes to developing new and innovative exam problems.

( Note: you can also go and sign up for engineering societies like ASME or others that usually have file cabinets full of exams.)

Framework 2: Hack your learning

Knowing what to spend your time on is of primary importance. But now that you know exactly which exams or assignments will most impact your grade, and have gotten a glimpse into what problems you will have to master for the exams, it’s time to get more efficient.

I’m talking about stuffing new information into your head twice as fast as typical students, who, while well-meaning, fail to learn efficiently because they dive in with whatever horrible study advice they picked up from grade school, parents, friends, etc. and don’t adopt a strategy.

There are best practices out there, folks. And here are the key ones for technical students.

Step 1: Use the 1-2 lecture prep punch to maximize your retention of new material.

The night before class, do a google search on the next thing up on the syllabus. Don’t try to learn it all, just read through the Wikipedia page and the basic information, and generate a list of 10 questions.

Now you’ve started your brain in motion and your sub-conscious will be churning on that new topic while you sleep before lecture the next day.

Then, get to lecture 5 minutes early and do a brain dump before class. If you just waltz into class without any sort of preparation, your brain is sitting idle, unreceptive to the completely foreign concepts about to fly your way.

As creative educator Harry Lloyd Miller wrote back in 1927,

“Lecturing is that mysterious process by means of which the contents of the note-book of the professor are transferred through the instrument of the pen to the note-book of the student without passing through the mind of either.”

This doesn’t have to be you.

Before lecture, take 5 minutes and a blank sheet of paper, and write down absolutely anything you can think of related to the topic of discussion for the day.

It doesn’t matter how idiotic you find yourself (and sometimes I even surprise myself with how idiotic that actually is). Just keep writing, drawing diagrams, or doodling about topics covered in last lecture.

By doing this, you’re kick-starting your mental circuits around the topic and initiating the questioning process, creating an anchor point for new learning, identifying exactly what you do and don’t know about a particular topic, and training your MacGyver-like powers of conjuring understanding out of nothing.

Step 2: Learn deeply by cracking the code of worked problems using the Reverse Learning Technique.

Fed up with reading the textbook? Most engineers are. We’re supposed to be out there tinkering, right? Building stuff and being all technical and whatnot?

How frustrating can it be to spend hours in lecture only to feel like you still have no idea how to do the homework problems?

The problem is, this isn’t really how we’re wired to learn. We’re wired to learn by doing.

One method of doing this is reverse engineering stuff – peeling back the layers from a finished product to try to gain insights into the structure, process, and technology that underlies it.

Reverse Learning works in much the same way. It’s a technique for working backwards from the solution to a complex homework problem or potential test question to a set of related core concepts (lecture and textbooks work the opposite way).

The benefit: this is much much deeper learning than you would ever achieve by staring at your lecture notes and textbook diagrams.

Plus, this is how it works once you graduate into the real world of engineering. You have to figure things out by looking at other people’s solutions, and recognizing the patterns of activity.

Editor’s note: This applies to all sorts of things. The main way I’ve learn how to make the videos on my YouTube channel in such high quality is through watching other polished videos and analyzing their components.

Work your way through the toughest problems you can get your hands on in this way, and you’ll develop the ability to look at a problem, recall what phenomena are acting, and apply a core set of formulas.

Step 3: Use Active Recall. Test your knowledge early and often.

Ever wonder why you can take pages and pages of notes, read the entire textbook, and sit through hours of lecture, but fail to answer virtually any question about the material immediately afterwards?

We run into this unfortunate situation because we think of ourselves like sponges – we’ll somehow absorb this new (albeit extremely uninteresting) information as it washes over us like a warm bath.

As the professor keeps droning on, it’s a fight to pay attention. Your focus drifts and your brain is off to the races about anything and everything besides the new material (Who won the game last night? What should I have for lunch? Is that guy sleeping?).

This is what we call passive learning : the antithesis to efficiently digesting new information.

The solution: something we call active recall (not to be confused with Total Recall ).

Listen to Cal Newport, author of How to Win at College , break it down for us:

So first, start with a problem from your study materials, making sure not to look at the solution beforehand.

Then try your best to come up with the solution method and steps off the top of your head, without any supporting materials. Do the best you can and even guess if you have to. Write down what you can, and then go back and verify whether you were correct with the actual solution.

Use Reverse-Learning to understand the underlying concepts and solution techniques first, but then repeat this Active Recall process throughout the semester and you’ll be very prepared for seeing and responding to tough questions on the exam.

Step 4: Rehearse your performance. Become a conditioned machine for attacking test problems.

“Most of the time students spend studying for exams in the traditional way is wasted because they aren’t practicing what they’ll have to do on the test.” ~Adam Robinson, author of What Smart Students Know

What’s the one thing you always hear from otherwise smart and hard-working engineering students following a tough exam?

“I know the stuff. I always do well on projects and problem sets. I just don’t test well.”

We can all empathize. Testing really doesn’t make too much sense in the whole scheme of developing as an engineer.

But like we’ve already discussed – engineering school is a game. And a huge chunk of that game, whether you like it or not, is test performance : the ability to walk in there, not freak out, and regurgitate specific information under extreme time pressure.

Think of it this way. It wouldn’t make too much sense to hear from a PGA tour pro:

“Man, I can really stripe the ball on the range, and sink 30 foot putts on the practice green. So I know that I have the skill. I just don’t play well on the course…”

So think of exams more like a performance. Forget “studying” and focus on “rehearsal.” This means recreating, as closely as you can, the exact test conditions and timing.

And don’t fool yourself into thinking that just because you’ve been able to do a few problems successfully in the past, that you’ll be able to do the same thing on test day. Performance anxiety is a bitch (you know what I’m talking about – that sweaty-palms, holy-shit-I-know-nothing, think you’re going to die feeling).

So not only do you need to rehearse (a la Active Recall), but you also need to do it under time pressure , and do it often. As Tony Robbins says,

“Repetition is the mother of skill.”

And intelligent, focused repetition, is the key to developing your test-taking chops in the shortest amount of time.

Framework 3: How to get through group projects and capstones without resorting to violence or blackmail

This is actually amazing practice for working with un-motivated co-workers, which is an inevitability of life you’ll soon discover upon graduation.

But seriously, group projects suck bad. Real bad. However, you can make the best of them.

Look, you’re going to have the guy who’s taken the class 2 times before. You’re also probably going to have the one guy who is painfully socially awkward. So don’t expect miracles.

Assume that you’re going to have to be the one who pushes the project forward from the outset, and you won’t be in for any unexpected surprises, frustration, or let-downs.

Take control – this is your education.

Here’s what to do:

Step 1: Make a schedule.

Take this as a great opportunity to teach yourself how to use Microsoft Project. Or just map it out by hand. Or use Trello .

Whatever you do, split the project up into multiple deliverables and set intermediate target dates for specific work items (e.g. week 1: brainstorming, week 2: research, week 3: preliminary simulation due, etc.).

Every single college engineering project I participated in ended up in a mad-scramble midnight dash. And ever single time it was entirely a result of poor planning (actually, no planning).

Step 2: Set up regular on-campus weekly meetings, preferably during the day.

Once you have your deliverables outlined, you’ll have something to work towards on a weekly basis. And despite you and your teammates’ best intentions you WILL NOT – I repeat WILL NOT – work on the project until the last minute unless you have a weekly check-in.

Other classes, exams, tailgating, meet-ups, whatever, will always always seem to get in the way unless you can all get together and be held accountable in-person.

Volunteer to do this unless someone else in your group has a burning desire to run the meetings. Being able to organize and run a technical team is probably the single most valuable skill you can develop in preparation for the real engineering world.

Plus, it puts you in the driver’s seat so you won’t have to rely on someone else remembering to do it.

Organize your meetings around your schedule deadlines, set an agenda beforehand by email, and make sure to assign and record next actions that each team member has committed to for the upcoming week.

Yes, it’s more work and somewhat of a headache to round everyone up and deal with the inevitable absences and excuses. But you’ll set yourself up extremely well for Steps 3 and 4.

Step 3: Hold your teammates accountable to getting their shit done on time.

There’s no magic here. If your group is meeting consistently, and agreeing on deliverables for each team member, there aren’t too many excuses to be had. If you’re real, honest, and straightforward in your communication, most people will get on-board quickly and realize that it’s in everyone’s best interest to do their part on time.

But, on the other hand, if they don’t get their part of the project done, take control .

We’re not trying to cultivate company culture here; we’re trying to learn and get a good result. Pick up your teammate’s slack if you have to. If nothing else, they’ll at least feel guilty enough for not contributing that they might even be compelled to write the final report for you.

Step 4: Turn in product and testing deliverables early.

Not because it’s just “good” to get things done early, but because turning in product and testing deliverables to class TA’s or professors early allows you the (golden) opportunity to get feedback and be able to iterate before turning it in.

They’re usually just happy to see that students are putting in the effort, and usually end up giving you feedback that is directly correlated with what they’re looking for – i.e. MORE POINTS.

This will set you way way ahead of your other classmates, who by nature of doing last-minute dashes the day before the due date, have to essentially turn in a first draft without getting that valuable feedback.

That could mean the difference between a 75 and a 95.

Framework 4: Get internships and build stuff – how to guarantee yourself a cool-ass job by getting legit engineering experience

To say there are a lot of misconceptions about what companies are looking for in new engineering hires is an understatement.

• Do I need a good GPA?
• What classes do I take?
• What if my degree doesn’t match up with the job requirements?
• I didn’t do any undergraduate research – am I screwed?
• Should I get an internship, or do a co-op?

And the Career Center at your school is probably not much of a help either.

“Really? Is a resume workshop really going to land me a job at 3M or Microsoft or Black & Decker?”

From my perspective, there are 3 things that will significantly contribute to landing a great job after graduation. And none of them involve – thank god – business cards or networking events.

• Demonstrate your ability to do hands-on work in a real environment and contribute to a company in a significant way
• Stand out by completing remarkable projects
• Develop your “natural” network

I’ll focus on #1 and #2 here. There are plenty of amazing materials on the long-game of networking out there ( here , here , and here for example).

Step 1: Demonstrate you can do work

There must be a question on r/EngineeringStudents literally every day asking one thing:

“How do I get an internship/entry-level job?”

And half of them are asking about GPA.

• “What if I have a 2.5? Will anyone ever hire me?”
• “Do I need a 4.0??”

Most companies feel more comfortable with someone who knows “how to work.” Now this can be an engineering internship, but it could also be working summers for the family business… or at Pita Pit…

The questions running through their head when they interview you will include:

• Can you get along with people?
• Have you built stuff in the past?
• Can you show up on time?
• Are you going to be a weirdo?

Now you’re probably thinking, “Yea, okay I’ll do all that and they’ll say, ‘There are 100 other students exactly like this person.'”

That’s where uniqueness comes in.

Step 2: Stand out

Bottom line: you need to do some cool shit.

It doesn’t matter how hard it was. No one is going to care whether you did it over a weekend, or whether it took you 200 hours.

If you make something that grabs someone’s attention (or is “remarkable” in Seth Godin speak ), you’ll stand out head and shoulders above everyone else who has the same Fluent simulation or power-tool improvement project on their resume.

The most compelling job application I’ve ever seen came across my desk 2 summers ago (I work at a small manufacturing company in the Automotive business). It was a rather sparse resume, with a GPA listed as “2.7” with a link prominently displayed that said something to the tune of “custom robot hand integrated with Matlab.”

Clicking the link brought me to a youtube video of this particular applicant wearing a custom-built robot glove , manipulating a matrix of force values within a Matlab window.

I was blown away.

I showed it to my team.

I showed it to my boss.

I showed it to the VP.

It was seriously the coolest job application I had ever seen. And honestly, the guy probably just focused on that one project instead of his courses for a semester.

But it paid off. We ended up offering him a position.

But guess what: yup, already took a job at another company he had a better offer with.

Which goes to show you the power of differentiating yourself. It doesn’t take much, but if you stand out , and haven’t completely blown it in the other areas (e.g. failing out of school, zero work experience, being a weirdo, etc.) you’ll stand head and shoulders above other applicants.

Want more tips for succeeding in your engineering career? Here’s one professional engineer’s top advice for students .

Git ‘er dun

Okay people. You’ve made it this far, so I know you have the determination and persistence to get through your degree program unscathed.

So remember:

• Put in the time and effort intelligently and selectively (by optimizing for assignments with big grade impact)
• Make sure that time is well spent (by using efficient learning techniques the most out of your study time and test prep)
• Don’t let group projects drag you down (take ownership and lead)
• Get yourself a sweet gig by doing cool stuff (without being a weirdo)

It’s not rocket science (well actually it is for you Aero people), but it does require that you step outside the norm. The difference between barely scraping by, and graduating cum laude might just come down to your strategy.

And in the end, you may just end up building robots after all.

Featured Image: Engineering Department employees, 1962 by Seattle Municipal Archives, CC BY 2.0

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Problems & Exercises

1.2 physical quantities and units.

The speed limit on some interstate highways is roughly 100 km/h. (a) What is this in meters per second? (b) How many miles per hour is this?

A car is traveling at a speed of 33 m/s 33 m/s size 12{"33"" m/s"} {} . (a) What is its speed in kilometers per hour? (b) Is it exceeding the 90 km/h 90 km/h size 12{"90"" km/h"} {} speed limit?

Show that 1 . 0 m/s = 3 . 6 km/h 1 . 0 m/s = 3 . 6 km/h size 12{1 "." 0`"m/s"=3 "." "6 km/h"} {} . Hint: Show the explicit steps involved in converting 1 . 0 m/s = 3 . 6 km/h. 1 . 0 m/s = 3 . 6 km/h. size 12{1 "." 0`"m/s"=3 "." "6 km/h"} {}

American football is played on a 100-yd-long field, excluding the end zones. How long is the field in meters? (Assume that 1 meter equals 3.281 feet.)

Soccer fields vary in size. A large soccer field is 115 m long and 85 m wide. What are its dimensions in feet and inches? (Assume that 1 meter equals 3.281 feet.)

What is the height in meters of a person who is 6 ft 1.0 in. tall? (Assume that 1 meter equals 39.37 in.)

Mount Everest, at 29,028 feet, is the tallest mountain on the Earth. What is its height in kilometers? (Assume that 1 kilometer equals 3,281 feet.)

The speed of sound is measured to be 342 m/s 342 m/s size 12{"342"" m/s"} {} on a certain day. What is this in km/h?

Tectonic plates are large segments of the Earth’s crust that move slowly. Suppose that one such plate has an average speed of 4.0 cm/year. (a) What distance does it move in 1 s at this speed? (b) What is its speed in kilometers per million years?

(a) Refer to Table 1.3 to determine the average distance between the Earth and the Sun. Then calculate the average speed of the Earth in its orbit in kilometers per second. (b) What is this in meters per second?

1.3 Accuracy, Precision, and Significant Figures

Express your answers to problems in this section to the correct number of significant figures and proper units.

Suppose that your bathroom scale reads your mass as 65 kg with a 3% uncertainty. What is the uncertainty in your mass (in kilograms)?

A good-quality measuring tape can be off by 0.50 cm over a distance of 20 m. What is its percent uncertainty?

(a) A car speedometer has a 5.0 % 5.0 % size 12{5.0%} {} uncertainty. What is the range of possible speeds when it reads 90 km/h 90 km/h size 12{"90"" km/h"} {} ? (b) Convert this range to miles per hour. 1 km = 0.6214 mi 1 km = 0.6214 mi size 12{"1 km" "=" "0.6214 mi"} {}

An infant’s pulse rate is measured to be 130 ± 5 130 ± 5 size 12{"130" +- 5} {} beats/min. What is the percent uncertainty in this measurement?

(a) Suppose that a person has an average heart rate of 72.0 beats/min. How many beats does he or she have in 2.0 y? (b) In 2.00 y? (c) In 2.000 y?

A can contains 375 mL of soda. How much is left after 308 mL is removed?

State how many significant figures are proper in the results of the following calculations: (a) 106 . 7 98 . 2 / 46 . 210 1 . 01 106 . 7 98 . 2 / 46 . 210 1 . 01 size 12{ left ("106" "." 7 right ) left ("98" "." 2 right )/ left ("46" "." "210" right ) left (1 "." "01" right )} {} (b) 18 . 7 2 18 . 7 2 size 12{ left ("18" "." 7 right ) rSup { size 8{2} } } {} (c) 1 . 60 × 10 − 19 3712 1 . 60 × 10 − 19 3712 size 12{ left (1 "." "60" times "10" rSup { size 8{ - "19"} } right ) left ("3712" right )} {} .

(a) How many significant figures are in the numbers 99 and 100? (b) If the uncertainty in each number is 1, what is the percent uncertainty in each? (c) Which is a more meaningful way to express the accuracy of these two numbers, significant figures or percent uncertainties?

(a) If your speedometer has an uncertainty of 2 . 0 km/h 2 . 0 km/h size 12{2 "." 0" km/h"} {} at a speed of 90 km/h 90 km/h size 12{"90"" km/h"} {} , what is the percent uncertainty? (b) If it has the same percent uncertainty when it reads 60 km/h 60 km/h size 12{"60"" km/h"} {} , what is the range of speeds you could be going?

(a) A person’s blood pressure is measured to be 120 ± 2 mm Hg 120 ± 2 mm Hg size 12{"120" +- 2" mm Hg"} {} . What is its percent uncertainty? (b) Assuming the same percent uncertainty, what is the uncertainty in a blood pressure measurement of 80 mm Hg 80 mm Hg size 12{"80"" mm Hg"} {} ?

A person measures his or her heart rate by counting the number of beats in 30 s 30 s size 12{"30"" s"} {} . If 40 ± 1 40 ± 1 size 12{"40" +- 1} {} beats are counted in 30 . 0 ± 0 . 5 s 30 . 0 ± 0 . 5 s size 12{"30" "." 0 +- 0 "." 5" s"} {} , what is the heart rate and its uncertainty in beats per minute?

What is the area of a circle 3 . 102 cm 3 . 102 cm size 12{3 "." "102"" cm"} {} in diameter?

If a marathon runner averages 9.5 mi/h, how long does it take him or her to run a 26.22-mi marathon?

A marathon runner completes a 42 . 188 -km 42 . 188 -km size 12{"42" "." "188""-km"} {} course in 2 h 2 h size 12{2" h"} {} , 30 min, and 12 s 12 s size 12{"12"" s"} {} . There is an uncertainty of 25 m 25 m size 12{"25"" m"} {} in the distance traveled and an uncertainty of 1 s in the elapsed time. (a) Calculate the percent uncertainty in the distance. (b) Calculate the uncertainty in the elapsed time. (c) What is the average speed in meters per second? (d) What is the uncertainty in the average speed?

The sides of a small rectangular box are measured to be 1 . 80 ± 0 . 01 cm 1 . 80 ± 0 . 01 cm size 12{1 "." "80" +- 0 "." "01"" cm"} {} , {} 2 . 05 ± 0 . 02 cm, and 3 . 1 ± 0 . 1 cm 2 . 05 ± 0 . 02 cm, and 3 . 1 ± 0 . 1 cm size 12{2 "." "05" +- 0 "." "02"" cm, and 3" "." 1 +- 0 "." "1 cm"} {} long. Calculate its volume and uncertainty in cubic centimeters.

When non-metric units were used in the United Kingdom, a unit of mass called the pound-mass (lbm) was employed, where 1 lbm = 0 . 4539 kg 1 lbm = 0 . 4539 kg size 12{1" lbm"=0 "." "4539"`"kg"} {} . (a) If there is an uncertainty of 0 . 0001 kg 0 . 0001 kg size 12{0 "." "0001"`"kg"} {} in the pound-mass unit, what is its percent uncertainty? (b) Based on that percent uncertainty, what mass in pound-mass has an uncertainty of 1 kg when converted to kilograms?

The length and width of a rectangular room are measured to be 3 . 955 ± 0 . 005 m 3 . 955 ± 0 . 005 m size 12{3 "." "955" +- 0 "." "005"" m"} {} and 3 . 050 ± 0 . 005 m 3 . 050 ± 0 . 005 m size 12{3 "." "050" +- 0 "." "005"" m"} {} . Calculate the area of the room and its uncertainty in square meters.

A car engine moves a piston with a circular cross section of 7 . 500 ± 0 . 002 cm 7 . 500 ± 0 . 002 cm size 12{7 "." "500" +- 0 "." "002"`"cm"} {} diameter a distance of 3 . 250 ± 0 . 001 cm 3 . 250 ± 0 . 001 cm size 12{3 "." "250" +- 0 "." "001"`"cm"} {} to compress the gas in the cylinder. (a) By what amount is the gas decreased in volume in cubic centimeters? (b) Find the uncertainty in this volume.

1.4 Approximation

How many heartbeats are there in a lifetime?

A generation is about one-third of a lifetime. Approximately how many generations have passed since the year 0 AD?

How many times longer than the mean life of an extremely unstable atomic nucleus is the lifetime of a human? (Hint: The lifetime of an unstable atomic nucleus is on the order of 10 − 22  s 10 − 22  s size 12{"10" rSup { size 8{ - "22"} } " s"} {} .)

Calculate the approximate number of atoms in a bacterium. Assume that the average mass of an atom in the bacterium is ten times the mass of a hydrogen atom. (Hint: The mass of a hydrogen atom is on the order of 10 − 27  kg 10 − 27  kg size 12{"10" rSup { size 8{ - "27"} } " kg"} {} and the mass of a bacterium is on the order of 10 − 15  kg. 10 − 15  kg. size 12{"10" rSup { size 8{ - "15"} } "kg"} {} )

Approximately how many atoms thick is a cell membrane, assuming all atoms there average about twice the size of a hydrogen atom?

(a) What fraction of Earth’s diameter is the greatest ocean depth? (b) The greatest mountain height?

(a) Calculate the number of cells in a hummingbird assuming the mass of an average cell is ten times the mass of a bacterium. (b) Making the same assumption, how many cells are there in a human?

Assuming one nerve impulse must end before another can begin, what is the maximum firing rate of a nerve in impulses per second?

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Sat / act prep online guides and tips, the 5 best homework help websites (free and paid).

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Listen: we know homework isn’t fun, but it is a good way to reinforce the ideas and concepts you’ve learned in class. But what if you’re really struggling with your homework assignments? 

If you’ve looked online for a little extra help with your take-home assignments, you’ve probably stumbled across websites claiming to provide the homework help and answers students need to succeed . But can homework help sites really make a difference? And if so, which are the best homework help websites you can use? 

Below, we answer these questions and more about homework help websites–free and paid. We’ll go over: 

• The basics of homework help websites 
• The cost of homework help websites 
• The five best homework websites out there 
• The pros and cons of using these websites for homework help 
• The line between “learning” and “cheating” when using online homework help 
• Tips for getting the most out of a homework help website

So let’s get started! 

The Basics About Homework Help Websites–Free and Paid

Homework help websites are designed to help you complete your homework assignments, plain and simple. 

What Makes a Homework Help Site Worth Using

Most of the best sites allow users to ask questions and then provide an answer (or multiple possible answers) and explanation in seconds. In some instances, you can even send a photo of a particular assignment or problem instead of typing the whole thing out! 

Homework help sites also offer more than just help answering homework questions. Common services provided are Q&A with experts, educational videos, lectures, practice tests and quizzes, learning modules, math solving tools, and proofreading help. Homework help sites can also provide textbook solutions (i.e. answers to problems in tons of different textbooks your school might be using), one-on-one tutoring, and peer-to-peer platforms that allow you to discuss subjects you’re learning about with your fellow students. 

And best of all, nearly all of them offer their services 24/7, including tutoring! 

What You Should Should Look Out For

When it comes to homework help, there are lots–and we mean lots –of scam sites out there willing to prey on desperate students. Before you sign up for any service, make sure you read reviews to ensure you’re working with a legitimate company. 

A word to the wise: the more a company advertises help that veers into the territory of cheating, the more likely it is to be a scam. The best homework help websites are going to help you learn the concepts you’ll need to successfully complete your homework on your own. (We’ll go over the difference between “homework help” and “cheating” a little later!) 

You don't need a golden piggy bank to use homework help websites. Some provide low or no cost help for students like you!

How Expensive Are the Best Homework Help Websites?

First of all, just because a homework help site costs money doesn’t mean it’s a good service. Likewise, just because a homework help website is free doesn’t mean the help isn’t high quality. To find the best websites, you have to take a close look at the quality and types of information they provide! 

When it comes to paid homework help services, the prices vary pretty widely depending on the amount of services you want to subscribe to. Subscriptions can cost anywhere from $2 to $150 dollars per month, with the most expensive services offering several hours of one-on-one tutoring with a subject expert per month.

The 5 Best Homework Help Websites 

So, what is the best homework help website you can use? The answer is that it depends on what you need help with. 

The best homework help websites are the ones that are reliable and help you learn the material. They don’t just provide answers to homework questions–they actually help you learn the material. 

That’s why we’ve broken down our favorite websites into categories based on who they’re best for . For instance, the best website for people struggling with math might not work for someone who needs a little extra help with science, and vice versa. 

Keep reading to find the best homework help website for you! 

Best Free Homework Help Site: Khan Academy

• Price: Free!
• Best for: Practicing tough material 

Not only is Khan Academy free, but it’s full of information and can be personalized to suit your needs. When you set up your account , you choose which courses you need to study, and Khan Academy sets up a personal dashboard of instructional videos, practice exercises, and quizzes –with both correct and incorrect answer explanations–so you can learn at your own pace. 

As an added bonus, it covers more course topics than many other homework help sites, including several AP classes.

Runner Up: Brainly.com offers a free service that allows you to type in questions and get answers and explanations from experts. The downside is that you’re limited to two answers per question and have to watch ads. 

Best Paid Homework Help Site: Chegg

• Price: $14.95 to $19.95 per month
• Best for: 24/7 homework assistance  

This service has three main parts . The first is Chegg Study, which includes textbook solutions, Q&A with subject experts, flashcards, video explanations, a math solver, and writing help. The resources are thorough, and reviewers state that Chegg answers homework questions quickly and accurately no matter when you submit them.  

Chegg also offers textbook rentals for students who need access to textbooks outside of their classroom. Finally, Chegg offers Internship and Career Advice for students who are preparing to graduate and may need a little extra help with the transition out of high school. 

Another great feature Chegg provides is a selection of free articles geared towards helping with general life skills, like coping with stress and saving money. Chegg’s learning modules are comprehensive, and they feature solutions to the problems in tons of different textbooks in a wide variety of subjects. 

Runner Up: Bartleby offers basically the same services as Chegg for $14.99 per month. The reason it didn’t rank as the best is based on customer reviews that say user questions aren’t answered quite as quickly on this site as on Chegg. Otherwise, this is also a solid choice!

Best Site for Math Homework Help: Photomath

• Price: Free (or $59.99 per year for premium services) 
• Best for: Explaining solutions to math problems

This site allows you to t ake a picture of a math problem, and instantly pulls up a step-by-step solution, as well as a detailed explanation of the concept. Photomath also includes animated videos that break down mathematical concepts to help you better understand and remember them. 

The basic service is free, but for an additional fee you can get extra study tools and learn additional strategies for solving common math problems.

Runner Up: KhanAcademy offers in-depth tutorials that cover complex math topics for free, but you won’t get the same tailored help (and answers!) that Photomath offers. 

Best Site for English Homework Help: Princeton Review Academic Tutoring

• Price: $40 to $153 per month, depending on how many hours of tutoring you want 
• Best for: Comprehensive and personalized reading and writing help 

While sites like Grammarly and Sparknotes help you by either proofreading what you write via an algorithm or providing book summaries, Princeton Review’s tutors provide in-depth help with vocabulary, literature, essay writing and development, proofreading, and reading comprehension. And unlike other services, you’ll have the chance to work with a real person to get help. 

The best part is that you can get on-demand English (and ESL) tutoring from experts 24/7. That means you can get help whenever you need it, even if you’re pulling an all-nighter! 

This is by far the most expensive homework site on this list, so you’ll need to really think about what you need out of a homework help website before you commit. One added benefit is that the subscription covers over 80 other subjects, including AP classes, which can make it a good value if you need lots of help!  

Best Site for STEM Homework Help: Studypool

• Best for: Science homework help
• Price: Varies; you’ll pay for each question you submit

When it comes to science homework help, there aren’t a ton of great resources out there. The best of the bunch is Studypool, and while it has great reviews, there are some downsides as well. 

Let’s start with the good stuff. Studypool offers an interesting twist on the homework help formula. After you create a free account, you can submit your homework help questions, and tutors will submit bids to answer your questions. You’ll be able to select the tutor–and price point–that works for you, then you’ll pay to have your homework question answered. You can also pay a small fee to access notes, lectures, and other documents that top tutors have uploaded. 

The downside to Studypool is that the pricing is not transparent . There’s no way to plan for how much your homework help will cost, especially if you have lots of questions! Additionally, it’s not clear how tutors are selected, so you’ll need to be cautious when you choose who you’d like to answer your homework questions.  

What Are the Pros and Cons of Using Homework Help Sites?

Homework help websites can be a great resource if you’re struggling in a subject, or even if you just want to make sure that you’re really learning and understanding topics and ideas that you’re interested in. But, there are some possible drawbacks if you don’t use these sites responsibly. 

We’ll go over the good–and the not-so-good–aspects of getting online homework help below. 

3 Pros of Using Homework Help Websites 

First, let’s take a look at the benefits. 

#1: Better Grades Beyond Homework

This is a big one! Getting outside help with your studies can improve your understanding of concepts that you’re learning, which translates into better grades when you take tests or write essays. 

Remember: homework is designed to help reinforce the concepts you learned in class. If you just get easy answers without learning the material behind the problems, you may not have the tools you need to be successful on your class exams…or even standardized tests you’ll need to take for college. 

#2: Convenience

One of the main reasons that online homework help is appealing is because it’s flexible and convenient. You don’t have to go to a specific tutoring center while they’re open or stay after school to speak with your teacher. Instead, you can access helpful resources wherever you can access the internet, whenever you need them.

This is especially true if you tend to study at off hours because of your extracurriculars, work schedule, or family obligations. Sites that offer 24/7 tutoring can give you the extra help you need if you can’t access the free resources that are available at your school. 

#3: Variety

Not everyone learns the same way. Maybe you’re more of a visual learner, but your teacher mostly does lectures. Or maybe you learn best by listening and taking notes, but you’re expected to learn something just from reading the textbook . 

One of the best things about online homework help is that it comes in a variety of forms. The best homework help sites offer resources for all types of learners, including videos, practice activities, and even one-on-one discussions with real-life experts. 

This variety can also be a good thing if you just don’t really resonate with the way a concept is being explained (looking at you, math textbooks!).

Not so fast. There are cons to homework help websites, too. Get to know them below!

3 Cons of Using Homework Help Websites 

Now, let’s take a look at the drawbacks of online homework help. 

#1: Unreliable Info

This can be a real problem. In addition to all the really good homework help sites, there are a whole lot of disreputable or unreliable sites out there. The fact of the matter is that some homework help sites don’t necessarily hire people who are experts in the subjects they’re talking about. In those cases, you may not be getting the accurate, up-to-date, and thorough information you need.

Additionally, even the great sites may not be able to answer all of your homework questions. This is especially true if the site uses an algorithm or chatbot to help students…or if you’re enrolled in an advanced or college-level course. In these cases, working with your teacher or school-provided tutors are probably your best option. 

#2: No Clarification

This depends on the service you use, of course. But the majority of them provide free or low-cost help through pre-recorded videos. Watching videos or reading info online can definitely help you with your homework… but you can’t ask questions or get immediate feedback if you need it .

#3: Potential For Scamming 

Like we mentioned earlier, there are a lot of homework help websites out there, and lots of them are scams. The review comments we read covered everything from outdated or wrong information, to misleading claims about the help provided, to not allowing people to cancel their service after signing up. 

No matter which site you choose to use, make sure you research and read reviews before you sign up–especially if it’s a paid service! 

When Does “Help” Become “Cheating”?

Admittedly, whether using homework help websites constitutes cheating is a bit of a grey area. For instance, is it “help” when a friend reads your essay for history class and corrects your grammar, or is it “cheating”? The truth is, not everyone agrees on when “help” crosses the line into “cheating .” When in doubt, it can be a good idea to check with your teacher to see what they think about a particular type of help you want to get. 

That said, a general rule of thumb to keep in mind is to make sure that the assignment you turn in for credit is authentically yours . It needs to demonstrate your own thoughts and your own current abilities. Remember: the point of every homework assignment is to 1) help you learn something, and 2) show what you’ve learned. 

So if a service answers questions or writes essays for you, there’s a good chance using it constitutes cheating. 

Here’s an example that might help clarify the difference for you. Brainstorming essay ideas with others or looking online for inspiration is “help” as long as you write the essay yourself. Having someone read it and give you feedback about what you need to change is also help, provided you’re the one that makes the changes later. 

But copying all or part of an essay you find online or having someone write (or rewrite) the whole thing for you would be “cheating.” The same is true for other subjects. Ultimately, if you’re not generating your own work or your own answers, it’s probably cheating.

5 Tips for Finding the Best Homework Help Websites for You

Now that you know some of our favorite homework help websites, free and paid, you can start doing some additional research on your own to decide which services might work best for you! Here are some top tips for choosing a homework help website. 

Tip 1: Decide How You Learn Best 

Before you decide which site or sites you’re going to use for homework help, y ou should figure out what kind of learning style works for you the most. Are you a visual learner? Then choose a site that uses lots of videos to help explain concepts. If you know you learn best by actually doing tasks, choose a site that provides lots of practice exercises.

Tip 2: Determine Which Subjects You Need Help With

Just because a homework help site is good overall doesn’t mean that it’s equally good for every subject. If you only need help in math, choose a site that specializes in that area. But if history is where you’re struggling, a site that specializes in math won’t be much help. So make sure to choose a site that you know provides high-quality help in the areas you need it most. 

Tip 3: Decide How Much One-On-One Help You Need 

This is really about cost-effectiveness. If you learn well on your own by reading and watching videos, a free site like Khan Academy is a good choice. But if you need actual tutoring, or to be able to ask questions and get personalized answers from experts, a paid site that provides that kind of service may be a better option.

Tip 4: Set a Budget 

If you decide you want to go with a paid homework help website, set a budget first . The prices for sites vary wildly, and the cost to use them can add up quick. 

Tip 5: Read the Reviews

Finally, it’s always a good idea to read actual reviews written by the people using these homework sites. You’ll learn the good, the bad, and the ugly of what the users’ experiences have been. This is especially true if you intend to subscribe to a paid service. You’ll want to make sure that users think it’s worth the price overall!

What’s Next?

If you want to get good grades on your homework, it’s a good idea to learn how to tackle it strategically. Our expert tips will help you get the most out of each assignment…and boost your grades in the process. 

Doing well on homework assignments is just one part of getting good grades. We’ll teach you everything you need to know about getting great grades in high school in this article. 

Of course, test grades can make or break your GPA, too. Here are 17 expert tips that’ll help you get the most out of your study prep before you take an exam. 

Need more help? Check out Tutorbase!

Our vetted tutor database includes a range of experienced educators who can help you polish an essay for English or explain how derivatives work for Calculus. You can use dozens of filters and search criteria to find the perfect person for your needs.

Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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Our name 24HourAnswers means you can submit work 24 hours a day - it doesn't mean we can help you master what you need to know in 24 hours. If you make arrangements in advance, and if you are a very fast learner, then yes, we may be able to help you achieve your goals in 24 hours. Remember, high quality, customized help that's tailored around the needs of each individual student takes time to achieve. You deserve nothing less than the best, so give us the time we need to give you the best.

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Structural engineering is a specialization in civil engineering . The main operational domains of structural engineering are analysis of the structural frameworks and designing of structures to withstand operational stresses and pressures. The key objectives of optimum design are keeping structures and the environment safe and secure during their entire life period, considering all the possible eventual environmental influences during the lifetime of the structure. Structural engineering can be considered one of the oldest engineering divisions, existing since prehistoric times: it has become much more sophisticated in the current era, of course, and is still developing. Structural engineering applications have become interdisciplinary, with several types of equipment used in medical applications being based on the principles of structural engineering.  Gustave Eiffel  and  Eero Saarinen are two of the most famous structural engineers of all time, remembered for their valuable contributions to the world.

Structural engineering graduates typically study advanced mathematical methods, concrete analysis, steel structures, structural dynamics, elasticity and plasticity theories, finite element analysis, external force (such as earthquake analysis) on structural integrity, study of experimental techniques and methods for structural analysis as well as instrumentation tools for structural analysis. Structural engineering spans from nano-scale constructions to those of mega-scale.

Apart from required courses, most structural engineering majors may choose from electives in bridge structural studies, maintenance and rehabilitation of structures, offshore structures, optimization of structural designs, advanced concrete technology, prestressed concrete , sub structural design, composite material mechanics, CAD, shell and spatial structures, or the stability of structures are often studied as special electives in structural engineering courses.  Recent research trends in structural engineering include fracture and damage mechanics , the application of neural networks, random vibrations and chaos, and structural reliability studies.

Structural engineers often find careers in the construction industry; apart from that, careers in specialized streams such as mechanical structures and industrial structural design and development are some of the popular career destinations for specialized structural engineers. In addition to the needs of interdisciplinary knowledge and a command of the basics of engineering, structural engineers must have a thorough knowledge of the prevailing codes and standards of building and non-structural elements in industry. From the identification of environmentally friendly novel structural materials, to working out new short- and long-term solutions to sustainable engineering problems continue to be major challenges for structural engineers. Structural engineering has immense scope to meet the demands of the modern world, supplying better designs that consume less material with reduced environmental impact and minimal  life cycle costs .  Knowledge of better structural materials, computer skills and proficiency with advanced design tools are all demanded of graduate engineers.

SE ,  IJCE ,  SEI ,  IJCER ,  IJASE are some journals sources offering valuable information on developments in contemporary structural engineering.

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Batten College Professor Co-Authors Book on Trustworthy AI

Murat Kuzlu, associate professor in the Department of Engineering Technology, recently co-authored a book titled, “ Trustworthy AI: From Theory to Practice.”

Tailored for artificial intelligence (AI) developers, researchers and end-users, the book offers theoretical insights and practical guidance for building, deploying and testing trustworthy AI models.

Kuzlu and co-author, Ferhat Ozgur Catak, an associate professor at the University of Stavanger, Norway, discuss the use of artificial intelligence across various fields, in particular, academia and industry, and the challenges related to the trustworthiness of AI systems in terms of reliability, fairness, transparency, privacy and security.

“In this book, we aim to bridge the gap between theoretical concepts of trustworthy AI, along with sharing their practical applications using Python and open-source libraries,” Kuzlu explained. The open-source code is published on GitHub.

The methodology is accessible to anyone with an understanding of fundamental AI concepts and programming skills, particularly in Python. Kuzlu recommends familiarity with open-source libraries relevant to AI development as well.

Kuzlu is optimistic about its future of trustworthy AI. “I believe we can collectively form a future where AI technologies are not only powerful and efficient but also ethical, fair, and responsible, ultimately benefiting society,” he said.

Kuzlu joined Old Dominion University in 2018. His expertise lies in cyber-physical systems, smart systems, artificial intelligence, trustworthy AI, and next-generation networks.

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Zand pursues a passion for research

Working on research projects, teaching and mentoring was initially not part of the plan for Computer Science and Engineering Assistant Professor Ramtin Zand . But it while working as a consultant for a startup company in Iran that he discovered more of an interest in research rather than industry. 

Zand’s interest in engineering was a combination of enjoying math in high school and applied, hands-on projects. Even though he earned his bachelor’s and master’s degrees in electrical engineering, most of his work was focused on computer hardware design. 

“I knew that fields like computer science and electrical engineering were where you could apply mathematical knowledge. I was excited about going in that direction because I knew the combination of liking math and project building would be interesting,” Zand says. 

Zand considered a career in academia because he was familiar with industry and wanted to innovate and have more freedom to work on projects. He moved to the U.S. and earned his Ph.D. in computer engineering from the University of Central Florida, where he took advantage of every opportunity to teach a course or lab. 

“My advisor, Dr. Ronald DeMara , was very supportive and he trained us to be professors. This was a dream opportunity after all my industry experience,” Zand says.

Zand’s research interests go back to his enjoyment of math and hands-on projects. He is director of the Intelligent Circuits, Architectures and Systems ( iCAS ) Lab. Zand’s team works on projects related to areas such as hardware, software and artificial intelligence. The iCAS Lab’s goal is to create smaller, faster and smarter computing systems to use in real-world applications without relying on large servers. 

“I was always excited about theory and practical projects coming together, and that's what I'm doing now,” Zand says. “I like building systems that are useful and thought it would be interesting to bring an AI model to small devices. If we do that, then it can have a variety of uses because many applications need tiny devices connected to their systems. That was the vision for my lab.” 

Contributing to Zand’s primary goal for the iCAS Lab are the other research focuses : neuromorphic computing, edge computing, in-memory processing and hardware design for AI. 

“We try to solve problems in different ways, which is why we use the term heterogeneous, which means there is more than one solution. It’s a combination of solutions coming together to build a useful computing system,” Zand says.

Neuromorphic computing uses specialized hardware, such as AI chips and software algorithms, to simulate how the brain works to process data more efficiently. Some of his current projects include hand gesture recognition for American Sign Language. 

“Neuromorphic combines machine learning and neuroscience. The idea is that if you make AI systems more inspired by the brain, there are benefits such as capturing temporal information, which are signals or data that is related to time,” Zand says. “Another benefit is event-based operation for battery-powered devices, which we want to run longer, so it conserves power by only processing data that's important.”

Edge computing refers to making more efficient machine learning models that can run on tiny devices. Zand has been working in this area since he started the iCAS Lab. One of the current projects is facial expression recognition using smaller neural networks and AI devices.

I like theoretical work, but to me, it's about bringing theory and application together. - Ramtin Zand 

In addition, Zand and his team’s work related to in-memory processing aims to construct a heterogeneous computer architecture to reduce the data movement between the memory and processor. Future projects include combining neuromorphic and edge computing for real time machine learning technology, which will build on current research. 

“I think we have the foundation right now in terms of the skills needed in the lab to do these projects. My graduate students are brilliant and have the skills to develop these projects going forward,” Zand says. “We are excited that we'll have technologies that will be used in real world applications and are not just theoretical.” 

Combined with research, Zand says that teaching and mentoring is one of the most satisfying aspects of his job. Over time, he sees changes and how students eventually contribute. 

“I'm open to having undergraduate and graduate students without much research experience work for me. However, I have expectations and want them to be serious and disciplined about their work,” Zand says. “It's rewarding because of the impact I have in their lives and their contributions. I’ve learned a lot from them, and they make the lab a better place.”

Computer Engineering Ph.D. candidate Peyton Chandarana is a member of Zand’s research team and one of his mentees. He describes Zand as a monumental mentor in helping him inside and outside the lab to succeed in academic and research settings.

“He strives to be a great academic advisor and goes above and beyond to help his students challenge themselves and become the best versions of themselves,” Chandarana says. “I remember a specific quote when I first met him while taking his neuromorphic computing class. It was: ‘When you encounter challenges, enjoy the process of those challenges and enjoy the journey they take you on.’”

Zand believes that research and teaching are connected because he works on projects that are enjoyable, while mentoring students who are passionate about learning and research. In both aspects, he can have impacts to better the lives of students and society.

“I like theoretical work, but to me, it's about bringing theory and application together. I have a rule with the students in my team that they must demonstrate their work so people can relate to it,” Zand says. “Research is supposed to change. If not, then it’s either not being done correctly or it is irrelevant.”

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Universities Have a Computer-Science Problem

The case for teaching coders to speak French

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Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

Updated at 5:37 p.m. ET on March 22, 2024

Last year, 18 percent of Stanford University seniors graduated with a degree in computer science, more than double the proportion of just a decade earlier. Over the same period at MIT, that rate went up from 23 percent to 42 percent . These increases are common everywhere: The average number of undergraduate CS majors at universities in the U.S. and Canada tripled in the decade after 2005, and it keeps growing . Students’ interest in CS is intellectual—culture moves through computation these days—but it is also professional. Young people hope to access the wealth, power, and influence of the technology sector.

That ambition has created both enormous administrative strain and a competition for prestige. At Washington University in St. Louis, where I serve on the faculty of the Computer Science & Engineering department, each semester brings another set of waitlists for enrollment in CS classes. On many campuses, students may choose to study computer science at any of several different academic outposts, strewn throughout various departments. At MIT, for example, they might get a degree in “Urban Studies and Planning With Computer Science” from the School of Architecture, or one in “Mathematics With Computer Science” from the School of Science, or they might choose from among four CS-related fields within the School of Engineering. This seepage of computing throughout the university has helped address students’ booming interest, but it also serves to bolster their demand.

Another approach has gained in popularity. Universities are consolidating the formal study of CS into a new administrative structure: the college of computing. MIT opened one in 2019. Cornell set one up in 2020. And just last year, UC Berkeley announced that its own would be that university’s first new college in more than half a century. The importance of this trend—its significance for the practice of education, and also of technology—must not be overlooked. Universities are conservative institutions, steeped in tradition. When they elevate computing to the status of a college, with departments and a budget, they are declaring it a higher-order domain of knowledge and practice, akin to law or engineering. That decision will inform a fundamental question: whether computing ought to be seen as a superfield that lords over all others, or just a servant of other domains, subordinated to their interests and control. This is, by no happenstance, also the basic question about computing in our society writ large.

When I was an undergraduate at the University of Southern California in the 1990s, students interested in computer science could choose between two different majors: one offered by the College of Letters, Arts and Sciences, and one from the School of Engineering. The two degrees were similar, but many students picked the latter because it didn’t require three semesters’ worth of study of a (human) language, such as French. I chose the former, because I like French.

An American university is organized like this, into divisions that are sometimes called colleges , and sometimes schools . These typically enjoy a good deal of independence to define their courses of study and requirements as well as research practices for their constituent disciplines. Included in this purview: whether a CS student really needs to learn French.

The positioning of computer science at USC was not uncommon at the time. The first academic departments of CS had arisen in the early 1960s, and they typically evolved in one of two ways: as an offshoot of electrical engineering (where transistors got their start), housed in a college of engineering; or as an offshoot of mathematics (where formal logic lived), housed in a college of the arts and sciences. At some universities, including USC, CS found its way into both places at once.

The contexts in which CS matured had an impact on its nature, values, and aspirations. Engineering schools are traditionally the venue for a family of professional disciplines, regulated with licensure requirements for practice. Civil engineers, mechanical engineers, nuclear engineers, and others are tasked to build infrastructure that humankind relies on, and they are expected to solve problems. The liberal-arts field of mathematics, by contrast, is concerned with theory and abstraction. The relationship between the theoretical computer scientists in mathematics and the applied ones in engineers is a little like the relationship between biologists and doctors, or physicists and bridge builders. Keeping applied and pure versions of a discipline separate allows each to focus on its expertise, but limits the degree to which one can learn from the other.

Read: Programmers, stop calling yourself engineers

By the time I arrived at USC, some universities had already started down a different path. In 1988, Carnegie Mellon University created what it says was one of the first dedicated schools of computer science. Georgia Institute of Technology followed two years later. “Computing was going to be a big deal,” says Charles Isbell, a former dean of Georgia Tech’s college of computing and now the provost at the University of Wisconsin-Madison. Emancipating the field from its prior home within the college of engineering gave it room to grow, he told me. Within a decade, Georgia Tech had used this structure to establish new research and teaching efforts in computer graphics, human-computer interaction, and robotics. (I spent 17 years on the faculty there, working for Isbell and his predecessors, and teaching computational media.)

Kavita Bala, Cornell University’s dean of computing, told me that the autonomy and scale of a college allows her to avoid jockeying for influence and resources. MIT’s computing dean, Daniel Huttenlocher, says that the speed at which computing evolves justifies the new structure.

But the computing industry isn’t just fast-moving. It’s also reckless. Technology tycoons say they need space for growth, and warn that too much oversight will stifle innovation. Yet we might all be better off, in certain ways, if their ambitions were held back even just a little. Instead of operating with a deep understanding or respect for law, policy, justice, health, or cohesion, tech firms tend to do whatever they want . Facebook sought growth at all costs, even if its take on connecting people tore society apart . If colleges of computing serve to isolate young, future tech professionals from any classrooms where they might imbibe another school’s culture and values—engineering’s studied prudence, for example, or the humanities’ focus on deliberation—this tendency might only worsen.

Read: The moral failure of computer scientists

When I raised this concern with Isbell, he said that the same reasoning could apply to any influential discipline, including medicine and business. He’s probably right, but that’s cold comfort. The mere fact that universities allow some other powerful fiefdoms to exist doesn’t make computing’s centralization less concerning. Isbell admitted that setting up colleges of computing “absolutely runs the risk” of empowering a generation of professionals who may already be disengaged from consequences to train the next one in their image. Inside a computing college, there may be fewer critics around who can slow down bad ideas. Disengagement might redouble. But he said that dedicated colleges could also have the opposite effect. A traditional CS department in a school of engineering would be populated entirely by computer scientists, while the faculty for a college of computing like the one he led at Georgia Tech might also house lawyers, ethnographers, psychologists, and even philosophers like me. Huttenlocher repeatedly emphasized that the role of the computing college is to foster collaboration between CS and other disciplines across the university. Bala told me that her college was established not to teach CS on its own but to incorporate policy, law, sociology, and other fields into its practice. “I think there are no downsides,” she said.

Mark Guzdial is a former faculty member in Georgia Tech’s computing college, and he now teaches computer science in the University of Michigan’s College of Engineering. At Michigan, CS wasn’t always housed in engineering—Guzdial says it started out inside the philosophy department, as part of the College of Literature, Science and the Arts. Now that college “wants it back,” as one administrator told Guzdial. Having been asked to start a program that teaches computing to liberal-arts students, Guzdial has a new perspective on these administrative structures. He learned that Michigan’s Computer Science and Engineering program and its faculty are “despised” by their counterparts in the humanities and social sciences. “They’re seen as arrogant, narrowly focused on machines rather than people, and unwilling to meet other programs’ needs,” he told me. “I had faculty refuse to talk to me because I was from CSE.”

In other words, there may be downsides just to placing CS within an engineering school, let alone making it an independent college. Left entirely to themselves, computer scientists can forget that computers are supposed to be tools that help people. Georgia Tech’s College of Computing worked “because the culture was always outward-looking. We sought to use computing to solve others’ problems,” Guzdial said. But that may have been a momentary success. Now, at Michigan, he is trying to rebuild computing education from scratch, for students in fields such as French and sociology. He wants them to understand it as a means of self-expression or achieving justice—and not just a way of making software, or money.

Early in my undergraduate career, I decided to abandon CS as a major. Even as an undergraduate, I already had a side job in what would become the internet industry, and computer science, as an academic field, felt theoretical and unnecessary. Reasoning that I could easily get a job as a computer professional no matter what it said on my degree, I decided to study other things while I had the chance.

I have a strong memory of processing the paperwork to drop my computer-science major in college, in favor of philosophy. I walked down a quiet, blue-tiled hallway of the engineering building. All the faculty doors were closed, although the click-click of mechanical keyboards could be heard behind many of them. I knocked on my adviser’s door; she opened it, silently signed my paperwork without inviting me in, and closed the door again. The keyboard tapping resumed.

The whole experience was a product of its time, when computer science was a field composed of oddball characters, working by themselves, and largely disconnected from what was happening in the world at large. Almost 30 years later, their projects have turned into the infrastructure of our daily lives. Want to find a job? That’s LinkedIn. Keep in touch? Gmail, or Instagram. Get news? A website like this one, we hope, but perhaps TikTok. My university uses a software service sold by a tech company to run its courses. Some things have been made easier with computing. Others have been changed to serve another end, like scaling up an online business.

Read: So much for ‘learn to code’

The struggle to figure out the best organizational structure for computing education is, in a way, a microcosm of the struggle under way in the computing sector at large. For decades, computers were tools used to accomplish tasks better and more efficiently. Then computing became the way we work and live. It became our culture, and we began doing what computers made possible, rather than using computers to solve problems defined outside their purview. Tech moguls became famous, wealthy, and powerful. So did CS academics (relatively speaking). The success of the latter—in terms of rising student enrollments, research output, and fundraising dollars—both sustains and justifies their growing influence on campus.

If computing colleges have erred, it may be in failing to exert their power with even greater zeal. For all their talk of growth and expansion within academia, the computing deans’ ambitions seem remarkably modest. Martial Hebert, the dean of Carnegie Mellon’s computing school, almost sounded like he was talking about the liberal arts when he told me that CS is “a rich tapestry of disciplines” that “goes far beyond computers and coding.” But the seven departments in his school correspond to the traditional, core aspects of computing plus computational biology. They do not include history, for example, or finance. Bala and Isbell talked about incorporating law, policy, and psychology into their programs of study, but only in the form of hiring individual professors into more traditional CS divisions. None of the deans I spoke with aspires to launch, say, a department of art within their college of computing, or one of politics, sociology, or film. Their vision does not reflect the idea that computing can or should be a superordinate realm of scholarship, on the order of the arts or engineering. Rather, they are proceeding as though it were a technical school for producing a certain variety of very well-paid professionals. A computing college deserving of the name wouldn’t just provide deeper coursework in CS and its closely adjacent fields; it would expand and reinvent other, seemingly remote disciplines for the age of computation.

Near the end of our conversation, Isbell mentioned the engineering fallacy, which he summarized like this: Someone asks you to solve a problem, and you solve it without asking if it’s a problem worth solving. I used to think computing education might be stuck in a nesting-doll version of the engineer’s fallacy, in which CS departments have been asked to train more software engineers without considering whether more software engineers are really what the world needs. Now I worry that they have a bigger problem to address: how to make computer people care about everything else as much as they care about computers.

This article originally mischaracterized the views of MIT’s computing dean, Daniel Huttenlocher. He did not say that computer science would be held back in an arts-and-science or engineering context, or that it needs to be independent.

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What are the top Universities in Moscow? uniRank answers this question by publishing the 2024 uniRank University Ranking of 66 Moscow higher-education institutions meeting the following uniRank selection criteria:

• being chartered, licensed or accredited by the appropriate Russian higher education-related organization
• offering at least three-year bachelor's degrees or postgraduate master's or doctoral degrees
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uniRank aims to provide a non-academic League Table of the top Moscow Universities based on valid, unbiased and non-influenceable web metrics provided by independent web intelligence sources rather than data submitted by the Universities themselves.

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Dean of College of Engineering at UToledo resigns following Title IX investigation

TOLEDO, Ohio (WTVG) - The Dean of the College of Engineering at the University of Toledo has resigned, according to the university.

UToledo says T. Michael Toole resigned on March 18 following a Title IX investigation. Toole had served as the dean of the College of Engineering since August of 2017.

“The University of Toledo is committed to maintaining a safe and welcoming campus environment for everyone and we expect our leaders to adhere to the highest standards,” said UToledo. “We take all reports of harassment seriously and investigate and act in accordance with the law.”

According to UToledo, the Title IX office investigates reports of sexual misconduct, implements supportive measures when necessary and works to remedy the effects of sexual misconduct.

A spokesperson for UT confirms the case does not involve a student.

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Professor Wenchao Li Earns NSF CAREER Award

by A.J. Kleber

The National Science Foundation has presented Professor Wenchao Li with a prestigious CAREER Award for a new project which has the potential  to transform the development of AI systems.

Titled “Specification-Guided Imitation Learning,” Professor Li’s project aims to overcome fundamental challenges in Imitation Learning (IL), a powerful machine learning approach which allows AI agents to learn from “expert demonstrations,” such as videos or other recorded data of a human performing a particular task or activity. However, Professor Li notes that “in practice, human demonstrations can be inadequate, partial, imperfect, environment-specific, or suboptimal.” To address this, he proposes a novel approach which adds a “guiding framework” to IL.

One of the major areas of concern in ML is providing effective safety parameters for technologies like autonomous vehicles. Relying exclusively on demonstrated driving practices could leave critical weaknesses in such a system, because training on exclusively safe and successful scenarios fails to provide the context to recognize unsafe situations; AI systems are not well equipped to generalize to broader conditions than their training covers. At the same time, providing demonstrations addressing every potential safety risk would be highly impractical. 

To address this shortcoming, Li proposes expanding the “expert inputs” provided in IL to include formal specifications for a given task, to further define the expectations and requirements for the “learner.” By utilizing a complimentary, mathematically precise framework to clarify and provide context, Li plans to vastly improve the overall effectiveness of IL training in general. “With our new approach, we envisage that it will lead to more efficient learning algorithms, AI systems that are better aligned with users’ intents, and ultimately safer and more trustworthy autonomous systems,” Li affirms.

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Deaf high school students learn the language of coding during pilot program.

RIVERSIDE, Calif. (KABC) -- The sound barrier is not an impediment for deaf students learning the language of coding at a camp hosted by California Baptist University.

"The student will engage with their instructor but they're engaging in another language in something I don't understand and in engineering computer science is very much another language," said Phil Van Haaster, dean of the Gordon and Jill Bourns College of Engineering.

Haaster is heading up a pilot program inviting students from the California School of the Deaf in Riverside to learn coding by creating their own video game.

The eight-hour course is taught by university instructors with the help from American Sign Language interpreters, some of whom are also students with the Center for Deaf Studies.

"There is a lot of finger spelling that goes on because there is a lot of specific jargon related to computer science that we don't have signs for," said Danny Blair, director for the Center of Deaf Studies at California Baptist University.

Seven students participated in the camp where they learn to program a snake which grows as it consumes.

"So it is really great to see how they are making the background, changing colors of the snake. I'm like slow down, slow down, we have to wait for the teacher and his instructions," said Rene Visco with California School for the Deaf in Riverside.

There is a bit of learning curve, but once mastered, students are able to see their video game come to life.

"I just really love technology by doing coding. I love learning with my friends. Sometimes things go over your head but this has been great the way they break it down and explain it to us," said Darius Zarembka.

While not a summer camp spent outdoors, this camp is exposing students to the possibility of a future in computer science and engineering.

"I like learning about technology and new technology today is taking off I would like to do that kind of thing as a career," said Kaden Adam.

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The 16 worst-paying college majors, five years after graduation

Students who major in liberal arts, performing arts and theology earn the lowest salaries within five years of graduating from college, a recent New York Federal Reserve analysis reveals .

All three majors made a median annual income of $38,000, the lowest out of the 75 majors in the study. Other low-paying majors include leisure and hospitality, history, fine arts and psychology, all of which made $40,000 or less per year.

For context, that's slightly less than the U.S. personal income median of $40,480 as of 2022, per the latest data available from the U.S. Census .

Here's a look at what the lowest-paying majors earn early in their careers.

With liberal arts degrees, graduates tend to get paid less overall, for various reasons. For one, their skills may not be directly related to generating revenue, even if their vocation is a benefit to society.

Or, it can be a case of too few well-paying jobs compared with the number of graduates each year, as is the case for fine arts degrees . As such, the lack of demand can drive down wages.

Education majors tend to be paid less, as well. While teachers have good job security, summers off and pensions, they're usually paid by state governments, which have lagged in keeping wages commensurate with inflation. In recent years, the "teacher pay penalty" has gotten worse, according to the Economic Policy Institute .

Unfortunately for teachers, they don't fare much better later in their careers. When looking at "mid-career" graduates — those ages 35 to 45 — education majors are the worst paid among all majors.

Here's a look at the mid-career rankings.

Early childhood education majors in the middle of their careers earn the least out of all majors. With a median annual income of $48,000, they only make $8,000 more than they do right after graduation.

In contrast, the highest-paid majors for both early and mid-career earners tend to be in science, technology, engineering and mathematics, otherwise known as STEM fields. 

Engineers earn the highest median income right after college, with computer engineers ranked first at $80,000 per year. Their pay grows to $133,000 by the time they've reached the ages of 35 to 45, the highest of all majors.

It's worth mentioning that mid-career graduates all make more than the U.S. personal income median of $40,480. The median pay for all mid-career majors is $75,500, according to the New York Fed.

Data for this annual study was compiled from U.S. Census data from 2022, the most recent available. The study excludes majors currently enrolled in school and is limited to a working-age population of those ages 25 to 65 who work full-time, with a bachelor's degree or higher.

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