Top Ten Things That Should Be In Every Undergraduate Physics Degree CourseI recently graduated with a physics degree from one of the highest ranking universities worldwide, soon to start a PhD in galaxy data cosmology, and I must say, I have accomplished a lot in the past four years. However, I feel that a lot of my developments as a scientist had to be taken into my own hands, as a number of things were missing from my course that would have prepared even the most underachieving students for the world of scientific research. As you meet more and more people in the community of physics, you learn a lot more about the aspects of degree courses from different institutions, and there are always subtle differences that makes your programme better or worse than theirs, but these can drastically influence what one learns from the course and what abilities one develops in the field. So here are some things which would make the perfect degree course, creating the most versatile and advanced skill set that a physicist could gain. Specifically, things that are readily available at some universities but not others, thereby making a huge difference in the quality of learning.
The most outrageous aspect of my physics degree was by far the assessment of coursework, which constituted approximately a third of my total degree mark. The fact is that you have no control over who is assessing your coursework, and they have their own, independent ideas about what constitutes a good submission. This meant there was absolutely no sure-fire way to predict what you'd get back, and I, for one, quickly became sick of being swindled, and never received a shred of useful feedback which would aid my performance in future. The lack of consistency with this marking system has been a huge setback for several people, and it really isn't OK.
The solution? A clear set of rules which both the students and the assessors can follow. An honest, beneficial response to everyone based on said rules. A system in which we can be confident that our ardent commitment to the course will lead us to success. Is that really too much to ask?
A lot of people go into a physics degree having never done any computer programming before. However, it is so crucial to scientific research and high profile careers that if there is no introduction to computing in year 1, anyone in the world of science would seriously question the credibility of the degree course.
I took a number of computing-based courses and it made me the computational physicist that I am today. However, I wouldn't have learned nearly as much if I had stuck to the core computing courses only, as that barely prepares one for advanced use of programming in the workplace.
The core stuff? Introduction to Python in year 1, going on to basic calculations and data treatment and simulation in SciPy and Pandas. Introduction to object oriented methods in Python in year 2, simply doing similar things to year 1 but in a new framework. Nothing that I hadn't already seen, at least to a moderate level of understanding.
The elective stuff? Details on the ...more
A new physics student would enrol on a standard physics degree program if they simply wanted an all-encompassing grasp on every corner of the subject, and in most cases, these people make the majority.
However, some universities will also offer degree programs (e.g. Physics with Chemistry, Physics with Astrophysics, Physics with Theoretical Physics) which tailor one's module selection to the associated discipline while maintaining the same number of hours put in (roughly).
Not only does this make your qualification considerably more specialised, it also guides one to make academic decisions in one's best interest, if that is what one intends to pursue. A large proportion of your learning and experience will be weighted in that favour, and that is beneficial, as taking one laser related course does not turn you into a laser scientist.
It can be difficult for a student to judge sometimes whether a certain course is worth taking to suit their academic interests, so why not have ...more
The IOP has a list of subjects which, if covered in its entirety in any undergraduate degree course, qualify any graduated student as an accredited physicist. This includes electromagnetic interactions with matter, advanced quantum mechanics applied to atoms and high energy particles, statistical thermodynamics, and advanced mathematics such as Fourier analysis and vector calculus.
In any good university, one will cover all of this eventually before it's all over, but at my university, it was ALL covered and examined in the first two years, including a comprehensive exam on all previously covered material, leaving the remaining years to be far more advanced and specialised. This also leaves the students fully able to take on very prestigious research placements before they've graduated; an invaluable asset to their academic record.
However, for those who have not the same experience, they may well be learning some crucial core science very late on in their course, which they ...more
In connection with teaching the crucial aspects of modern physics at the start, there are some things that aren't necessarily covered by every institution, and frankly I am astounded that the IOP's list doesn't include the action principle, calculus of variations, and other things that underpin Lagrangian and Hamiltonian Mechanics, and the links to dynamical systems. It is incredibly important, fundamental and versatile, and whether or not one will use a Hamiltonian system directly in one's research, the level of understanding of this form of mathematics is a cornerstone of quantum mechanics and statistical physics, being completely glossed over in cases where it has not yet, if at all, been taught. Not to mention that in combination with tensor algebra it is a very important part of general relativity and quantum field theory. Thus, in most cases this information will be optionally available, but I honestly think everyone should be learning this.
LaTeX is any esteemed scientist's go-to document typesetting programme, which has a countless number of advantages for the sake of implementing equations, tables and figures into scientific writing. Yet, this is something which is barely covered in your typical physics degree. Yes, some places will actively teach it, but many physics students go far through the course either not knowing anything about it or being completely daunted by the prospect of using it. Not only do I think a comprehensive introduction, similar to that in programming, should be given to every physics student at an early stage, but it should be encouraged for submission of assignments such as lab reports, and students should be given advice on which LaTeX distro should be installed based on their requirements. It is so commonplace in the world of science that every physics student should graduate with confidence in their abilities with LaTeX.
Just make LaTeX use mandatory for submission in first year and provide a few tutorials on setup and style. Once you know the bare bones the rest is very easy to pick up on your own; I personally went from 0-60 after about a month of typing up (weekly) math assignments, with no such training.
A lot of scientific nomenclature is, to begin with, very difficult to understand, and in a typical physics course, one is given very little, often inadequate time to mull it over. The impact of this is very clear when one gets on to general relativity courses in one's final year, and half of the student feedback is complaining that they don't understand the notation used in lectures and exercises, which is quite frankly pathetic. The fact is, this complicated form of writing is absolutely necessary to generalise huge sets of equations with a countless number of solutions, or an extended integral across dozens of dimensions. A physicist may well take it for granted, but that may be why it is overlooked this way. It should be taught early to take the pressure off later on, and prepare one for understanding very useful mathematics at an early stage.
Object-oriented programming redefines the programming method; it allows you to organise every variable, every aspect of your calculations according to their class. However, aside from a few courses and modules which utilise it, it isn't really encouraged. A lot of people instantly forget about it once they've crammed in what they needed to know for this one assignment, and perhaps the way around this is to set more tasks which logically make use of it, or better still, to teach it in an object-oriented syntax such as C++.
The thing that bored me the most throughout my time as a physics student was the amount of material which was shown again, months or years after it was introduced. The intent is often to touch up on things that people may have forgotten which are important for the forthcoming topic.
That should be one lecture MAX. But no, even half the course can be devoted to retelling what we've been told already, which is incredibly frustrating when you just want to get on with the new topic. The nature of the physics course means that we work extensively on the topic in our own time, so by the time the new term takes place, we already understand the prerequisite material well enough.
The time we lose because of these cover-ups could be devoted to subject matters which require more thorough explanation and practice, but no, this compromises the efficiency of learning, and it does so throughout the course.
A physics degree means you'll be covering some very advanced mathematical techniques in lectures and do some mathematics by hand, but in practice, when doing this with research and with big data, some of which will have been acquired in the lab, you will be doing it computationally. That is an entirely different game; you may be familiarising yourself with the functionality of a module, or designing one yourself. The amount of hectic practice I had to do just to implement a Fourier Transform to a CMB data subset was absurd, and it would be nice to have had some preparation from the physics course. In fact, numerous students have trouble putting things that can be very simple in theory into computational practice, and while SciPy introductions can be useful, one might need something more vigorous. Of course, teaching it all at once would be unrealistic, so doing lab and computing work, which applies it in this fashion as it's covered in lectures, would constitute a much better and ...more
It shortens all of one's matrix equations to one simple, compact expression, and is so widely used that one might as well get some ironclad instruction with it.