Hello,

(I apologise for the length!)

My career path to this point has been somewhat untraditional. I began teaching in HE the moment I graduated from my undergraduate degree. I then progressed to be a Course Leader over the next couple of years. I hold a BSc in Computing and an MBA. While my MBA was valuable, my core subject area is computing. The university I was enrolled to at the time did not offer an MSc and as funding was available for an MBA, it seemed a good decision.

I'm aware that my career beyond my current position will require me to have a PhD. I also have a genuine desire to complete the work required to obtain a PhD.

Unfortunately, after many months of going around in circles I'm struggling to choose a topic. As an academic, I teach web development which doesn't lend itself to PhD topics very naturally. While I achieved a first class BSc, the teaching wasn't the best and my role as an academic at a different university has highlighted the real lack of fundamental computer science topics in the curriculum I was taught. This, combined with me not completing an MSc, has made the process of finding a PhD topic VERY difficult.

I'm stuck in a position where I feel the expertise I do have in web development can't be applied to a PhD topic and common areas of research in computing (such as Data Science, Artificial Intelligence etc) are far beyond my capabilities.

I'm not one that normally finds situations overwhelming but this is becoming a major strain on my mental wellbeing. I feel as though I'm spending hours and hours reading journals trying to find something I feel is within my range of knowledge (or at least something I can learn within any reasonable period of time).

Does anyone have any experience of being in a similar situation? Any advice?

I've had some topic ideas. However they don't really tickle the taste buds of my supervisors who continue to push me towards topics that feel out of my depth. Some of the ideas I have are being reached heavily so there has also been originality concerns raised by my supervisors.

I'm pretty lost right know ...

Thanks in adv.

Maybe it's a good time to take a step back and fill in the gaps in your undergraduate background in your spare time?
You might only need a few months of going through online courses and videos from the likes of MIT.

What is it you feel you are missing?

Hello,

Thanks for your reply. Firstly, I'd like to apologies for the many grammatical errors in my initial post. It's my own fault for writing so late at night!

To answer your question, pm133, much of the research in Computer Science currently focuses on (or at least involves) data science, machine learning, artificial intelligence or IoT. I have been spending my spare time learning ML. However, I fear this will take at least 12-18 months and even then, I may not be able to reach a sufficient level to complete a PhD in the subject.

I might not be the best person to give advice on computer science. However you won't find a PhD topic by reading a broad range of papers and hoping for inspiration. You need to have a deep understanding of one topic to properly develop a research question and understand what is feasible. A PhD thesis only needs to incrementally find new knowledge and I think you should be looking for small problems that have already been partially explored.

I understand you feel limited by your prior knowledge but I know a scary number of cross-disciplinary PhD students who have done PhDs in subjects unrelated to their Bachelors/Masters. From talking with them, they feel lost at the start but after a couple years working on one topic, they learn what they need to know. You are not expected to be an expert on the field when you start but you just have to be committed enough to follow it through. As most PhD students are not productive until they have already spent 1-2 years working on their project.

Goodluck!

It's normal to feel like you hit a brick wall in the first year of a PhD. There is a 'hump' you need to get over, which is partly about developing your expertise, but also realising what you'd previously considered 'expertise' to, in fact, not be as total a mastery as a layperson expects ;)

It is essential to get over this hump, because students that struggle never really do; they lump together a thesis from general reading and a small user-study, but never develop the expertise and passion for a niche.

To try and give some practical advice, if you want to shape the PhD around web development, you could consider;

- Implementing (with a clear framework/underlying theory) an e-learning, e-health, or e-whatever intervention and assessing it's efficacy.
- Anything on e-learning obviously works well in a Uni setting. It's over-researched for this reason but there are gaps and it's legitimate work.
- Web usability isn't something you can approach naively (lot of work done), but it's not a solved problem.
- Web accessibility - same applies.
- You have a huge gap at the moment on covid + web use/habits!

It's tempting in CS to think programatically harder=better. Sitting up all night for 0.1% performance gain on a stack lit shader, genetic algorithm, or semantic query is very legitimate work, but it's not all CS is, and often understanding users might seem 'easier' intellectually, but it's very demanding work deserving of a PhD.

I'd say the important thing throughout is to understand that making something can be a big part of a PhD (and, to be honest, for a talented developer doing a PhD it's the bit they enjoy), but it's often not the most critical in a research sense - whatever you do should be fundamentally grounded in theory/methodology.