Aligning education with the workplace
Chris Brignell, Deputy Director
Last week the Observatory hosted Ayse Bilgin, past-president of the International Association for Statistics Education and incoming vice-president of the International Statistical Institute. Over lunch we discussed the artificial divide in Higher Education between ‘research and teaching’ staff and ‘teaching-focussed’ staff. The former are under pressure to publish papers and get grant income, while simultaneously squeezing in teaching; meanwhile the latter have higher teaching loads while trying to find time for pedagogical research. Inevitably both groups can be forgiven for thinking the grass looks greener on the other side.
However, a university’s desire to label staff can create bizarre situations. Suppose a PhD student wants to research maths education. The most appropriate supervisor may be a ‘teaching’ staff member, but some universities prevent ‘teaching’ staff members from supervising research. In other cases, a university may insist the student is registered in the education department, but that creates problems if supervisors are in the maths department and fall under a different cost centre. Sometimes, it seems, our desire to label people or things into neat boxes creates problems for ourselves.
The same might be said for our university teaching. It’s organisationally or conceptually easier if we separate the teaching of ‘theory’ from the teaching of ‘practice’. Most university maths courses seem to have modules labelled ‘Mathematical modelling’ and ‘Professional skills’ or similar. Does this unintentionally imply that mathematical modelling is not a professional skill of a mathematician? Or that it is possible to be a first-class professional mathematician without any knowledge of mathematical modelling?
Of course, when students graduate and enter the workplace, they will inevitably need to combine the theory and practice. Theory is of less value if it can’t solve a problem, and problems are harder to solve without the relevant background knowledge. And yet whenever it is proposed that students do more project work, some mathematicians will throw their arms up in disgust because, they claim, it leaves less teaching time for the ‘curriculum’.
Ayse presented a seminar on aligning statistics education with today’s workplace needs through project work. She argued that a statistics project is an essential component in ensuring that students have mastered communicating statistical findings in a non-technical manner suitable for a general audience. One hallmark of her teaching is students working on real client projects with messy data and ill-defined research questions. Preparing a data set for analysis, analysing data and communicating results are all essential skills for finding employment as a statistician and yet theoretical modules will only focus on the middle element.
Whenever I do statistical consultancy work for industry a lot of time is spent deciphering what the client actually wants, which is particularly ‘fun’ when the client doesn’t know themselves or hasn’t understood what is possible with the data. The actual ‘fun’ part, coming up with a statistical solution, often doesn’t conform to the neat ‘textbook’ answers found in theoretical modules either.
Perhaps we need to rethink the divide between ‘theory’ and ‘practice’, and the divide between ‘teaching and learning’ and ‘research’. Perhaps we should heed Ayse’s call for students to be considered apprentices, where novices begin their journey on becoming experts under the mentorship of their lecturers. Students may find project-based learning daunting at times, but Ayse reports they value the experience gained, improve their communication skills and, whisper it quietly, improve their knowledge of theory too.
Author information
Chris is the Deputy Director of the Observatory and an Associate Professor of Statistics in the School of Mathematical Sciences.
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