When I began my university career back in the final years of the last century, my role included ensuring that teaching rooms were allotted to fit the number of students enrolled on the module.
I also physically made sure marks were collated and inputted – via Optical Character Recognition (OCR) – into student records. Then, alongside timetables, we printed and placed paper copies in student pigeonholes. No ‘General Data Protection Regulations (GDPR)’ back then.
My morning routine then was different to the typical university employee today. On awakening, I didn’t reach for the most recent paper memo or fax about student admin matters from my bedside cabinet. Yet when I collaborate with teams today and look at what their barriers to progress and current stressors are, I find there are very few who don’t check their work email within the first waking hour of their day. From the outset their day is driven by their emails, social media feeds and the demands, expectations and requests from others. They are at the mercy of their ‘tech’ often before getting out of bed.
Practice and preaching
What universities increasingly suggest that students should practice – in terms of effective strategies for both well-being and using devices and software effectively – is rarely being implemented by the multigenerational workforce in higher education. This is an error. Both university employees and students alike are underusing the ‘assistive’ elements of the technology they work with daily. As students who do utilise assistive software often find, productivity increases once assistive tech is mastered. Ensuring your websites and apps meet the 2018 accessibility regulations can be further achieved by staff and students proficient in the use of assistive software.
Assistive Tech or software such as voice recognition, mind-mapping software and, text-to-speech capability (in written and mathematical language), is increasing at pace (using machine learning, a subset of AI). In utilising this ‘tech’ the productivity of time spent working is increased reducing overspill into time outside of normal working hours. Such tech can help people to avoid spending precious time on ‘workarounds’ including those readers tasked with making manual inputs to data sets that can increasingly be done automatically (by a robot). Effectively using assistive software often avoids the need to ‘workaround’ which leaves time to think, to talk and to innovate (and have a life outside of work).
Although the impact on the well-being of academic, professional support staff and the wider university community is multifactorial, one detrimental factor is likely to be the ‘always on’ practice adopted by many. This ‘working harder for longer’ mentality, as a response to ‘doing more with less’, is often an attempt to meet the increasing demands of university teaching, learning and assessment. There is also the societal pressure to post, document, stream and digitally discuss all aspects of life. There is indeed a place for this in universities. However, the academic community should also be able to enable thinking time and space away from this. Indeed, this is now a crucial skill for us all.
This should not be imposed, but can and should be modelled from the top and mirrored throughout. This ensures that people in roles that are not ‘rapid response’ are clear that, for example, an email sent at 10pm need not be read or responded to until the next working day. This must not just be said but shown by example. Including colleagues in suggested solutions is good practice in these initiatives [and likely boosts your #stepchange progress].
Currently across higher education, people at all levels are experiencing ‘burnout’; oftentimes whilst attempting to bridge the gap’ between what technology *can* deliver (in comparison to outside of education e.g. Amazon, Hotels.com, uber et al) and what current university systems are able to achieve. Particularly impactful is the current rapid and constant pace of change. This often leads to over-committed teams juggling ‘business as usual’ with new projects and ‘new’ ways of working whilst marking, emails, teaching prep, placement planning and other tasks multiply.
University marketing to students and potential employees often suggests a well-oiled machine for living and learning, rather than the complex and clunky academic community often encountered. Is your VLE, records system or university app in the same league of usability as the Facebook, Amazon, Apple, Microsoft, and Alphabet’s Google platforms? If it’s not, then why set up the expectation that it is? Being clear that study and employment in universities brings an exciting challenge – including navigating complicated systems – is important and avoids over-expectation.
We are all aware of technological advances which mean we can now ask a device to order a car to come and collect us and to deliver food to us along with a book (old fashioned kindle). Alexa or Google will also keep our to-do lists, turn the heating up or down, help children with maths homework and recommend where we might eat or stay when visiting a conference or university open day. Indeed, much of this tech was developed within universities.
Nevertheless, even if academics, support practitioners or students are digitally literate and competent in communicating with Alexa or Google, this doesn’t immediately enable their ‘structural literacy’. Structural and emotional literacy are key skills needed to navigate the constantly changing environments within universities today.
The robots aren’t here yet
The ‘strain,’ brought about by people compensating for tech-created challenges, brings to mind a discussion with a pro-vice chancellor about inclusive teaching and learning which included the observation that “universities, in spite of being institutions for learning are not very good at learning themselves”. Until the robots arrive, giving people time may be the best solution. Given what we know about productivity and the importance of time to think, acknowledging the ineffectiveness of back to back meetings and ‘reply all’ communications much could be gained by enabling and modelling time. This would be opportunities that students and employees can use to develop their digital, structural and emotional literacy. This must not just be said, but shown by example.
To remove the tyranny of tech we need to start learning to make it work for us, rather than working for it – not least because we can then apply our (freed up) time to solve some of the human issues that machines simply can’t compute.