Restart – skimpy plan

Well that was an embarrassingly long hiatus. Sorry about that.

I’m now free of my management responsibilities (well most of them, plus a few bits of tidying up) and my main task for the next while is – as I mentioned before – to re-kickstart my research profile. I’ve enjoyed being a manager, but it has been at the expense of my research activity, so I’m now looking forward to a spell of being a researcher.

First job is to set out a two-year plan, based on an assessment of my research profile and strengths. I had an outline of this somewhere but can’t put my hand on it, so in the spirit of getting moving quickly, here’s a quick-and-dirty redraft from memory, in very loose terms:

1. Outputs/writing

  • Journal articles above all else. Need quick wins (rewrite/re-place a couple of bounced joint papers) .
  • Plus churning them out on all the projects I’m involved in.
  • Also stuff that looks across a lot of projects with my management eye, to gain traction and impact.
  • And/or the Theory idea I blogged about before.

2. Bids/income

  • Focus on hard-research stuff, so aim for RCs, foundations, EU in that order. JISC etc low priority unless it has a clear route to something more big-R research, even though it might play to some of my strengths.
  • Develop bid for Big Pet Project, with me as PI, linked to the labs and the Big Lab idea since I have the clearest conception of how that should work.  Could include the U3A people as a particular focus – very neat fit and hits lots of interesting buttons.
  • Work as Co-I on OPAL, plus other bits and pieces as appropriate.

3. Research students

  • Keep up with existing students, think about taking on another one or two, if synergistic – contribute specific project to next recruitment round.
  • Think about EdD supervision, maybe.
  • Fish for an external examiner gig or two.

4. External recognition

  • Get out more. Virtually for sure. Blog more and better. Pick off clever conferences to go to. Be ruthless about what I’m getting rather than just ‘for general background’, even when it’s staff-development funding, not research.
  • Look for external chums to be regular partners, and a (preferably nascent) community to locate work in. (Pick one, or go my usual liminal route between several? One is easier to start with, plough-your-own synthesis might be better long-term strategy to build a chair profile.)
  • Maybe pick up reviewing/journal editing if opportunities come up (JIME, *sigh*).
  • Fish for keynotes (yeah, right – hard to do from a standing start but may be possibilities linked to new labs)

Supporting activities

  • Do systematic reading/lit reviewing to meet specific writing projects, but no general background. But develop some better literature-scanning habits/routines so I don’t miss things coming through that route.
  • Keep reading blogs (fold research-related blogroll in to here and expand?) etc.
  • Keep playing with bits of new technology.
  • Think about how to develop all of this in to something approaching a unified take across a lot of stuff, that can build over time into a huge chair-securing portfolio of Clever Stuff.

Tactics

  • Write little and often. Aim to blog on research at least once a week, and bang out a paper or a bid every month, at least in discussable draft.
  • Work with others/openly – easier with shared projects than my own pet one.
  • Remember to have fun.

Posts to come

Specific projects and how they fit with all this –

  • OPAL/Biodiversity Observatory/Evolution Megalab
  • Knowledge Network 2.0
  • My Pet Project (Big Lab idea).

Author: dougclow

Data scientist, tutxor, project leader, researcher, analyst, teacher, developer, educational technologist, online learning expert, and manager. I particularly enjoy rapidly appraising new-to-me contexts, and mediating between highly technical specialisms and others, from ordinary users to senior management. After 20 years at the OU as an academic, I am now a self-employed consultant, building on my skills and experience in working with people, technology, data science, and artificial intelligence, in a wide range of contexts and industries.

%d bloggers like this: