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With all the hype about big data it’s sometimes hard to realise that it’s about more than just data. In fact, it’s real interest doesn’t come from big-ness at all.
The move towards massively open on-line courseware (MOOCs) has the potential fundamentally to change the practice and experience of university. But what does it feel like to study on a MOOC-delivered course?
I’m a little perplexed by the direction of the current discussion over Ireland’s chief scientific advisor.
The shifts in economic power are being mirrored in the university sector, both in education and research. It’s happened before.
Hiring anyone is always a risk, and hiring a new academic especially so given the nature of our contracts. So what’s the best way to approach it?
What the invention of complicated foods tells us about discovery, innovation, and university research funding.
What should the university of the 21st century look like? What are we preparing our students for, and how? And how should we decide what is the appropriate vision for modern universities?
What contributions can computer scientists uniquely make to the latest scientific challenges? The answer may require us to step back and look at how instruments affect science, because the computer is the key instrument for the scientific future.
If you try to do everything, you always end up doing nothing. Which is why Gray’s laws suggest searching for the twenty “big questions” in a field and then focusing-in the first five as the ones that’ll generate the biggest return on the effort invested. So what are the five biggest open issues in programming for sensorised systems?