Category: Data

Initial Effects of a $9000 Tuition Hike

It’s been nearly two years since the U.K. government announced radical new tuition plans. From a little under 3300 GBP/year, the government allowed institutions to raise fees up to 9000 GBP. Loans rose to compensate, but grants did not. “Top” universities – essentially, any institution with pretensions to graduate education – all hiked their fees to the maximum; others, sometimes in response to some frankly weird government incentives, kept them a bit lower. Average tuition paid by U.K. students rose

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Just Over the Horizon

Recently I was asked about what I thought the big upcoming challenges – beyond the regular budget stuff – were for universities and colleges. From the shortest-term to the longest-term, my answer was: Not Getting Ahead of the Metrics Game. A perennial topic, but no less important for that. In every recession, governments re-double their efforts to manage the system through metrics. The odds are very strong that government-designed metrics are going to be goofy in the extreme (anyone remember

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Bibliometrics Finale: Age and Size

Today, we use our H-index Benchmarking of Academic Research (HiBAR) to look at the relationship between institutional characteristics and H-index scores. We’ve talked a lot this week about the positive correlation between a researcher’s age and his or her H-index score. But there’s another correlation to watch for: normalized institutional average H-index scores and institutional age. Check it out: Normalized Institutional Average H-Index Score as a Function of Institutional Age The result isn’t wholly clear cut: there are a lot

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Back to Bibliometrics

About two months ago, we did a series on bibliometrics (if you missed it the first time out, you can catch up here), and promised we’d be back shortly with some new results. Well, we’ll those results will be released Wednesday, and we think they’re so interesting that we’ll be spending all week telling you about them. For bibliometrics to be really useful, they need to (a) be able to capture information about both productivity and impact, (b) be easy

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Getting a Global Common Data Set Off the Ground

How could a global common data set (CDS) come into existence? Here are a few considerations: In addition to improving accuracy and comparability, common data sets come into existence for two reasons. The first is to save money by limiting the number of data requests flying in from every yahoo wanting to create his or her own ranking. The second, less obvious reason, is that the creation of an open-access data platform lowers the barriers to entry for new rankers.

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