Share this article on...
Contact Us
- Report errors or inaccuracies topmba@qsnetwork.com
- Contribute articles contribute@qsnetwork.com
- Advertise advertise@qsnetwork.com
Notes on processing data for US universities
The aim of this article is to shed some light on how we have compiled our list of nearly 130 US universities competing on a global level in the Times Higher – QS World University Rankings (WUR) 2008 as well as to provide transparency in how we have derived at student and faculty staff figures.
The aim of this article is to shed some light on how we have compiled our list of nearly 130 US universities competing on a global level in the Times Higher – QS World University Rankings (WUR) 2008 as well as to provide transparency in how we have derived at student and faculty staff figures.
Below are the points that have influenced our decision making process to include a university in the WUR:
• 2007 participants
• Recommendations by third party sources
• Inclusion of institutions ranked in the US News Top National Universities
• The Basic Carnegie Classification System
For the first three points, we cross-checked our initial list of participating universities with the US News Ranking and included institutions which were not on our list. We also referred to last year’s participants and followed up on recommendations by third party sources, such as websites or reports.
The Basic Carnegie Classification System allowed us to focus on doctorate-granting universities, a category that includes institutions which award at least 20 doctoral degrees per year. Hence we were concentrating on the following classification categories: RU/VH: Research Universities (very high research activity), RU/H: Research Universities (high research activity), DRU: Doctoral/Research Universities.
This step is crucial in the context of universities with several campuses. Our objective was to only include campuses, which are research universities or doctoral/research universities. In cases of more than one campus claiming the status of a research university and which are not an autonomous part of the university system, we have collected figures for each campus and added them together in order to arrive at a final figure that represents the university as a whole. We are aware that this may raise concerns, especially in a situation when these campuses are separately accredited, are separate IPEDS institutions, or are separate in the Carnegie listings. The rational behind this decision is to provide an overall picture of the university concerned without focusing on particular locations.
For example, 50% of our evaluation are based upon opinion surveys – 10% from employers with the remainder being from world academics. They are presented with a finite (approximately 600) list of institutions from which to select up to 30 they consider to be excellent in the context of the question they have been asked.
In that context we can’t extend the list indefinitely and we also have to refer to entities that are broadly recognisable and for many US university systems it seems that international audiences relate to the University of X, rather than discerning between the independent parts of the system. Distinguishing between component campuses creates confusion rather than clarity in the minds of our international respondents. To visualise it, a biochemist from Tokyo meets one of the academics from University of X at a conference in Japan – does he identify having met someone explicitly from the A campus or is it the “University of X ” that gets logged in his mind?
As in 2007, the data were taken from the National Center for Education Statistics (NCES) website for all crucial measures in order to represent the institutions as accurately as possible as well as to establish consistency throughout the listings with: Number of Undergraduate Students, Number of Graduate/Postgraduate Students, Number of International Undergraduate Students, Number of International Graduate Students and Number of Faculty Staff referring to Fall 2007.
With reference to the student figures, please find below an example of how we derived at those, which were entered into our school admin system:
http://nces.ed.gov
Data Tools
Peer Tools
IPEDS Dataset Cutting Tool (DCT)
Enter the system at Institution Level
Year from which to select a universe of schools: 2007 / select schools using specific criteria / view data by collection year:
In Race/ethnicity, gender, attendance status, and level of student: Fall 2007 select for all students, full-time and part-time students:
The final figures are presented in a table with following headings:
Faculty staff figures
With reference to the faculty staff figures, we have applied:
In Employees by faculty status, primary function/occupational activity: Fall 2007 we have chosen:
> All employees / Full time / Part time: With faculty status total
>> Primarily instruction total: With faculty status total
>>> Instruction combined with research/public service total: With faculty status total
>>>> Primarily research total: With faculty status total
>>>>> The final result is shown in:
University Rankings
Is anyone aware of any benchmarking exercises for university websites such as the SOCITM one for Local Authorities?
Mark
Add comment