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Methodology

Consult the complete methodology and analysis of the main results here

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What are university rankings?

University rankings classify universities, allowing them to be compared by concentrating heterogeneous data on their characteristics and results in one indicator. However, although these rankings simplify complexity, they provide a straightforward classification with the advantages and disadvantages that this entails: they offer a more user-friendly assessment for those who do not have the time or the preparation to analyze the performance of a university in depth but they conceal differences between universities that could be of significance.

Given the nature of how they are constructed, transparency and rigour are inalienable principles when creating rankings. Excessive simplification is dangerous and, whenever possible, a ranking system should provide different information on the main missions of universities – teaching, research, and innovation and technological development – allowing the achievements of each institution in each area to be compared. Furthermore, as universities do not always perform equally in the various fields of knowledge, it makes sense that the rankings also allow their performance to be compared in areas of knowledge and specific qualifications.

Constructing a ranking involves a certain amount of subjectivity when selecting variables, and building and weighting indicators. In order to limit the effects of subjectivity, it is important to provide a detailed explanation of the methodology used and allow the user to express preferences for teaching, research or transfer, thus creating a personalized ranking.

What does the U-Ranking project offer?

The U-Ranking project has created a set of Synthetic Indicators of the Spanish University System, taking into account the above-mentioned criteria and following the recommendations of specialized literature and experts on creating indicators.

The U-Ranking project indicators represent four major contributions making it a precise tool which, in addition to being easy to use and access, is useful for managers and experts in higher education, as well as for students and career counsellors alike:

  • Classifying universities according to both the volume of results (U-Ranking Volume) and their performance (U-Ranking), while assessing the effect of university size.
  • Examining the three missions of universities - teaching, research, and innovation and technological development - providing rankings for each area.
  • Offering rankings for various qualifications, facilitating a very useful and user-friendly tool to choose the university in which to study.
  • Allowing users to obtain a personalized ranking by responding to the questions “what to study”, “where” and “what are your preferences for education and research”.

What is the methodology of U-Ranking?

To create a ranking, it is necessary to select variables and manage, homogenize and incorporate diverse data. The complete process followed in the U-Ranking project is explained in detail in the reference document, with a summary below:

  1. Once the relevant variables have been selected and the sources analyzed, the missing values in the data are calculated by an automatic estimation process.
  2. The indicators are standardized so that their magnitude is comparable.
  3. The indicators are weighted and aggregated to create level 1 synthetic indicators in four areas –Resources, Output, Quality and Internationalization - for each of the three dimensions–Teaching, Research, and Innovation and Technological Development-.
  4. The areas of each dimension are weighted and aggregated to create three level 2 indicators: Teaching, Research, and Innovation and Technological Development.
  5. In the case of degree rankings, the user is asked about their preferences regarding the importance of each of these three dimensions.
  6. The three dimensions are weighted and aggregated to obtain one level 3 synthetic indicator, or a final ranking.

What information is used to construct the ranking?

The first two editions of the U-Rankings project analyzed the 48 Spanish public universities. From the 2015 editon private universities have been included with sufficient public information available. In the 2016 edition, 13 private universities have been included. Data is provided by public statistics and information systems.

To assess universities’ activities in each of their large dimensions —teaching, research, and innovation and technological development—, the following four areas have been studied:

  • Resources
  • Output
  • Quality
  • Internationalization

Each of the four areas mentioned above has been analyzed using a series of indicators. For each area, between one and three indicators have been taken into account, depending on the availability and suitability of data, and according to the dimension that is being studied. The following table describes the indicators used, their sources, period and disaggregation.

Teaching
Resources
Indicator and definition Source Period Disaggregation
Faculty member with PhD per 100 students: Faculty member with PhD equivalent to full-time per each 100 students registered in studies of 1st and 2nd cycle (former Spanish degree structure) and in Bachelor’s degrees in centers belonging to the University, Master’s degrees and Doctoral degrees (Bologna’s degree structure) CRUE 2008/09, 2010/11, 2012/13 and 2013/14 Branch of knowledge
Budget / Student: Effective income of the University by number of students registered in studies of 1st and 2nd cycle and Bachelor’s degree (in centers belonging to the University), Master’s degrees and Doctoral degrees CRUE 2008, 2010, 2012 and 2013 University
Faculty member with PhD / Faculty members: Faculty member with PhD equivalent to full-time over total teaching and research staff equivalent to full-time CRUE 2008/09, 2010/11, 2012/13 and 2013/14 University
Output
Indicator and definition Source Period Disaggregation
Success rate: Number of credits passed (excluding transfer, validated and recognized credits) over total credits evaluated SIIU1 2009/10 to 2013/14 Bachelor’s degree group
Evaluation rate: Number of credits evaluated over total credits registered SIIU1 2009/10 to 2013/14 Bachelor’s degree group
Drop-out rate: Students registered in academic year t who, two years after registering in the first year of a degree, abandon it without graduating, over the total number of students registered in year t SIIU1 2009/10 to 2013/14 Bachelor’s degree group
Quality
Indicator and definition Source Period Disaggregation
Attractiveness index - - -
Percentage of postgraduate students: Students registered in Master’s degrees over the total number of students of 1st and 2nd cycle, Bachelor’s degrees and Master’s degrees MECD 2008/09 to 2014/15 Branch of knowledge
Cut-off mark: Mark of the last general group2 student that gained admission to a degree with limited places SIIU 2015/16 Bachelor’s degree
Internationalization
Indicator and definition Source Period Disaggregation
Percentage of foreign students: Non-Spanish students of 1st and 2nd cycle, Bachelor’s degrees and Master’s degrees over the total number of students of 1st and 2nd cycle, Bachelor’s degrees and Master’s degrees SIIU 2009/10 to 2013/2014 Branch of knowlegde
Percentage of students in exchange programs: Spanish Students of 1st and 2nd cycle and Bachelor’s degrees who participate in the ERASMUS programme, over the total number of students of 1st and 2nd cycle and Bachelor’s degrees CRUE 2008/09, 2010/11, 2012/13 and 2013/14 Branch of knowledge
Percentage of students registered in programs imparted in non-official languages - - -
Research
Resources
Indicator and definition Source Period Disaggregation
Competitive public resources per faculty member with PhD: Competitive public resources for undirected research projects, including both projects and complementary actions and ERDF funds, over the total number of faculty members with PhD equivalent to full-time DGICT CRUE 2008 to 2014 Branch of knowledge
Contracts with PhDs, research grants and technical support over total budget: Competitive resources obtained for research staff training, Juan de la Cierva, Ramón y Cajal and support technicians over total effective income DGICT CRUE 2009 to 2014 Branch of knowledge
Output
Indicator and definition Source Period Disaggregation
Citable documents with ISI reference per faculty member with PhD: Documents with ISI reference published per 100 faculty members with PhD equivalent to full-time IUNE (Thomson Reuters) CRUE 2009 to 2014 Branch of knowledge
Total sexenios over possible sexenios: Sexenios obtained over the total possible sexenios for the universities’ tenured research staff. CRUE 2012 and 2013 Branch of knowledge
Doctoral theses read per 100 faculty members with PhD: Doctoral theses read per 100 faculty members with PhD equivalent to full-time MEyCD CRUE 2008 to 2013 Branch of knowledge
Quality
Indicator and definition Source Period Disaggregation
Mean impact factor: Mean impact factor of the publications with at least one author affiliated to the University IUNE (Thomson Reuters) 2008 to 2013 Bachelor’s degree group
Percentage of publications in the first quartile: Publications corresponding to journals in the first quartile of relevance within the Thomson Reuters classification by areas, over the total number of publications belonging to that area IUNE (Thomson Reuters) 2009 to 2014 Bachelor’s degree group
Citations per document: Citations received by each document from the date of publication to the date of data gathering IUNE (Thomson Reuters) 2009 to 2014 Bachelor’s degree group
Internationalization
Indicator and definition Source Period Disaggregation
European or international research funds per faculty member with PhD: Effective income from abroad due to applied research per faculty member with PhD equivalent to full-time CRUE 2008 and 2010 University
Percentage of publications with international co-authorship: Publications with at least one co-author affiliated to a foreign institution over the total number of publications IUNE (Thomson Reuters) 2009 to 2014 Bachelor’s degree group
Innovation and Technological Development
1.For the calculation of the customized rankings is still using information that supplies the CRUE for the courses 2008/09 and 2010/11, 2012/13 and 2013/14 as is ogrece by groups of degree and University.
2. General group: students finishing high school or students graduated in Advanced Vocational Training or foreign students.
3. The faculty members with PhD used for calculating the indicators of Innovation and Technological Development are those in the following categories: Professor, University School Professor, Associate Professor, University School Associate Professor, and Assistant Professor, registered each year in the centers belonging to the public universities. In the case of private universities, faculty members with indefinite contract registered each year are used.
Resources
Indicator and definition Source Period Disaggregation
Income from licenses per 100 faculty members with PhD3: Income generated by the use and exploitation of licenses of the university for each 100 faculty members with PhD IUNE (OTRIs) 2008 to 2013 University
Income from consultancy contracts per 100 faculty members with PhD3: Income from R&D and consultancy contracts and from provision of services per 100 faculty members with PhD IUNE (OTRIs) 2008 to 2013 University
Income from continuing professional development (CPD) courses per faculty member with PhD3: Fees received from registration both for CPD and for the university’s own postgraduate programs (master, specialist and expert) per faculty member with PhD CRUE IUNE (INE) 2008, 2010, 2012 and 2013 University
Output
Indicator and definition Source Period Disaggregation
Number of patents per 100 faculty members with PhD3: Number of national patents granted to each Spanish university by the Spanish Patents and Trade Marks Office per 100 faculty members with PhD IUNE (OTRIs) 2009 to 2014 University
CPD hours per faculty member with PhD - - -
Number of contracts per faculty member with PhD - - -
Quality
Indicator and definition Source Period Disaggregation
Patents commercialized per faculty member with PhD - - -
Internationalization
Indicator and definition Source Period Disaggregation
Triadic patents per 100 faculty members with PhD: Number of simultaneous protections of inventions in different countries obtained through an international patent application, per 100 faculty members with PhD IUNE (OTRIs) 2008 to 2013 University
Income from international contracts per faculty member with PhD - - -
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Consult the complete methodology and analysis of the main results here

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