Methodology

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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, and research and innovation – 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 or research and innovation 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 main missions of universities - teaching, and research and innovation - 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 indicators are standardized so that their magnitude is comparable.
  2. The indicators are weighted and aggregated to create level 1 synthetic indicators in four areas –Resources, Output, Quality and Internationalization - for each of the dimensions –Teaching, and Research and Innovation-.
  3. The areas of each dimension are weighted and aggregated to create two level 2 indicators: Teaching, and Research and Innovation.
  4. In the case of degree rankings, the user is asked about their preferences regarding the importance of each of these dimensions.
  5. The two 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 2020 edition, 22 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, and research and innovation—, 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: Full-time equivalent faculty members and research staff in centers belonging to the University per 100 full-time equivalent students in studies of 1st and 2nd cycle, Bachelor’s and Master’s degrees and students in Doctoral degrees (all of these students registered in centers belonging to the University) SIIU 2012/13 - 2017/18 Branch of knowledge
Budget / Student: Effective income of the University by number of full-time equivalent students in studies of 1st and 2nd cycle, Bachelor’s and Master’s degrees and of students in Doctoral degrees (all of these students registered in centers belonging to the University) SIIU/SABI/WEB 2012 to 2017 University
Faculty member with PhD / Faculty members: Full-time equivalent faculty members with PhD in centers belonging to the University over total full-time equivalent teaching and research staff in centers belonging to the University SIIU 2012/13 to 2017/18 University
Output
Indicator and definition Source Period Disaggregation
Success rate: Number of credits passed by grade students registered in an academic year over total credits evaluated within the same course (excluding transfer and recognized credits) SIIU 2012/13 to 2017/18 Branch of knowledge
Evaluation rate: Number of credits evaluated by grade students registered in an academic year over total credits registered within the same course (excluding transfer and recognized credits) SIIU 2012/13 to 2017/18 Branch of knowledge
Overall dropout rate in Bachelor’s degree studies: Total sum of Bachelor’s degree dropout rates during first, second and third year of studies SIIU 2009/10 to 2013/14 Branch of knowledge
Quality
Indicator and definition Source Period Disaggregation
Percentage of postgraduate students: Full-time equivalent students registered in Master’s degrees over the total number of full-time equivalent students registered in studies of 1st and 2nd cycle, Bachelor’s and Master’s degrees (all of these students registered in centers belonging to the University) SIIU 2012/13 to 2017/18 Branch of knowledge
Cut-off mark: Mark of the last general group2 student that gained admission to a degree with limited places SIIU 2019/20 Bachelor’s degree
Internationalization
Indicator and definition Source Period Disaggregation
Percentage of foreign students: Non-Spanish students of 1st and 2nd cycle, Bachelor’s and Master’s degrees over the total number of students of 1st and 2nd cycle, Bachelor’s and Master’s degrees SIIU 2012/13 to 2017/2018 Branch of knowledge
Percentage of students in international mobility programs: Number of bachelor’s and master’s degree students who study abroad through a mobility program over total number of bachelor’s and master’s degree students SIIU 2014/15 to 2017/18 Branch of knowledge
Research and Innovation
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 full-time equivalent PhD Agencia Estatal de Investigación / SIIU 2013 to 2018 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 and Cajal and support technicians over total effective income Agencia Estatal de Invetigación / SIIU / SABI / WEB 2013 to 2018 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 full-time equivalent PhD IUNE (Thomson Reuters) / SIIU 2013 to 2018 Branch of knowledge
Number of patents per 100 faculty members with PhD: Number of national patents granted to each Spanish university by the Spanish Patents and Trade Marks Office per 100 faculty members with PhD IUNE (INVENES) / SIIU 2013 to 2018 University
Doctoral theses read per 100 faculty members with PhD: Doctoral theses read per 100 faculty members with full-time equivalent PhD SIIU 2013 to 2018 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) 2013 to 2018 Branch of knowledge
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) 2013 to 2018 Branch of knowledge
Citations per document: Citations received per document from the date of publication to the date of data gathering IUNE (Thomson Reuters) 2013 to 2018 Branch of knowledge
Internationalization
Indicator and definition Source Period Disaggregation
Horizon 2020 European research funds per faculty members with PhD: Funding received by the university from EU research funds (H2020 programme) per every 100 full-time equivalent faculty members with PhD European Commission (H2020 Dashboard) 2014 a 2018 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) 2013 to 2018 Branch of knowledge
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